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      Natural Disaster SurveT Report






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             G74
             1994











                                                    Property of CSC Library
             noaa

       

                         


        

            


       Natural Disaster Survey Report

               
       The great Flood of 1993                                       



       February 1994


                                              US Department of Commerce
                                              NOAA Coastal Services Center Library
                                              2234 South Hobson Avenue
                                              Charleston, SC 29405-2413


       U.S. Department of Commerce
       Ronald H. Brown, Secretary

       National Oceanic and Atmospheric Administration
       Dr. D. James Baker, Administrator


       National Weather Service
       Dr. Elbert W Friday, Jr., Assistant Administrator
                                         
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          rushed past the Gatei,\,,Y\, Arch in St. A    -1 second.
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                   GUISH - Christina Hein, 24, weeps as AW.                            Iskace
               df-trino the President's visit to a water-cl"r                          WI Ricloc
               Mall on July -14. 1 lein, ivho is fron-I Des Aff                            It, \ \,c
               need help."






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              OVERWHELMED - Aerial vic", of water works plant (it
                                                   - 7vq - ` I- I.. - C"4`






              West Des Mohics, IOWa, 011 JLII@' 17, 1997).






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                  SURROUNDED           -1   SLIII HIL1111illaICS HIC CUrrent of the N issi; i  -.,Nlvel,
                                                                                          '. P-Pj-' I            I
                  flmvin- thrOL1011 a I-CSICIC[Itial al-Ca Of'\/,IlIIICVCI-, Illinois. The town df Sl@,Out 900-
                  last Flooded in 1947, before a levee ivas bUill.

























                                                  PROPHETIC - Floodwater from the
                                                  Missouri River at St. Charles,
                                                  Missouri, on July 21, 1993.










                         ridge West Of Columbia, South Ddkotd, has a long VVO@-
     ANN70 to s                       -iis -balfmile or-,@e of-I
                _-pati the gap across tl                   -32L '8

                                                                  CLOSED - The Lou Fusz Ford
                                                                  dealership in the Chesterfield
                                                                  Valley of St. Charles, Missouri,
                                                                  was one of 500 businesses
                                                                  inundated when a Missouri
                                                                  River levee failed..







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          ,d,,.A%`UGEE    A fci@vn inches across a sx,\,aniped MiSSOUri River levee fii St. Charles COUnty,
                               I
           N/tisSOUri, in JLII\I. While deer, raccoons and other wild animals fled flooded botton-fland,
            egrets and other norn-ialf\ scarce ivadh    birds Oegan reappearing in the river's recla.i,med
          ,@@floocl pjain.







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                      RECAPTURED -
                      Kaskaskia Island, Illinois,
                         =u, reclaim one of
                              p
                               igs from along
                              [email protected] levees in late July
                                 Qkk off of rooftops and off
                                           Dan
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                                                     CONSTERNATION -
                                                     Larry Katz braves fast
                                                     moving flood waters
                                                     to save his cat, Tom,
                                                     in West Des Moines,
                                                     Iowa. A dike holding
                                                     back a nearby river
                                                     failed during the
                                                     night, making Katz
                                                     dash hastily for
                                                     higher ground. Tom
                                                     was left behind in
                                                     the confusion and is
                                                     shown being rescued.






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                  Transportation

                  SNAGGED - Flood. waters
                  scooped Up two plaiies al
                  the Spirit Of St. LOUIS
                  Airport iii Chesterfie.1d,
                  M'ISSOLiri.






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                WASHOUT        A Burlington Northern Railroad
                manager walks on granite roadbed material washed
                out from under rails by flood waters near Rock Port,
                Missouri.



























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            LEADER -A
                          IjiFII'm leads trxc north into Webster,     c-?h Dakota, alona:l malmm.
                        . - - 111p@                                                   0
            Highway      t@@,k%Firsuy County The road was closed fo   wo i,\,e(*s due'to hioh mumt
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                                           STALLED     MUlticolored bar-es
                                           Stalled iii the Mississippi River near
                                           Portage des SiOLIX, Nlissouri, wait
                                           for Hood waters to recede.












                                 DEFIANT -
                                 I-JI klacarthy checks his crew's hanchwork near Lemay, Miss









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                                                              0
                                                   Spirit


                     WISHFUL - A painted
                                    rth of the
                      sentiment no
                  Missouri Botanical Garden
                       proves that citizens of
               St. Louis' high and dry center
                         thinking of residents
                     are
                       to the north and south
                              of its flood wall.


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                                             NO

                                                                                                           AIL










                                                                                e in e r's
                                                 sandbags i-narks Mart
                MESSAGE - A line %,Nritten in            11 ty, 1\4iSSOUH.
                I-Iome on Iffrig Road in St. Charles COLIII











             BATTLEGROUND - McMbcrs of the loixa Nationa[ GUard                             Now
                                      a levee along [lie Des X/loines River at.,
                                   011    Oil jLIl)' -17,1995-
                                       US






           ..........









































             SCRAIMLING - A barge crane strLIg les to gouge a hole in a
             levee large C1101-1all to make the Army Corps Of Engineers' last-
             ditcli p1dil to save Prairie dLi Roclier, Illinois,.work. flie city was
             sparred.







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         RIPTIDE     The Alississippi River drives dwedge of water thrOUgh the   Fountai'n-,Creek
   @4"VV-T-' jUS1 north of Vali-neyer, Illinois. Residents, National GUard troops and vol'Urlteers   4
       AM 101-Ight for 24 days to reinforce it.















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                                                                                     THWARTED                                A fe", lonely stalks peck above                                                   the
                                                                                      Missouri River from Jerry I luber's corn fields.
















                                                                               er reveals its forri-rer.'
                                   power in the                            r trucks near 1-liahway W@ii
                                                                                             0
                                   east of West;                               had moved the x7etuctes to
                                   what he tho




















                                                             MAROONED-Aii illldiid SCa SU I I 0111111iL,
                                                             a Glriii ill iiortl-i St. Cliarics Cowit),,
                                                                                          5
                                                             N'liSSOLII-i, III Cdl-l)'jLIl\', 199). EVC11 GICIIINIVIP-
                                                             0
                                                                 -1i()ll (')I-OLIIld %,\,(,rc hurt as discases,
                                                              [l I
                                                             %\'CCds"lIld il"ISCCIS IIOLII-iSll('(1 ill 111C
                                                             sOdkcd soil aild moist air.












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                                                  r          AWASH - A farm near Winfield,

                                          -7E
                                                             Missouri, gradually loses more and
                                                             more of its crop to the Mississippi
                                   77711777"                 River in July.






               People/Impact














                 CONSOLATION -The Rev. Donald E. Rau, pas                         ricis of,,
                 Portage des SiOLIX, N/lissouri, catches a ride acr
                                                                                          11 lvt -A- the
                                                                                             h6 fl
                 of Coast Guardsmen Tom Jasina Qeft-) and Bill
                 crest, Rau carne to say Mass for 20 Darishiont@o@@                       rk 'A-114rch.


                                                                         MA Porta0e des Si67LIX, N/liSSO'Llri,
                                                                      s s i ;ti R-      ill continue to I-'
                                                                            pp I , I vdqw       I         Ise,
                                                   forcing her to leave her home.
                                                                        wf-






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                                                                                  67








                                    -n,'Lenk peeks into his Mooded (garage in
                $I  Monr4c, Assoqri, in late July 1993.







                                                           OLK



                            CONTRAST -
                    Landsat images of the
              St. Louis, Missouri area, and
            the confluence of the Illinois,
                Mississippi, and Missouri
               Rivers. The top image was
                  acquired on July 4, 1988
                 during a severe drought.
                   The bottom image was      ap  is, P93
               acquired on July 18, in the
              midst of The Great Flood of
                1993. Vegetation is green,
             bare soil appears as tan, and
                    white areas are cloud
                                formations.
                                                                                                    T,



                                                                                   A
                                                                                     4
















































                                                                                         :7



           INTERSECHON - Aerial mosaic taken by NOAA aircraft on July 29,1993, showing the
           confluence of the Illinois (upper-left) and Missouri Rivers (bottom-center) with the
           Mississippi River. Metropolitan St. Louis is visible to the left of the Mississippi River in the
           lower-right.





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                                                                  BOAT RAMPS
                                                                  Kansas City's interstate
                                                                  system was
                                                                  interrupted by the
                                                                  floodwaters.






                    Acknowledgements

               We would like to acknowledge the gracious cooperation of the many sources listed below
               in providing photos used in the preceding section. In the case of copyrighted pieces, they
               are reprinted with permission. Except for photos explicitly identified as being provided by
               Federal government agencies, all photos are copyrighted and may not be reproduced
               without permission.

               We would especially like to thank the St. Louis Post-Dispatch for allowing us to draw from
               their publication, High and Mighty: The Flood of '93. This single source accounted
               for more than half the photos included in this section. Copies of High and Mighty can
               be obtained from Andrews and McMeel, 4900 Main Street, Kansas City Missouri 64112.
               The following list identifies the sources of the preceding photos.

                    Front Cover                                                                       spirit
                    SWEPT AWAY              Jim Rackwitz, St. Louis Post-Dispatch                      DEFIANT                  Wes Paz, St. Louis Post-Dispatch
                    OVERPOWERED             Kevin Manning, St. Louis Post-Dispatch                     WISHFUL                  Jerry Naunheim, Jr., St. Louis Post-Dispatch
                    TENUOUS TIE             Jim Rackwitz, St. Louis Post-Dispatch                    MESSAGE                  Sam Leone, St. Louis Post-Dispatch

               Cities                                                                                  Levees
                    WATERWAY                Kevin Manning, St. Louis Post-Dispatch                      BATTLEGROUND             Paul Griffin, Department of Defense
                    SWAMPED                 Dan Ipock, Kansas City Star                              SCRAMBLING               Jerry Naunheim, Jr., St. Louis Post-Dispatch
                    SUBMERGED               John Sleezer, Kansas City Star                              RIPTIDE                  Scott Dine, St. Louis Post-Dispatch
               Water, Water, Everywhere                                         
                                                                                                     Agriculture
                    ENGULFED                Scott Dine, St. Louis Post-Dispatch                        THWARTED                 Sam Leone, St. Louis Post-Dispatch
                                                                                                       TOSSED                   Wes Paz, St. Louis Post-Dispatch
                Not a drop to drink                                                                    MAROONED                 Wayne Crosslin, St. Louis Post-Dispatch
                    ANGUISH                 Jeffrey Carney, Des Moines Register                        AWASH                    Scott Dine, St. Louis Post-Dispatch
                    DRAINED                 Jeff Beiermann, Associated Press                       People/Impact
                    OVERWHELMED             Paul Griffin, Department of Defense
                                                                                                       CONSOLATION              Jerry Naunheim, Jr., St. Louis Post-Dispatch
               Inundated                                                                             EVICTED                  Jerry Naunheim, Jr., St. Louis Post-Dispatch
                    SURROUNDED              Scott Dine, St. Louis Post-Dispatch                        CRUISING                 Anne Ryan, USA Today
                    PROPHETIC               Tom Dietrich, NOAA                                         RIVER VIEW               Jerry Naunheim, Jr., St. Louis Post-Dispatch
                    ISOLATED                Frank Robertson, Aberdeen American News               From On High
                    CLOSED                  Pat Slattery NOAA
                                                                                                       CONTRAST                 Earth Observation Satellite Company
               All Creatures Great and Small                                                          INTERSECTION             NOAA
                    REFUGEE                 Sam Leone, St. Louis Post-Dispatch                         CONFLUENCE               Surdex Corporation
                    RECAPTURED              Odell Mitchell, Jr., St. Louis Post-Dispatch               BOAT RAMPS               Topeka Capital Journal
                    CONSTERNATION           Jeffrey Carney, Des Moines Register                    Back Cover
               Transportation                                                                          BEACON                   Jim Rackwitz, St. Louis Post-Dispatch
                    SNAGGED                 Larry Williams, St. Louis Post-Dispatch
                    WASHOUT	              Janet Walsh, Omaha world-herald
			  Leader			  John stennes, grand forks herald
			  Stalled                 Renyold ferguson, St. louis post-dispatch















                    WASHOUT                 
                    LEADER                  
                    STALLED                 



                                The graphics design and layout support for the cover and photographic section of this report was provided
                                   by Sue E. Dietterle, Visual Information Specialist, Office of Public Affairs, NOAA, Rockville, Maryland.
 








                                               TABLE OF CONTENTS



                                                                                                               E4@
              Prologue  ..................................................                                       Vill

              Preface   ..................................................                                        ix


              Foreword    ..................................................                                        x

              Disaster Survey Team Membership and Itinerary          .........................                    xi
                     1. Disaster Survey Team and Support Personnel            ....................                xi
                     2. Disaster Survey Team Itinerary         .............................                     xiv

              Executive Summary       ..........................................                                 xvii

              Abbreviations and Acronyms         .....................................                           xxi

              Chapter I - General Description of the Event and Its Impact           .................            1-1
                     1. 1 Introduction    .........................................                              1-1
                     1.2 Interagency Flood Response        ...............................                       1-3
                     1. 3 Impact of the Flooding      ..................................                         1-4

              Chapter 2 - Major Lessons Learned and Opportunities for the Future              ...........        2-1
                     2.1  Introduction    .........................................                              2-1
                     2.2  Scope and Benefits of the National Weather Service Response           ..........       2-1
                     2.3  Advanced Hydrologic Prediction System          .......................                 2-3
                          2.3.1 National Weather Service River Forecast System           ..............          2-3
                          2.3.2 National Weather Service Modernization          ...................              2-7
                          2.3.3 Partnerships with Cooperators         .........................                  2-9
                          2.3.4 Water Resources Forecast System          ......................                  2-11
                     2.4 Near-Term Hydrologic Outlook and Needs            .....................                 2-16

              Chapter 3 - Hydrometeorological Setting          .............................                     3-1
                     3.1  Introduction    .........................................                              3-1
                     3.2  Meteorological Analysis     ..................................                         3-3
                          3.2.1 Antecedent Conditions        ..............................                      3-5
                          3.2.2 Circulation Patterns During The Great Flood of 1993           ...........        3-7
                          3.2.3 Rainfall Patterns During The Great Flood of 1993           ............          3-11
                          3.2.4 Possible Causes of 1993 Midwest Heavy Precipitation           ..........         3-15
                     3.3 Hydrologic Analysis       ...................................                           3-18
                          3.3.1 Antecedent Conditions and Hydrologic Setting            ..............           3-18



                                                                iii









                          3.3.2 Review of Major Flooding      ...........................                  3-21
                              3.3.2.1   Major Flooding in June  .........................                  3-24
                              3.3.2.2   Major Flooding in Early July    .....................              3-25
                              3.3.2.3   Major Flooding in Late July  ......................                3-25
                              3.3.2.4   Flash Flooding  ..............................                     3-29
                              3.3.2.5   Water Control Structures    .......................                3-30
                          3.3.3 Future Flood Potential     .............................                   3-32

               Chapter 4 - Hydrologic and Hydraulic Forecast Methodology          ................         4-1
                     4. 1 Introduction  .........................................                          4-1
                     4.2 Physical Description of Major River Basins Affected by
                          The Great Flood of 1993     .................................                    4-1
                     4.3 River Forecasting Overview     ...............................                    4-4
                          4.3.1 National Weather Service River Forecasting System       ............       4-5
                                 4.3. 1.1 Runoff    ..................................                     4-7
                                 4.3.1.2 Rating Curves and Tables    .......................               4-9
                                 4.3.1.3 River Routing     .............................                   4-11
                                 4.3.1.4 Reservoir Operations   .........................                  4-12
                     4.4  Current Forecast Methodology at the North Central and Missouri Basin
                          River Forecast Centers    .................................                      4-12
                     4.5  Weather Service Offices with Hydrologic Responsibilities     ............        4-13
                     4.6  Forecasting Challenges During The Great Flood of 1993        ............        4-15
                          4.6.1  Data Input    ....................................                        4-15
                          4.6.2  Rating Curves . . p  ...............................                      4-16
                          4.6.3  Flood Routing    ..................................                       4-17
                          4.6.4  Reservoir Effects    ................................                     4-17
                          4.6.5  Levee Effects   ...................................                       4-18
                          4.6.6  User Interaction with Forecast System     ...................             4-19
                     4.7  Modernized RFC/WSFO Hydrologic Forecast Methodology           ...........        4-21
                          4.7. 1 Input  ........................................                           4-21
                          4.7.2 Modeling      .....................................                        4-22
                          4.7.3  Human Interaction with the Forecast System     ................           4-25

               Chapter 5 - Data Acquisition, Telecommunications, Facilities, and Computer Systems          5-1
                     5. 1 Introduction  .........................................                          5-1
                     5.2 Data Acquisition    ......................................                        5-2
                          5.2.1  Cooperative Observer Network      .........................               5-2
                          5.2.2  Automated Systems    ................................                     5-4
                                 5.2.2.1 Data Collection Platforms   .......................               5-4
                                 5.2.2.2 Limited Automatic Remote Collectors       ...............         5-5
                                 5.2.2.3 Telemarks/Talkamarks      .........................               5-8
                                 5.2.2.4 Backup Observers for Automated Gages        ..............        5-9
                          5.2.3 Radar Data     .....................................                       5-9




                                                             iv









                             5.2.4    Other Data Sources        ...............................                                 5-13
                                      5.2.4.1   Satellite Information       . . . . . . . . . . . . . . . . . . . . . . . . .   5-13
                                      5.2.4.2   Quantitative Precipitation Forecasts          . . . . . . . . . . . . . . . .   5-14
                                      5.2.4.3   Alert Systems       .............................                               5-14
                                      5.2.4.4   Skywarn Spotters        ...........................                             5-15
                                      5.2.4.5   Streamflow Measurements             .....................                       5-16
                                      5.2.4.6   Stranger Reports         ...........................                            5-17
                                      5.2.4.7   Airborne Snow and Soil Moisture Survey                  . . . . . . . . . . .   5-18
                       5.3   Telecommunications          ...................................                                    5-19
                       5.4   Facilities    ..........................................                                           5-22
                       5.5   Current Hydrologic Forecast System Capabilities and Limitations at
                             the RFC and Hydrologic Service Area Offices                  ..................                    5-23
                             5.5.1 Current Hydrologic Hardware/Software Systems at the RFC                           .....      5-23
                             5.5.2 Current Hydrologic Hardware and Software Systems at
                                      the HSA Offices        .................................                                  5-25
                       5.6   Modernized Hydrologic Forecast System Capabilities at the RFC
                             and HSA Offices         .....................................                                      5-25
                             5.6.1 Modernized Hydrologic Forecast System Capabilities at
                                      the RFC      ......................................                                       5-25
                             5.6.2 Modernized Hydrologic Forecast System Capabilities at
                                      the HSA Offices        .................................                                  5-26


                Chapter 6 - Warning and Forecast Services                  ...........................                          6-1
                       6.1   Introduction     .........................................                                         6-1
                       6.2   Responsibilities of River Forecast Centers            .......................                      6-1
                       6.3   Offices with Hydrologic Service Area Responsibility                 ................               6-2
                       6.4   Hydrologic Services for the Upper Mississippi River Basin                   ............           6-4
                             6.4.1 Overview of Forecast Products               .........................                        6-4
                             6.4.2 Analysis of Selected Hydrologic Forecasts for the
                                      Upper Mississippi River          .............................                            6-9
                       6.5   Hydrologic Services for the Missouri River Basin                .................                  6-13
                             6.5.1 Overview of Forecast Products               ........................                         6-13
                             6.5.2 Analysis of Selected Hydrologic Forecasts for the Missouri River                      ...    6-15
                       6.6   Hydrologic Services for the Red River of the North                  ...............                6-17
                             6.6.1 Overview of Forecast Products               ........................                         6-17
                       6.7   River Forecasts and Use of Predicted Precipitation               ................                  6-17
                       6.8   General Analysis of Forecast and Warning Services                ................                  6-19
                       6.9   Case Studies     ........................................                                          6-26
                             6.9.1 Case 1: Des Moines, Iowa, Flooding of July 9-11, 1993                       ........         6-27
                             6.9.2 Case 2: Mississippi River Flood at St. Louis                  ...............                6-39

                Chapter 7 - Coordination and Dissemination                  ..........................                          7-1
                       7.1 Intra-agency Coordination             .................................                              7-1
                       7.2 External Coordination           ...................................                                  7-3



                                                                         v










                      7.3 Media Contacts      .......................................                         7-7
                           7.3.1 National Weather Service Services to Media        .................          7-7
                           7.3.2 Other Agency Media Contacts         ........................                 7-10
                      7.4 Direct User Services     ...................................                        7-10


                Chapter 8 - Preparedness and User Response          ..........................                8-1
                      8.1  Introduction   .........................................                           8-1
                      8.2 Internal Preparedness     ...................................                       8-1
                      8.3  External Preparedness    ...................................                       8-2
                      8.4  Public Awareness of and Response to National Weather Service River
                           Forecast Services   ......................................                         8-4


                Chapter 9 - Summary of Findings and Recommendations            ...................            9-1
                      9.1  General Description of the Event and Its Impact (Chapter 1)       ...........      9-1
                      9.2  Major Lessons Learned and Opportunities for the Future (Chapter 2)        ......   9-1
                      9.3  Hydrometeorological Setting (Chapter 3)      .......................               9-4
                      9.4  Hydrologic and Hydraulic Forecast Methodology (Chapter 4)         ...........      9-5
                      9.5  Data Acquisition, Telecommunications, Facilities, and Computer Systems
                           (Chapter 5)    .........................................                           9-7
                      9.6  Warning and Forecast Services (Chapter 6)      .....................               9-16
                      9.7  Coordination and Dissemination (Chapter 7)       ....................              9-21
                      9.8  Preparedness and User Response (Chapter 8)       ....................              9-26


                Appendix A - Disaster Survey Team Contacts         .........................                  A-1
                      A. 1 National Oceanic and Atmospheric Administration/National Weather Service           A-1
                      A.2 U.S. Army Corps of Engineers        ............................                    A-2
                      A.3 Emergency Management Agencies           ..........................                  A-3
                      A.4 News Media        .......................................                           A-4
                      A. 5 Others    ...........................................                              A-5


                Appendix B - Precipitation Forecasting       .............................                    B-1
                      B. 1 Introduction   ........................................                            B-1
                           B. 1. 1 Types of Precipitation Forecasts    .......................                B-1
                      B.2  Quantitative Precipitation Forecasting    ........................                 B-2
                           B.2.1 Quantitative Precipitation Forecast Verification Scheme       . . . . . . . .B-4
                           B.2.2 Case Studies     ...................................                         B-5
                                   B.2.2.1  Review of the June 17-19 Rainfall Event      ............         B-7
                                            B. 2.2. 1. 1 Synoptic Discussion   ..................             B-7
                                            B.2.2.1.2 Forecast and QPF Discussion        ............         B-7
                                   B.2.2.2  Review of the July 4-9 Rainfall Event     ..............          B-10
                                            B.2.2.2.1 Synoptic Discussion      ..................             B-10
                                            B.2.2.2.2 Forecast and QPF Discussion        ............         B-11



                                                               vi









                                B.2.2.3 Review of the July 21-25 Rainfall Event      ............        B-15
                                         B.2.2.3.1 Synoptic Discussion     ..................            B-15
                                         B.2.2.3.2 Forecast and QPF Discussion       ............        B-16
                         B.2.3 Summary and Conclusions on Quantitative Precipitation Forecasts
                                and Models     ...................................                       B-19
                   B.3. Hydrologic Analyses of Selected Quantitative Precipitation Forecasts     .....   B-21
                         B.3.1  State-scale Comparison of Quantitative Precipitation Forecasts and
                                Observed Precipitation   .............................                   B-22
                         B.3.2  Detailed Comparison between Quantitative Precipitation Forecasts
                                and Observed Precipitation for Iowa     ....................             B-25
                         B.3.3  Comparison between Quantitative Precipitation Forecasts and
                                Observed Precipitation for Subbasins Above Des Moines       ........     B-27
                   B.4. Monthly and Seasonal Precipitation Outlooks       ...................            B-28
                   B.5. Summary and Conclusions       ...............................                    B-32

             Appendix C - Use of Satellite Data during The Great Flood of 1993         ...........        C-1
                   C. 1  Geostationary Satellite Imagery   ............................                   C-1
                   C.2   Polar-orbiting Satellite Imagery  ............................                  C-12
                   C.3   Soil Wetness Index     ...................................                      C-13
                   CA    Suggestions for Future Study of Satellite "IFFA-derived" Precipitation
                         Estimates    .........................................                          C-16
                   C.5   Suggestions for Future Study of Soil Wetness Index      ...............         C-16
                   C.6   References    ........................................                          C-17

             Appendix D - Locations with New Record and Near-record Stages            ............        D-1

             Appendix E - Weather Service Forecast Office Product Issuance Summary            .......     E-1

             Appendix F - Analysis of Selected Hydrologic Forecasts       ...................             F-1
















                                                            vii









                                                       PROLOGUE




               The U.S. Department of Commerce's National Oceanic and Atmospheric Administration
               (NOAA), through the National Weather Service (NWS), has broad Federal responsibility to
               provide to the public severe storm and flood warnings and weather forecasts, as wen as river
               flow and water resource forecasts. Timely and accurate forecasts and warnings of river and
               weather conditions are critical to protect life and property and to help support the Nation's
               economic and environmental well-being.

               The Great Flood of 1993 constituted the most costly and devastating flood to ravage the United
               States in modem history. This disaster survey report on The Great Flood of 1993 that struck the
               Upper Midwest identifies opportunities to improve NOAA's weather and flood forecast and
               warning systems, not only for the affected region but also throughout the Nation.            These
               improvements to NOAA's environmental prediction capabilities will: (1) advance the agency's
               overall contributions to environmental services, (2) expand the payback on current investments,
               and (3) improve and/or extend the benefits to many more segments of the public. An enhanced,
               modernized hydrologic forecast and warning system will help to achieve several of NOAA's
               goals and objectives as outlined in the 1995-2005 Strategic Plan that specifically include:

                       1.     Reducing fatalities and injuries due to hazards from weather and floods,

                       2.     Improving the flow of more accurate environmental data and predictions to
                              the public,

                       3.     Enhancing the ability of planners to use hydrologic forecasts in the range
                              of days to months,

                       4.     Providing better information for management of fi-esh water resources,

                       5.     Preventing avoidable damage to private, public, and industrial property
                              over land, in coastal areas, and along rivers, and

                       6.     Improving efficiency, reliability, and savings in industry, transportation,
                              agriculture, and hydro-energy systems.

               Although The Great Flood of 1993 has caused devastating human, environmental, and economic
               impacts, the lessons learned will guide us in providing improved services and benefits to the
               Nation in the future.




               D. James Baker
               Under Secretary for Oceans and Atmosphere
                 and Administrator                            viii









                                                    PREFACE




             The size and impact of The Great Flood of 1993 was unprecedented. Record river stages,
             areal extent of flooding, persons displaced, crop and property damage, and flood duration
             surpassed all floods in the United States in modem times. During the event, 95 forecast
             points in the Upper Midwest exceeded the previous floods of record, many by 6 feet or
             more. Approximately 500 forecast points on major rivers and tributary systems exceeded
             flood stage at some time during The Great Flood of 1993.

             Throughout the event, the NWS generated and issued many river and flood forecasts and
             distributed numerous products to the public as well as to various Federal, state, and private
             agencies across the affected region.    NOAA routinely conducts a survey of each major
             hydrometeorological natural disaster to assess thoroughly all aspects of its forecast and
             warning system including data collection and assimilation, forecast product creation and
             dissemination, and, ultimately, effective user response.

             A NOAA disaster survey team was formed and initially met in Minneapolis, Minnesota, on
             Sunday, August 22, 1993. The team surveyed all aspects of the weather and flood warning
             and forecast systems--from data acquisition to user response--to determine the effectiveness
             of the NWS during the flood and to recommend any required improvements. The survey
             team interviewed more than 120 individuals representing more than 60 Federal, state, and
             private organizations across the flood-stricken region.

             The consensus of opinion was clearly that the NWS provided exceptionally good services
             throughout this unprecedented event. As the team visited the many NWS field offices that
             provided hydrologic warning and forecast services to the flood-stricken area, the unparalleled
             human effort by NWS personnel became conspicuously apparent. NWS employees worked
             long hours to provide high-quality forecast products to the Upper Midwest during the
             prolonged flood event.     The timely information contained in NWS forecast products
             dramatically helped to minimize the loss of life and property. Special thanks are due to the
             NWS employees whose conscientious efforts and dedication to excellence provided
             outstanding service to the Nation during The Great Flood of 1993.

             This report summarizes 106 findings resulting from the survey team's investigation as well as
             the associated recommendations for improvement where deficiencies were found. Relevant
             findings and recommendations are contaffied in each chapter. A summary of all 106 findings
             and recommendations is contained in Chapter 9.



             Diana H. Josephson
             Deputy Under Secretary for Oceans and Atmosphere
               and Team Leader
                                                          ix









                                                     FOREWORD




               The NOAA disaster survey team, with the support from many NWS offices, assessed the
               impact of The Great Flood of 1993 on the Nation and on the NWS itself. Severe flooding
               began in the Upper Midwest before March 1993 and continued through November 1993.
               The massive flooding in the region, however, occurred principally during June, July, and
               early August.

               In August and September, after the most devastating flooding receded, the survey team
               visited much of the nine-state region affected by the disaster. The team visited NWS offices
               that provided flood warning services to the affected region. It interviewed many Federal,
               state, local, and private officials, as well as print and broadcast media representatives, from
               more than 60 different offices across the region.

               This report summarizes 106 findings and recommendations that, when implemented, will
               improve the NWS hydrologic forecast services for the Nation in the future. The NWS will
               implement these recommendations whenever possible. Additionally, we will systematically
               track the implementation status of all appropriate recommendations to capitalize on the many
               lessons learned from The Great Flood of 1993.


               The survey team deserves thanks for compiling the data and information and for preparing
               this report. The U.S. Army Corps of Engineers, the Federal Emergency Management
               Agency, and the Illinois State Water Survey deserve special thanks for providing expert
               scientists who served on the disaster survey team and who contributed valuable sections to
               this report. Additionally, I express the special gratitude of the NWS to the many Federal,
               state, and local officials and media representatives (summarized in Appendix A) who
               provided data, information, and insight to the survey team. In addition to assisting the
               survey team in its assessment of the hydrologic forecast and warning services provided by
               the NWS, personnel from many Federal, state, local, and private organizations served the
               Nation admirably during The Great Flood of 1993.
               ct-a'Q-@@          -1-7
               Elbert W. Friday, Jr.
               Assistant Administrator
                 for Weather Services










                                                             X









                 DISASTER SURVEY TEAM MEMBERSHIP AND ITINERARY




             1. DISASTER SIRVEY TEAM AND SUPPORT PERSONNEL

                    Diana. H. Josephson, Team Leader, Deputy Under Secretary for Oceans and
                    Atmosphm, NOAA, Washington, D.C.

                    Michael D. Hudlow, Team Coordinator, Director, Office of Hydrology, NWS,
                    Silver Spring, Maryland

                    Thomas R. Carroll, Technical Leader, Director, National Operational Hydrologic
                    Remote Sensing Center, NWS, Minneapolis, Minnesota

                    David G. Brandon, Hydrologist in Charge, Colorado Basin River Forecast
                    Center, NWS, Salt Lake City, Utah

                    Nfichael K. Buckley, Hydraulic Engineer, Federal Emergency Management
                    Agency, Washington, D.C.

                    Stanley A. Changnon, Chief, Emeritus and Principal Scientist, Illinois State Water
                    Survey, Champaign, Illinois

                    Nancy 1. Eiben, Service Hydrologist, Pittsburgh Weather Service Forecast Office,
                    NWS, Pittsburgh, Pennsylvania

                    Janice M. Lewis, Research Hydrologist, Office of Hydrology, NWS,
                    Silver Spring, Maryland

                    Dale G. Lillie, Hydrologist in Charge, Arkansas-Red Basin River Forecast
                    Center, NWS, Tulsa, Oklahoma

                    David Miskus, Meteorologist, National Meteorological Center, NWS,
                    Camp Springs, Maryland

                    Roderick A. Scofield, Research Meteorologist, Physical Sciences Branch, National
                    Environmental Satellite, Data, and Information Service, Camp Springs, Maryland

                    Patrick J. Slattery, Public Affairs Specialist, NOAA, NWS Central Region,
                    Kansas City, Missouri




                                                            xi









                      John J. Tcbcau, Public Affairs Specialist, Office of Public Affairs, NOAA,
                      Washington, D.C.

                      Dewey M. Walston, Warning and Preparedness Meteorologist, Pittsburgh
                      Weather Service Forecast Office, NWS, Pittsburgh, Pennsylvania

                      Dennis R. Williams, Chief, Hydrologic Engineering Section, U.S. Army Corps of
                      Engineers, Nashville, Tennessee

                      Gary R. Woodall, Warning and Coordination Meteorologist, Southern Region
                      Headquarters, NWS, Fort Worth, Texas

              In addition to the official disaster survey team, the following NOAA personnel provided critical
              support during the field survey and compilation of the report:

                      Robert K. Hartman, Development and Implementation Hydrologist, National
                      Operational Hydrologic Remote Sensing Center, NWS, Minneapolis, Minnesota

                      Andrea M. Hrusovsky-Klein, Lieutenant, NOAA Corps, National Operational
                      Hydrologic Remote Sensing Center, NWS, Minneapolis, Minnesota

                      Katherine L. Husnik, Hydrologic Technician, National Operational Hydrologic
                      Remote Sensing Center, NWS, Minneapolis, Minnesota

                      Scott T. Kroczynsld, Manager, Hydrometeorological Information Center, Office
                      of Hydrology, NWS, Silver Spring, Maryland

                      Daniel M. Lipins1d, Computer Programmer, National Operational Hydrologic
                      Remote Sensing Center, NWS, Minneapolis, Minnesota

                      Robert W. Maxson, Lieutenant Commander, NOAA Corps, National Operational
                      Hydrologic Remote Sensing Center, NWS, Minneapolis, Minnesota

                      Robert W. Poston, Lieutenant, NOAA Corps, National Operational Hydrologic
                      Remote Sensing Center, NWS, Minneapolis, Minnesota

                      Frank P. Richards, Chief, Special Studies Branch, Office of Hydrology, NWS,
                      Silver Spring, Maryland

                      Edward R. Johnson, Chief, Hydrologic Operations Division, Office of Hydrology,
                      NWS, Silver Spring, Maryland

                      Eric Secretan, Lieutenant Commander, NOAA Corps, National Operational
                      Hydrologic Remote Sensing Center, NWS, Minneapolis, Minnesota


                                                           xii









                    Eugene A. Stallings, Chief, Hydrologic Services Branch, Office of Hydrology,
                    NWS, Silver Spring, Maryland

             The following individuals provided outstanding graphics, editorial, production, and secretarial
             support required to generate this disaster survey report:

                    Debra A. Anderson, Program Assistant, Hydrologic Systems Branch, Office of
                    Hydrology, NWS, Silver Spring, Maryland

                    Cassandra Gangadhar, Secretary, Hydrologic Systems Branch, Office of
                    Hydrology, NWS, Silver Spring, Maryland

                    Susan M. Gillette, Physical Science Technician, Hydrometeorological Branch,
                    Office of Hydrology, NWS, Silver Spring, Maryland

                    Jennifer L. Hanson, Computer Specialist, Water Management Information
                    Division, Office of Hydrology, NWS, Silver Spring, Maryland

                    Elaine A. Hauschildt, Editorial Assistant, Hydrologic Research Laboratory, Office
                    of Hydrology, NWS, Silver Spring, Maryland

                    Nancy L. Helmick, Secretary, Hydrologic Services Branch, Office of Hydrology,
                    NWS, Silver Spring, Maryland

                    Amy M. Hillard, Computer Clerk, Water Management Information Division,
                    Office of Hydrology, NWS, Silver Spring, Maryland

                    Tonya N. Lantz, Computer Graphics Specialist, Hydrologic Research Laboratory,
                    Office of Hydrology, NWS, Silver Spring, Maryland

                    Anne G. Morgan, Senior Computer Graphics Specialist, Hydrologic Research
                    Laboratory, Office of Hydrology, NWS, Silver Spring, Maryland

                    Stephen L. Pond, Meteorological Technician, Special Studies Branch, Office of
                    Hydrology, NWS, Silver Spring, Maryland

                    Virginia M. Radcliffe, Senior Editorial Assistant, Hydrologic Research
                    Laboratory, Office of Hydrology, NWS, Silver Spring, Maryland

                    Audrey M. Sorensen, Editorial Assistant, Hydrologic Research Laboratory, Office
                    of Hydrology, NWS, Silver Spring, Maryland

                    Larry A. Wenzel, Hydrometeorological Technician, Hydrologic Services Branch,
                    Office of Hydrology, NWS, Silver Spring, Maryland


                                                            xiii










              2. DISASTER SURVEY TEAM IT IN ERARY


              The team was divided into groups so that the wide geographic area of interest across the nine-
              state region could be covered as efficiently as possible.


                                  Entire Field Survey Team


                     August 22: (evening)

                           NWS National Operational Hydrologic Remote Sensing Center,
                           Minneapolis, Minnesota


                     August 23:

                           Minneapolis Weather Service Forecast Office (WSFO)
                           North Central River Forecast Center
                           U.S. Army Corps of Engineers, St. Paul District
                           Minnesota State Emergency Management Agency
                           KARE-TV and WCCO-TV



                    August 24:

                           Group la - Josephson, Hudlow, Tebeau, Lillie, Secretan,
                                      Poston


                                  Des Moines WSFO
                                  Des Moines City Manager
                                  West Des Moines City Manager
                                  WHO Radio


                           Group lb - Buckley, Walston, Changnon, Maxson, Hrusovsky-Klein

                                  Milwaukee WSFO
                                  Chicago WSFO
                                  Chicago Federal Emergency Management Agency







                                                        xiv








                        Group 2 - Carroll, Brandon, Eiben, Slattery, Williams, Lewis, Woodall

                                Missouri Basin River Forecast Center
                                Kansas City WFO
                                Topeka WSFO
                                KMBC-TV


                  August 25-

                        Group I

                                Des Moines Water Works
                                Iowa Emergency Services Agency
                                Des Moines Public Works Director
                                Omaha WSFO
                                U.S. Amy Corps of Engineers, Omaha District and Division Offices
                                KCCI-TV


                        Group 2

                                U.S. Army Corps of Engineers, Kansas City District
                                Columbia Weather Service Office (WSO)
                                Missouri State Emergency Management Agency
                                Boone County Emergency Management Agency
                                Transportation Division, Missouri Highway and
                                 Transportation Department
                                Office of Railroad Safety, Division of Transportation, State of Missouri
                                KOMU-TV



                  August 26:

                        St. Louis Red Cross
                        St. Louis WSFO
                        KMOX Radio
                        St. Louis Post Dispatch
                        Associated Press, St. Louis
                        Lincoln County Sheriff, Troy, Missouri
                        Jersey County Sheriff, Jerseyville, Illinois
                        KMOV-TV








                                                     xv









                     August 27:

                           St. Louis WSFO
                           Federal Aviation Administration, St. Louis
                           U.S. Coast Guard/U.S. Army Corps of Engineers Command Center
                           Congressman Jim Talent's Office
                           KSDK-TV
                           St. Louis County Police
                           St. Charles County Farm Bureau


                    August 28:

                           St. Charles County Emergency Management Agency


                    August 29:

                           U.S. Army Corps of Engineers, Rock Island District
                           (Both groups return to Minneapolis)


                    August 30:

                           Fargo WSO
                           Sioux Falls WSFO


























                                                        xvi









                                          EXECUTIVE SUMMARY




             Unique and extreme meteorological, climatological, and hydrological conditions led to
             The Great Flood of 1993. The stage was set in 1992 when a wet fall resulted in above-
             normal soil moisture and water storage conditions in the upper Mississippi and Missoue
             River basins. These conditions were followed by meteorological patterns in the spring and
             summer months of 1993 that were more reminiscent of patterns typically experienced during
             the late winter and early spring months when storms often follow more northerly tracks. The
             persistent, repetitive nature of the storm systems, and their broad areal extent throughout the
             entire late spring and summer months, bombarded the Upper Midwest with copious rainfall
             amounts. Some areas received more than 4 feet of rain during the period.

             The duration, extent, and intensity of the flooding uniquely defines this event in the
             20th century. Measured in terms of economic and human impacts, The Great Flood of 1993
             will be recorded as the most devastating flood in modem U.S. history. Nine states, more
             than 15 percent of the contiguous United States, were catastrophically impacted. Initial
             assessments of the economic damages of The Great Flood of 1993 indicate that losses will
             range between $15-20 billion, rivaling those of Hurricane Andrew. The impact of social
             disruption is beyond measure. Experts estimate that more than 50,000 homes were damaged
             or destroyed and that approximately 54,000 persons were evacuated from flooded areas.

             The principal objective of the disaster survey team's assessment of the National Oceanic and
             Atmospheric Administration's (NOAA) services was to identify significant deficiencies, if
             any, in the overall hydrologic forecast and warning system and to make recommendations to
             improve the system. In this context, it is important to differentiate the superior performance
             of the National Weather Service (NWS) employees from the inherent deficiencies in the
             technology of the current system that, in some ways, diminish the accuracy and timeliness
             of today's forecast and warning services.

             The performance of the NWS employees was superb. Their extraordinary and unprecedented
             efforts, exerted under extremely stressful conditions, continued for literally months. Their
             devotion to high quality services and protection of life and property was outstanding. In
             many cases, human judgment and expertise compensated for serious deficiencies in the
             current technological capabilities of the forecast and warning system. The services provided
             during this historic event constituted a major team effort by 3 River Forecast Centers,
             9 Weather Service Forecast Offices, and 20 Weather Service Offices with support from
             multiple NWS national centers.

             This team effort was momentous, and the collaborative effort by all offices was outstanding.
             Perhaps a specific illustration will help to put in perspective the dedication of NOAA
             employees and their human contributions to the forecasting for this cataclysmic event: One


                                                          Xvii









                of the hydrologic forecasters at 2 a. m., unable to sleep, realized he was uneasy about the
                latest river stage forecast for St. Louis. After days of extended hours of duty, the forecaster
                got up, took a shower, and returned to the River Forecast Center (RFC) to examine
                additional information and to further confer with his colleagues. After considerable debate,
                this forecaster convinced himself and other staff members that the forecast stage at St. Louis
                should be raised.    In retrospect, the decision was correct and consequently resulted in
                significantly improved mitigation actions. Arriving at a decision to change a forecast of this
                importance is stressful and places the forecaster in an extremely lonely position when he/she
                knows that the ultimate decision will likely impact directly on life and property. This
                anecdote epitomizes the dedication of the men and women on the NOAA team and is only
                one illustration of the countless, magnanimous efforts made throughout the event.

                By and large, most of the deficiencies identified by the NOAA survey team resulted from
                inadequate technological capabilities within the current forecast and warning system. In large
                measure, the identified deficiencies can be corrected through implementation of more
                advanced hydrologic prediction capabilities. A substantial number of these deficiencies will
                be corrected as part of modernization and associated restructuring (MAR) of the NWS. In
                fact, a major recommendation of the team is that MAR must be maintained on schedule or
                accelerated wherever possible. The modernization has progressed to the point that limited
                benefits were clearly capitalized upon during The Great Flood of 1993.

                The installed base of Weather Surveillance Radar 88 Doppler (WSR-88D) systems under
                MAR provided major benefits during the flood event. At least two        specific instances were
                documented in which radar rainfall estimates from the Chicago and       Kansas City WSR-88D
                systems saved lives during flash flood conditions on July 18, 1993, and on August 11-12,
                1993, respectively. Maximum use of WSR-88D data for hydrologic          forecast and warnings,
                however, awaits completion of the Next Generation Weather Radar (NEXRAD--now called
                the WSR-88D) network over the upper Mississippi River basin.            In addition, Advanced
                Weather Interactive Processing System (AWIPS), or AWIPS-type capability under MAR, is
                needed at the RFCs to process and mosaic the information from multiple radars in their areas
                of forecast responsibility. Such capabilities are currently being implemented as part of the
                AWIPS contract at the Missouri Basin RFC at Kansas City, Missouri. It is important to
                implement similar capabilities at the North Central RFC in Minneapolis, Minnesota, in
                preparation for the high potential of spring snowmelt flooding in 1994.

                Of equal importance to the technological enhancements are the advances in human resources
                also planned as part of MAR. These include training on modernized NWS technology and
                advanced hydrometeorological functions as part of the RFC operations. These new RFC
                hydrometeorological capabilities will facilitate the closer coupling of meteorological and
                hydrological operations required to effectively include quantitative precipitation forecasts and
                climate information in the hydrologic prediction models.





                                                             xviii








             Other elements needed to improve deficiencies beyond those addressed by MAR inciude
             substantial advances in NOAA's capabilities to model and to predict the complex hydrologic
             and hydraulic conditions experienced in the Missouri and Mississippi River basins during
             The Great Flood of 1993. Prediction of strearnflow conditions on these majoy fiveirs and
             tributaries requires the best possible physical irepresentation of all phases of the wateir cycle.
             This includes proper accounting for sofi moisture conditions, levee effects, and transport of
             water through complex river channels, reservoirs, and locks and dams. Hn addition, achieving
             the greatest forecast and warning accuracy, with the longest lead-times possible, requires
             incorporation of future meteorological and climatological forecasts, especially the
             incorporation of future rainfall estimates in le forecast methodology. Finally, hydrologic
             forecasts require greater quantification that includes bracketed confidence limits, of
             associated probabilities, that provide likelihood of occurrences for a range of specific stage
             forecasts. These more specific and timely forecasts would enable emergency managers and
             water facility operators to make more accurate, precise, and informed decisions required to
             carry out their routine operations and emergency flood mitigation actions effectively.

             The Department of Commerce and NOAA are committed to develop and to implement an
             advanced hydrologic prediction system for the entire Nation. This activity constitutes a
             major component of the NOAA 1995-2005 Strategic Plan to improve NOAA's irole in
             environmental prediction. Part of this effort clearly will be critically dependent on major
             collaborative efforts with many of NOAA's partners at the Federal, state, and local levels, as
             well as in the academic and the private sectors. Emprovements in the Nation's capabilities to
             predict more accurately the hydrologic extremes of droughts and floods, as well as to provide
             day-to-day information for improved water management decisions, will translate into
             enormous economic and environmental benefits for the Nation. Improved decision-making
             information for The Great Flood of 1993 alone could have easily translated into savings of
             hundreds of millions of dollars through improved mitigation actions.               Moreover, the
             associated human suffering could have been dramatically reduced with more timely, accurate,
             and improved decision-making information.

             Other areas of deficiency identified by the survey team in the overall prediction and response
             system included inadequate computer processing and telecommunications capabilities, as well
             as problems associated with timely and complete dissemination of appropriate products. Any
             single forecast is of value only if it is disseminated in a timely fashion and appropriate
             actions are taken. During The Great Flood of 1993, effective communication of critical
             information was inadequate on several occasions.               In other instances, conflicting
             communications and the absence of suitable preparedness response plans by local officials
             hampered mitigation actions. The findings and recommendations pertaining to these and
             other areas of concern are contained in the relevant chapters of this report. Also, for ease of
             reference, all 106 findings and recommendations are consolidated in Chapter 9.






                                                             Xim









               In conclusion, it is clear that appropriate actions should be taken in the short term to
               strengthen the hydrologic service capabilities of the NWS and to prepare for the potentially
               devastating spring floods that may develop in 1994 over precisely the same region of the
               country impacted by The Great Flood of 1993. Moreover, it is imperative that, over the
               longer term, NOAA take systematic actions to capitalize on the NWS MAR and on the
               proven, advanced hydrologic prediction capabilities required to improve NOAA's services
               during future flood and drought events. More detailed findings and recommendations to
               seize on opportunities for improvements based on lessons learned from The Great Flood
               of 1993 are contained in Chapter 2 of this report.          Additionally, the impacts; the
               hydrometeorological setting; the hydrologic and hydraulic forecast methodology; the data
               acquisition, telecommunications, facilities, and computer systems; the warning and forecast
               services; the coordination and dissemination; and the preparedness and user-response issues
               related to The Great Flood of 1993 are discussed in considerable detail in Chapters 1, 3, 4,
               5, 6, 7, and 8, respectively.
































                                                           xx









                         ABBREVIATIONS AND ACRONYMS





         ABRFC        Arkansas-Red Basin River Forecast Center
         AFOS         Automation of Field Operations and Services
         AHPS         Advanced Hydrologic Prediction System
         ALERT        Automated Local Evaluation in Real-Time
         API          Antecedent Precipitation Index
         API-CIN      Ohio RFC Antecedent Precipitation Index Rainfall-Runoff Model
         API-CONT     Continuous Antecedent Precipitation Index
         API-HAR      Middle Atlantic RFC Antecedent Precipitation Index Rainfall-Runoff Model
         API-MKC      Central Region Antecedent Precipitation Index Rainfall-Runoff Model
         API-SLC      Colorado RFC Antecedent Precipitation Index Rainfall-Runoff Model
         ASOS         Automated Surface Observing System
         AVHRR        Advanced Very High Resolution Radiometer (NOAA)
         AWIPS        Advanced Weather Interactive Processing System
         BASEFLOW     Baseflow Generation Runoff Model
         BIS          Bismarck WSFO
         BON          Boonville river forecast point (MBRFC)
         BUR          Burlington river forecast point (NCRFC)
         CAC          Climate Analysis Center (NMC)
         CADAS        Centralized Automatic Data Acquisition System
         CHANLOSS     Channel Loss Routing Model
         CHI          Former designation for Chicago WSFO (now LOT)
         CHS          Chester river forecast point (NCRFC)
         COE          U.S. Army Corps of Engineers
         CRT          Cathode Ray Tube (computer monitor)
         DAC          Disaster Application Centers
         DCP          Data Collection Platform
         DFO          Disaster Field Office
         DMSP         Defense Meteorological Satellite Program
         DOC          Department of Commerce
         DSM          Des Moines WSFO
         DWOPER       Operational Dynamic Wave Routing Model
         D24          Dam 24 river forecast point (NCRFC)
         EMA          Emergency Management Agency
         ENSO         El Nifio/Southern Oscillation
         EOC          Emergency Operations Center
         E-19         river forecast point description





                                            xxi










           FAA         Federal Aviation Administration
           FEMA        Federal Emergency Management Agency
           FFA         Flash Flood Watch
           FFP         Flash Flood Potential
           FFS         Flash Flood Statement
           FFW         Flash Flood Warning
           FLS         Flood Statement
           FLW         Flood Warning
           FSD         Sioux Falls WSFO
           GIS         Geographic Information System
           GOES        Geostationary Operational Environmental Satellite
           GRF         Grafton river forecast point (NCRFC)
           GUT         Guttenburg river forecast point (NCRFC)
           HADS        Hydrometeorological Automated Data System
           HAS         Hydrometeorological Analysis and Support
           HEM         Hermann river forecast point (MBRFC)
           HIC         Hydrologist in Charge
           HRL         Hydrologic Research Laboratory (OH)
           HSA         Hydrologic Service Area
           IFFA        Interactive Flash Flood Analyzer
           LAC         LaCrosse river forecast point (NCRFC)
           LAG/K       Lag and K Routing Model
           LARC        Limited Automatic Remote Collector
           LAY/COEF    Layered Coefficient Routing Model
           LFWS        Local Flood Warning System
           LMRFC       Lower Mississippi River Forecast Center (Slidell, Louisiana)
           MAP         mean areal precipitation
           MAR         modernization and associated restructuring
           MBRFC       Missouri Basin River Forecast Center (Kansas City)
           MCI         Kansas City WSO
           MCS         Mesoscale Convective System
           MIC         Meteorologist in Charge
           MKE         Milwaukee WSO
           MOD         Meteorological Operations Division (NMC)
           MSP         Minneapolis WSFO
           MUSKROUT    Muskingum Routing Model
           MW          microwave
           NCCF        NOAA Central Computer Facility
           NCRFC       North Central River Forecast Center (Minneapolis)
           NESDIS      National Environmental Satellite, Data, and Information Service (NOAA)
           NEXRAD      Next Generation Weather Radar
           NIDS        NEXRAD Information Dissemination System
           NMC         National Meteorological Center (NWS)
           NOAA        National Oceanic and Atmospheric Administration


                                           xxii








         NOHRSC      National Operational Hydrologic Remote Sensing Center (NWS)
         NPPU        National Precipitation Prediction Unit
         NWR         NOAA Weather Radio
         NWS         National Weather Service
         NWSRFS      NWS River Forecast System
         NWWS        NOAA Weather Wire Service
         OH          Office of Hydrology (NWS)
         OM          Office of Meteorology (NWS)
         OVN         Omaha WSFO
         PDI         Palmer Drought Index
         PUP         Principle User Processor (WSR-88D)
         QPF         Quantitative Precipitation Forecast
         raob        radiosonde observation
         RCC         Regional Climate Center
         RES-SINGL   Single Reservoir Simulation Routing Model
         RFC         River Forecast Center (NWS)
         RJE         remote job entry
         ROSA        Remote Observation System Automation
         RVA         River Summary
         RVS         River Statement
         SAB         Synoptic Analysis Branch (NESDIS)
         SAC-SMA     Sacramento Soil Moisture Accounting Runoff Model
         SH          Service Hydrologist
         SHEF        Standard Hydrometeorological Exchange Format
         SHIMS       Service Hydrologist Information Management System
         SNOW-17     NWSRFS snow accumulation and melt runoff model
         SPS         Special Weather Statement
         SRWARN      Southern Region Warn (a computer program)
         SSM/I       Special Sensor Microwave/Imager
         SST         sea surface temperature
         STAGE-Q     Stage-Discharge Conversion Model
         STL         former designation for St Louis WSFO (now LSX)
         STP         St Paul river forecast point (NCRFC)
         SVR         Severe Thunderstorm Warning
         SVS         Severe Weather Statement
         SXC         Sioux City river forecast point (MBRFC)
         TATUM       Tatum Routing Model
         TIR         thermal infrared
         TM          thematic mapper
         TOP         Topeka WSFO
         TOR         Tornado Warning
         USDA        U.S. Department of Agriculture
         USGS        U.S. Geological Survey
         UTC         Universal Coordinated Time


                                         xxiii









         VDUC       VAS Data Utilization Computer
         VIS        visible
         WARFS      Water Resources Forecasting System
         WCM        Warning and Coordination Meteorologist
         WGRFC      West Gulf River Forecast Center
         WPM        Warning and Preparedness Meteorologist
         WFO        Weather Forecast Office
         WSFO       Weather Service Forecast Office
         WSO        Weather Service Office
         WSR-57     Weather Surveillance Radar 1957
         WSR-88D    Weather Surveillance Radar 1988 Doppler
         XIN-SMA    Xinanjiang Soil Moisture Accounting Runoff Model







































                                    xxiv









                                                     CHAPTER 1


                GENERAL DESCRIPTION OF THE EVENT AND ITS EMPACT




             1.1 INTRODUCTION

             The Great Flood of 1993 was an unprecedented hydrometeorological event since the United
             States started to provide weather services in the mid-1800s. In terms of precipitation amounts,
             record river stages, areal extent of flooding, persons displaced, crop and property damage, and
             flood duration, this event (or sequence of events) surpassed all floods in the United States during
             modem times.        The purpose of this chapter is to provide a cursory overview of
             The Great Flood of 1993 and some of its impacts. Its contents are by no means all-inclusive.
             Full meteorologic and hydrologic analyses of this event, as well as a complete study of the flood
             impacts, will be the subject of many reports and studies conducted by Federal, state, and private
             agencies for years to come.

             Record and near-record precipitation during the spring of 1993, on soil saturated from previous
             seasonal precipitation, resulted in flooding along many of the major river systems and their
             tributaries in the Upper Midwest.        Rivers climbed above flood stage at approximately
             500 forecast points in the nine-state region. Moreover, record flooding occurred at 95 forecast
             points in the Upper Midwest during the summer of 1993. Flood records were broken at
             44 forecast points on the upper Mississippi River system, at 49 forecast points on the Missouri
             River system, and at 2 forecast points on the Red River of the North system. Within the
             Mississippi River system, 1993 floods of record include those set at 15 forecast points on the
             main stem, at 4 forecast points on the Iowa River, at 5 forecast points on the Des Moines River,
             and at 2 forecast points on the Raccoon River.

             Within the Missouri River system, 1993 floods of record include those set at 14 forecast points
             on the main stem and at 4 forecast points on each of the Saline, Smoky Hill, and Grand Rivers.
             During the event, near flood of record stage occurred at an additional 23 forecast points on the
             Missouri River system alone. Record flood stages surpassed old record stages by more than
             6 feet in some cases. For example, in 1993, flood records set more than 42 years ago on the
             main stem of the Missouri were broken by more than 4 feet at multiple forecast points. In at
             least one case, a new flood of record was established early in the event only to be broken by
             higher water later in the event. The historic flood of record on the Mississippi at St. Louis was
             established on April 28, 1973, at 43.2 feet; reestablished on July 21, 1993, with a flood stage
             of 46.9 feet; and reestablished again 11 days later on August 1, 1993, with a record flood stage
             of 49.58 feet. Figure 1-1 gives an overview of the areal extent of The Great Flood of 1993.




                                                             1-1














                              ..... . . . . . . . . . . .







                                                                                                                                                ....... ......








                                  0,




                                                                        ra










                                                                                                                                               .................




                                                         latte
                                          Repubfican River



                                                     Swomon R
                                                                                      Wesoud River
                                                      SWIno River

                                                                          Keln@wsw
                                                sm     Hill


                                              ...............



                                                    . . . . . . . .                                                                    ...

                                                                 .....                                             ......

                                                     mom
                                                                 Record Flooding
                                                                 Major Flo



                       Figure 1-1. General area impacted by heavy rainfall andlorflooding during
                       The Great Flood of 1993.


                     The duration of The Great Flood of 1993 was as overwhelming as the areal extent of flooding
                     and the number of record stages established. Spring flooding began in March as a result of a
                     previous wet fall, normal to above-normal snow accumulation, and rapid spring snowmelt
                     accompanied by heavy spring rainfall. On May 8, record flooding occurred in South Dakota
                     on Split Rock Creek at Corson and in Minnesota on the Rock River at Luverne. On May 22-24,
                     heavy thunderstorms produced 3-7 inches of rain in 3 hours over Sioux Falls resulting in major
                     urban and residential flooding across the city. The Big Sioux and Vermillion Rivers in


                                                                                       1-2









             South Dakota went above flood stage in late May and remained in flood through mid-June.
             Major flooding continued throughout the summer along the Missouri and Mississippi Rivers.
             For example, on September 1, 1993, the towns of Hannibal, Louisiana, and Clarksville,
             Missouri, had experienced 153 consecutive days of flooding. Flooding at levels above flood
             stage continued through the middle of September in many regions along the Mississippi River.

             The duration and magnitude of The Great Flood of 1993, as well as its antecedent conditions,
             strongly support the premise that this event was a significant climate variation rather than simply
             a sequence of meteorological events. It is quite possible that one or more climate-driving forces
             (e.g., El Niffo/Southem Oscillation) significantly contributed to this climate variation. A more
             thorough analysis of this situation is expected to result in improved understanding of the roles
             contributing factors may have played.


             1.2 INT MAGENCY FLOOD RESPONSE

             The forecasting services provided by the National Weather Service (NWS) is but one of many
             activities undertaken by the Federal Government in responding to The Great Flood of 1993. The
             high quality and timeliness of these forecasts were critical to the success of evacuation and
             emergency mitigation actions initiated at all levels of government, as well as by voluntary groups
             and private citizens. The Federal Response Plan was signed by 26 Federal departments and
             agencies, who participated in a coordinated effort to address the basic needs for the victims of
             The Great Flood of 1993. Nearly 4,000 Federal personnel from the various Federal agencies
             were committed to assist in the response activities. Two major Federal contributors to the
             response operations included the U.S. Army Corps of Engineers (COE) and the Federal
             Emergency Management Agency (FEMA).

             The COE provided technical assistance to states and local authorities to prevent loss of life and
             property damage during The Great Flood of 1993. In addition, the COE maintained and
             operated navigation and flood control facilities on the flooded river systems. Response and
             recovery assistance was provided by the COE under two laws, Public Law 84-99 and Public
             Law 93-288 (Stafford Act). The COE received $20 million from FEMA to supply emergency
             sanitary and water supply facilities, bridge and pier inspections, damage survey report, and other
             technical support to local authorities. In addition, the COE distributed more than 31 million
             sand bags and more than 400 water pumps. At the height of the flood, the COE committed
             800 personnel to these efforts. The COE and FEMA worked together to evacuate flood water
             in low areas and impounded behind levees, to remove debris, and to restore public facilities.

             With the first Federal disaster declaration issued on June 11, 1993, for several counties in
             Minnesota, FEMA immediately mobilized response and recovery operations authorized under
             the Stafford Act (Public Law 93-288). This initial response included the establishment of a
             Disaster Field Office (DFO) which coordinated the operations in the affected areas, and several
             Disaster Application Centers (DAC) where applications for individual assistance were processed.
             At the peak of the response operations, FEMA had established I I DFOs and numerous DACs


                                                             2-3









                throughout the affected areas, in addition to operating a tele-registration 800 hot line to provide
                information and to receive applications from those unable to make it to one of the DACs. At
                the time of this writing, over 120,000 registrations for disaster assistance have been accepted
                from flood victims totaling more than $150 million in payments. Another $200 million has been
                paid from premiums collected under the National Flood Insurance Program for flood damage
                to insured property.


                1.3 ITOPACT OF THE FLOODING


                The Great Flood of 1993 caused enormous human suffering. At least 75 towns were completely
                inundated, some of which may never be rebuilt. Many people worked 24 hours a day for weeks
                building up levees to ward off the flood, only to have these levees eventually fail. The flood
                destroyed family businesses, community schools, people's homes and property, and treasures
                of their heritage. In Hardin, Missouri, more than 700 coffins were washed out of grave sites,
                many of which have not been recovered.

                More than 20 million acres of land in nine states were inundated by The Great Flood of 1993.
                The entire state of Iowa was designated as a Federal disaster area. Large sections of eight other
                states--North Dakota, South Dakota, Minnesota, Wisconsin, Illinois, Missouri, Nebraska, and
                Kansas--were also declared Federal disaster areas. The number of fatalities caused by the flood
                is estimated to be 48 people. Approximately 54,000 people had to be evacuated from flooded
                areas at some time during the flood, and 50,000 homes with associated property were estimated
                to be destroyed or damaged. The flood also had enormous ongoing, indirect impacts on
                hundreds of thousands of people. In Iowa, for example, tens of thousands of people were unable
                to work because of a lack of public water supplies needed for sanitation, fire flghting, or routine
                operation of businesses. Barge, rail, and truck traffic was curtailed or completely halted in
                many areas.

                Initial assessments of the economic impact of The Great Flood of 1993 indicate that losses will
                range between $15-20 billion. This damage estimate may prove to be too low as the flood
                continues to recede, exposing additional previously unknown destruction. In terms of interstate
                commerce alone, the flood has had dramatic impact. The towing industry estimates that at least
                $3-4 million was lost each day that the Mississippi River was closed to barge traffic. The
                trucking industry was forced to reroute much of its traffic to more lengthy routes due to the
                many interstate highway and local bridge closures. At different times during the flood, all
                bridges from Davenport, Iowa, to St. Louis, Missouri, on the Mississippi River, and all bridges
                from Kansas City, Missouri, to St. Louis on the Missouri River, were closed. Sections of
                Interstate Highways 1-35, 1-70, and 1-29, as well as hundreds of miles of secondary roads, were
                also closed.








                                                                1-4









             Numerous miles of railroad track were flooded, halting rail transit along many rail systems.
             Furthermore, the flow of flood waters eroded the rail beds, and it will require significant funds
             to return these tracks to operation. At one time, seven of the eight rail lines across the state of
             Missouri were closed to rail traffic. It has been estimated that the rail industry suffered
             operating losses in excess of $300 million loss and $100 million in flood damages in Missouri
             alone. Finally, 12 commercial airports were closed by the flood, including the Spirit of
             St. Louis Airport, which is a major executive airfield located in Chesterfield, Missouri.

             Locks, dams, and levees on the affected river systems must all be inspected and repaired in the
             aftermath of the flood. Approximately 6,000 miles of non-Federal levees protect cities, towns,
             and farm land along many of the major rivers affected by the flood. The COE reports that
             40 of 229 Federal levees and 1,043 of 1,347 non-Federal levees were overtopped or damaged
             during the flood. Damage to locks and dams will be fully assessed only after the rivers fall well
             below flood stage. The major courses and beds of the rivers themselves may be significantly
             altered as a result of the flood that will affect future river navigation and commerce.

             The agriculture industry experienced major economic losses as a direct result of
             The Great Flood of 1993. In large areas inundated by the flood, the harvest of 1993 was a total
             loss. More than 600 billion tons of topsoil erosion by the river flow and vast deposits of sand
             and silt on farm land will have long-term impacts on future farm productivity. Much of the soil
             removed from agricultural land has been deposited in the major rivers and may affect the flora
             and fauna that form the various river ecosystems. Pollutants and raw sewage released as the
             flood spread inland will cause additional stress on the river environment.

             The Great Flood of 1993 began well before the devastating flooding that occurred during June,
             July, and early August. Moreover, disastrous flooding continued in the late summer and fall
             across portions of the Upper Midwest. This report, however, focuses on the forecasts and
             services provided by the NWS during June, July, and early August when the most catastrophic
             flooding occurred across the region. Nonetheless, late-summer and fall flooding was quite
             significant. One example occurred on August 29, 1993, when the city of Des Moines, Iowa,
             received enough precipitation to force once more thousands of people out of homes to which
             they had recently returned in the aftermath of previous flooding. Above-normal fall soil
             moisture conditions provide serious potential for new flooding should significant rainfall occur.
             Fall soil moisture conditions coupled with normal snow accumulation and spring precipitation
             help constitute a significant threat of major spring snowmelt flooding across the Upper Midwest
             in 1994.













                                                             1-5









                                                     CHAPTER 2


                                        MAJOR LESSONS LEARNED
                              AND OPPORTUNITIES FOR THE FUTI





             2.1 INTRODUCTION

             The unique meteorological, climatological, hydrological, and hydraulic conditions that led to
             The Great Flood of 1993 provide many lessons dw can lead to future improvements in the
             services provided by the National Weather Service (NWS). All aspects of the performance of
             the NWS river forecast and warning system were evaluated as part of the field survey.

             Almost all the findings and associated recommendations stem from lessons learned and point
             toward refinements for the future. The purpose of this chapter is to highlight some of the more
             fundamental, global findings and recommendations.


             2.2 SCOPE AND                   I OF TTIE NATTONAL WEATIIER SERVICE
                  RESPONSE


             As illustrated in Figure 1-1, the area impacted by flooding covered major portions of nine states.
             This area, comprising approximately 15 percent of the 48 contiguous states, contains 2 River
             Forecast Centers (RFC), 9 Weather Service Forecast Offices (WSF0), and 20 Weather Service
             Offices (WSQ) located within the Central Region of the National Oceanic and Atmospheric
             Administration's (NOAA) NWS. The staffs of these forecast and warning offices worked
             tirelessly to provide high-quality services over a period of several months. Their continuous
             contributions clearly saved many lives and prevented substantial increases in property damage.

             The duration and magnitude of the event placed enormous stress on both humans and the forecast
             system infi-astructure. Given current resources and system limitations, the forecasts and warnings
             were incredibly good. For example, at the peak of the flood along a stretch of the Mssissippi
             River near Hannibal, Nfissouri, approximately 50 percent of the estimated 4 million gallons of
             water per second was flowing outside the "main channel" of the river and behind the levee
             systems. In spite of these complex hydraulic conditions, the North Central RFC provided
             forecasts for the city of Hannibal that were sufficiently accurate and timely to allow the
             U.S. Army Corps of Engineers (COE) and the city of Hannibal to take action to reinforce the
             major levee system protecting the city. Although numerous anecdotes of major mitigation
             actions, such as this one, could be presented, there are still substantial opportunities for
             improvements that will provide significant benefits during future flood events and that will pay
             even larger dividends to the Nation.


                                                             2-1









                     One overriding conclusion reached by the survey team is that the magnitude and historical
                     importance of The Great Flood of 1993 warrants considerable additional research and study
                     to benefit from all lessons to be learned. The total scope of potential lessons learned will
                     pertain not only to ways of improving prediction capabilities but also to water resources
                     planning and assessment, water law, water use policy and regulation, flood mitigation
                     strategies, facility operations, water management decisions, and hydrologic warning and
                     public response. Only those aspects directly related to the quality of hydrometeorological
                     predictions and ensuing user response were considered by the survey team.



			Finding 2.1: The meteorological,         	   Recommendation 2.1: NOAA
			climatological, hydrological, and hy-    	   should work closely with its many
			draulic conditions that converged to     	   collaborators to encourage further
			produce The Great Flood of 1993 were     	   investigations into the various aspects
			unique in many aspects. Initial assess-  	   of The Great Flood of 1993. Much is
			ments of the economic impact of The      	   left to be learned. Additional scientific
			Great Flood of 1993 indicate that losses 	   studies should be conducted to provide
			will range between $15-20 billion            important insights on how to further
			This is the single, greatest flood loss in   minimize losses from future disastrous
			the Nation's history and rivals Hurri-       floods.
			cane Andrew in overall losses. The
			extent of social disruption is beyond
			measure.


			Finding 2.2: There were major                Recommendation 2.2: NOAA
			benefits, as well as some problems,          should support a comprehensive, exter-
			related to the many uses of NWS flood        nal study to evaluate and quantify the
			forecasts. The disaster survey team          benefits derived from hydrologic fore-
			was unable to assess comprehensively	   casts. This study should take maxi-
			the impact of the hydrologic forecasts       mum advantage of the lessons learned
			and products due to the limited dura-        during The Great Flood of 1993.
			tion of the survey. because of the 
			large socioeconomic impacts of this
			historical flood event and the potential
			mitigating effects of higher-quality
			hydrologic forecasts, a more detailed
			post-flood impact analysis would be
			invaluable.








									2-2









             2.3 ADVANCED HYDROLOGIC PREDICTION SYSTEM


             Figure 2-1 illustrates the major components or functions of a river forecast system. The
             disaster survey team identified ways to improve all components of the current forecast
             system. Chapter 4 discusses the hydrologic and hydraulic models and procedures employed
             in the current forecast system.

             Users indicated great interest in improving hydrologic prediction to help mitigate the impacts
             of future floods. The staggering loss of $15-20 billion in The Great Flood of 1993 clearly
             indicates a need to cut future losses. The key to providing improved river and flood
             forecasts in the future will depend on establishing and maintaining an Advanced Hydrologic
             Prediction System (ABPS). The Department of Commerce and NOAA, in partnership with
             other major cooperators, are committed to the development and implementation of an AHPS
             to improve services to the Nation. This effort is a key component in the NOAA 1995-2m
             Strategic Plan to enhance NOAA's role in environmental prediction. The basic components
             of an ABPS are illustrated in Figure 2-2.





                                                                                      Provide
                                                     . . . . . . . . . . . . . . . . . . . . . .
                     Collect
                                                                                       Output
                       Data
                                                                                     Products




             FIgure 2-1. Majorfunctions of a fiverforecast system.



             2.3.1 NATIONAL WEATHER SERVICE RIVER FORECAST SYSTEM

             Figure 2-2 shows that the first major building block critical to the foundation of an AHPS is
             the current NWS River Forecast System (NWSRFS), including all of the supporting
             personnel and service infrastructure. Both the North Central and Mssouri Basin RFC staffs
             expressed concern that sufficient depth of expertise and training be maintained at both NWS
             Headquarters and the RFCs to support properly the NWSRFS. The NWSRFS consists of
             software modules totaling several hundred thousand lines of computer code used to execute
             all functions shown in Figure 2-1. It is a modular software system that allows the addition
             of more advanced data processing and modeling techniques as they become available. A
             more detailed description of NWSRFS is given in Chapter 4 (Section 4.3).



                                                          2-3




















                              Current
                     NWS River Forecast
                      System (NWSRFS)
                   Operational Foundation


                                                         ............
                                                      . .. .... ...........
                                                     ............... .............
                                                      .................... ........
                                                      .........................
                                                 ........ ......... ix
                                                  ....................        .. ....

                                                      .... .........
                                                             ............
                                                                            ... .... ... .
                                                                                 ..........

                                                        ........................
                                                                             ..........
                                                                            ............
                                                                            .............
                                                       .... ........
                                                                                 ..........
                          Advanced
                                                         ................... ..... ........ ......

                                                        ....... ...          ... . ....
                                                      .................... ..... . .......
                     Water Resources
                                                                              ........ ........-
                                                                             ............

                                                                      ...........
                                                               @WW
                                                 ......             . . .....
                   Forecasting System
                          (WARFS)
                                             ..........
                                                         ............
                                                             'r  za
                                                      M6.0.0 -.nJ . ti: dln-
                         Capabilities
                                           ...........         .......
                                           .............
                                           ............
                                           ............



                                                                   ... .......

                                                             ..........
                                                         ............ ..

                                                             ..... ..... ..........
                                                         .......... ... ........
                                                 ....... ...   .... . . ..........
                                                                   .........
                                                         ........... .....
                                                      .....................
                                                      ....................
                                                  ...........
                                                 . .........X
                                                  ................. ........
                                                 ...........


                                                         ............





           Figure 2-2. Basic components of an Advanced Hydrologic Prediction System (AHPS).







                                                 2-4














                  A critical component required to improve model development and calibration is the capability
                  to archive routinely the real-time, operational, hydrometeorological data in digital format.
                  This capability does not currently exist at the RFCs, nor at the National Meteorological
                  Center (NMC), for much of the hydrometeorological data needed to support hydrologic
                  research and development.


			FINDING 2.3: A large suite of soft-			RECOMMENDATION 2.3: The
			ware and hydrologic procedures,			NWS Office of Hydrology should
			especially NWSRFS, is critical to 			systematically evaluate the operational
			current RFC operations and even more		readiness of NWSRFS and other
			critical to future operations. There is		software used in hydrologic
			significant concern about maintaining		forecasting.
			the required depth of expertise and
			support at both the field and
			headquarters levels required for this
			complex system.

			FINDING 2.4: RFCs do not routinely			RECOMMENDATION 2.4: Routine
			store river and flood forecast			procedures must be implemented at the
			information and products in digital			NMC and the RFCs, as part of 
			form. Similarly, the NMC does not			modernized system capabilities, to 
			routinely archive quantitative			archive all data and products in digital
			precipitation forecasts products in digital	format that are pertinent to ongoing
			form. These data and forecast products		developmental, operational, and
			are critical for post-event analyses,		verification programs.
			research and development, model
			calibration, exteded streamflow
			prediction and simulation requirements,
			climatological studies, and forecast
			verification.








										2-5



                                                                                                                                              ................. .........-.......... ............ .. ............... --- ....................... .......... .......................
                    














                                                                                                        07/18/93 22:51
                                                                                         JfACINE        STM PRECIP 80 STP
                                                                       . . ....... .
                                                                                                         124 NM 1.1 NM RES
                                                                              UNI
                                                                  BRLN 1                                07/18/93 22:40
                                                                                                        RDA:KLOT 41/36/14--H
                                                                                                         75S FT    88/33/02N
                                                                                                        MAX=     6.5 YN
                                                                                                        MODE A /    21
                                                                                                        CNTR 340DEG     32NM
                                                                      W-fl                             ISEG=07/17/93 07:e@8
                                                                                                                        22:d@2
                                                                                                                 NO
                                                                                                                 0.0  IN
                                          Ilan
                                                                                                                 0.1
                                                RVARD                                                            1.0
                                                                                                                 2.0
                                                                                                                 3.0
                                                                                         WAUKGN
                                                                                                                 4.0
                                 BOONE             'i@@,XC H E N R
                                                                                LAK                              5.0
                                                       .#DSTCK                                                   6.0
                                                                                                                 7.0
                                                                            CND                                  80
                                                                                                                 9.0
                                                                                                              10.0
                                                                                                              11 .0
                                                                                                              13.0
                                                                                                              15.0
                                                                                                        MAG=4X   FL= I COM=1
                                           G:
                                                                                             S
                                                                                 R   G ON H




                                                                           -RO  LL
                                              3F,
                                                                                    0

                                                     :.KANE
                                         EKALB
                            LL     DEKA68-,_                     T.CH                                   n/R   RDA
                                                                                                        Q15 R    2246       R
                                                                                                        PROD RCUD: R      PIPS
                                                                                                        KLOT 2246 .54     6.3
                                                                             is                         18/2245 VV ALERT
                                                                                                        AA#1      53 KT
                                      -WAf@RMA                                                          HARDCOPY

                                                                                                        HARDCOPY REQUEST
                                                                                                           CEPTED
                                                                                A @K
                                                                                      0 @NS

                                                                                                        ALERTS:1) VV FV VP
                                                                           01
                                                                                                         2) VV FV FT VD
                                                                                        H.

                     Figure 2-3. Chicago, Illinois, WSR-88D image sho%4ng stonn total precipitation ending at 5:42 p.m. CDT (22:42 UTC)
                     on July 18, 1993.













            2.3.2 NA17IONAL WEATHER SERVICE MODERNIZATION

            A second major building block for the AHPS is the capability provided by the NWS
            modernization and associated restructuring (MAR). The NWS MAR includes organizational
            and human resource components needed to take advantage of modernization technologies,
            principally the Next Generation Weather Radar (NEXRAD) network, the Advanced Weather
            Interactive Processing System (AWIPS), and the next generation of geostationary
            environmental satellites. NWS modernization contributes to improved hydrologic prediction
            through:

                 L    On-site, powerful, interactive computer processing that supports:
                      - a modem, interactive river forecast system; and
                      -   interactive precipitation analysis using data from radar,
                          satellite, aircraft, and automated surface gages;

                 2.   Rapid, wide-band communications; and

                 3.   More effective use of human resources.


            Even in the early stages of the implementation of NWS modernization technologies, it is
            clear that the payoff in improved forecasts and warnings will be enormous.             Several
            examples were noted by the disaster survey team when Weather Surveillance Radar 1988
            Doppler (WSR-88D)--the nomenclature for NIEXRAD radars--rainfall estimates were used to
            provide flash flood warnings. One example is illustrated in Figure 2-3, where the Chicago
            WSR-88D detected a heavy rainfall area between DeKalb and Crystal Lake, Illinois. The
            radar display provides an estimate of the storm total ending at 5:42 p.m. CDT on July 18,
            1993. Precipitation accumulations exceeded 6.5 inches. These radar observations led to the
            issuance of a flash flood warning. A greater lead-time, however, could have been given if
            the flash flood potential (FFP) algorithm had been implemented in the WSR-88D Radar
            Product Generator. Implementation of the FFP has been under configuration management
            review for an extended period.

            Current RFC computer resources lag the state of the art considerably and impact forecast
            operations in many ways. One critical example is that AWIPS-type computer resources will
            be required at RFCs to process and to mosaic the radar rainfall estimates from multiple
            radars providing coverage of the RFC's area of responsibility. At WSFOs, little or no local
            hydrologic forecast capability exists now. AWIPS-type computer resources will also be
            needed at the Weather Forecast Offices (WFO) of the modernized NWS to provide a
            Hydrometeorological Forecast and Warning subsystem to assist WFO personnel to forecast
            for small, quick-responding basins.




                                                         2-7









                      Critical also to the modernization effort is the professional staffing of personnel trained in
                      both the hydrologic and meteorologic sciences.                                                                              The disciplines are distinct but
                      interconnected. It is critical that NWS offices be staffed with qualified personnel trained to
                      provide the hydrometeorological support required by the AHPS. The modernized hydrology
                      program provides for Hydrometeorological Analysis and Support positions in the modernized
                      RFCs and for new qualification criteria for hydrometeorologists.                                                            Although these new
                      hydrometeorologist criteria have been defined, suitable changes in the personnel, recruitment,
                      qualification, and promotion process have not yet been implemented.



				FINDING 2.5: Although only nine			RECOMMENDATION 2.5: Every
				WSR-88D radars had been installed for		effort must be made to keep the NWS
				areas covering parts of the flooded			modernization on schedule and to accel-
				states, several instances illustrated the 	erate its implementation and operational
				revolutionary impact the WSR-88D will		support. It is imperative that the
				have on flood and flash flood forecasts		change-management process for the 
				and warnings. One especially notewor-		WSE-88D program be streamlined so
				thy example occurred on July 18, 1993,		that it does not take a year, or longer in 
				when the Chicago WSR-88D accurately			some cases, to get critical software
				mapped a 4.0 to 6.6 inch rainfall core		changes or enhancements implemented--
				that led to a warning being issued prior		the FFP alforithm being a case in
				to significant flooding. Greater lead-		point. Furthermore, AWIPS-type capa-
				time could have been provided, how-			bilities must be installed at the RFCs to
				ever, if the FFP algorithm had been			use effectively WSR-88D rainfall esti-
				implemented in the WSR-88D Radar			mates for numerical imput to hydrological
				Product Generator.					models.



				FINDING 2.6: WSFOs in the affected			RECOMMENDATION 2.6: NWS na-
				area have headwater tables for selected		ional and regional headquarters, NWS
				basins that are used to provide flash		field offices, and the Forecast Systems
				flood guidance. Nonetheless, many			Laboratory of the Office of Oceanic and 
				offices felt a need for more advanced,		Atmospheric Research should accelerate
				local river forecast procedures to pro-		development of the WFO Hydrometeor-
				duce headwater forecasts systematically		ological Forecast and Warning Subsys-
				or to update RFC forecasts. This was 		tem for incorporation into the AWIPS
				especially critical in situations in small	application software suite.
				river basins where hydormeteorological
				conditions changed rapidly.






										2-8















                   FINDING 2.7; The modernized NWS                 RECOMMENDATION 2.7:                   NWS
                   has a critical need for professional            and NOAA managers and personnel
                   personnel trained in both hydrology and         offices must ensure that personnel,
                   meteorology and has developed qualifi-          recruitment, qualifications, and promo-
                   cation criteria for these new hydromete-        tion processes appropriately reflect
                   orologists.                                     requirements for hydrometeorologists.



              2.3.3 PARTNERSHIPS WITH COOPERATORS


              The third building block critical to the successful implementation of an AHPS is externai
              cooperator support.       It is important to continue the high priority of developing and
              maintaining even closer partnerships with NOAA's many cooperators. This undoubtedly is
              the most important component of the AHPS as depicted in Figure 2-2, since NOAA's
              partners at Federal, state, and local levels, as well as in the academic and private sectors,
              contribute directly and indirectly to many aspects of an effective prediction system.
              Specifically, closer coordination and cooperation with the COE and the Federal Emergency
              Management Agency, which clearly had a major role in mitigating and responding to the
              effects of The Great Flood of 1993, is especially critical.



                   FINDING 2.8: The effectiveness of               RECON04ENDATION 2.8: The NWS
                   the NWS's river forecasting services            needs to maintain and strengthen coop-
                   critically depends on other Federal,            erative arrangements with current part-
                   state, and local agencies for (1) infor-        ners and to seek additional opportunities
                   mation used in the forecasting process,         to work with interested parties to ensure
                   (2) the dissemination of forecasts and          the protection of life and property.
                   warnings, and (3) ensuring that the
                   P    C take actions necessary to prevent
                   loss of life and to mitigate damage.














                                                               2-9








                                    NWS River Forecasting System
                                Hydro-
                            meteorological       p    Modeling
                                 Data



                                                      Prediction



                                            River Levels





                                                    Past         Future
                                                           I
                                                       Forecast





              Figure 24. Current NWY River Forecasting System (NWSRFS).



                           Advanced NWS River Forecasting System'
                                 Hydro-              Advanced
                             meteorological           Modeling              eteorological
                                  Data                                        rediction



                                Prediction                           Simulation


                          River Level                           River Level




                                 Past         Future              Past             Future
                                                                    I
                                      Forecast                  Probability     Climatological
                                                                 Forecast         formation



              Figure 2-5. Advanced NW5 Water Resources Forecasting System (WARFS).

                                                         2-10










             2.3.4 WATER RESOURCES FORECAST SYSTEM

             The fourth major building block of an ABPS is the capability provided by the Water
             Resources Forecast System (WARFS). Almost every user visited by the disaster survey team
             expressed a desire for river forecasts with greater lead-times. Some also wanted forecast
             ranges, or probabilities of occurrences, to accompany river forecasts that, in some way,
             consider future precipitation possibilities. WARFS will accommodate these requirements
             through the use of-

                  1.    Advanced hydrologic and hydraulic models,

                  2.    Integrated data management and analysis techniques,

                  3.    Coupled rainfall and temperature forecasts,

                  4.    Advanced remote sensing and analysis of snow water equivalent, and

                  5.    A consortium of cooperative efforts with NOAA's partners.

             A comparison of Figures 2-4 and 2-5 illustrates the major enhancements that WARFS will
             provide over the current NWSRFS capabilities. The most important changes will be the
             application of more advanced hydrologic and hydraulic models using improved
             hydrometeorological data and the capability to incorporate both short-term meteorological
             predictions and longer-term, climatological information (Figure 2-5).               Quantitative
             precipitation forecasts (QPF) are not being used directly and objectively in Central Region
             RFC forecast procedures, but an AHPS with integral WARFS components will allow
             scenarios to be run that can quantify the probabilities of various hydrologic conditions
             occurring up to several months in the future. This simulation capability is illustrated in the
             lower right portion of Figure 2-5.

             Figure 2-6 schematically depicts an integrated, operational concept of many of the
             components of an AHPS including WARFS. Shown in Figure 2-6 are data flowing into an
             RFC from multiple WSR-881)s located at WFOs, satellites, aircraft, local flood warning
             systems, data collection platforms, automated surface observing systems, and cooperative
             observers. Also shown are QPFs flowing into an RFC from multiple WFOs and from the
             NMC; other graphical and gridded products also will be provided by the WFOs, the NMC,
             and the National Operational Hydrologic Remote Sensing Center. These vast amounts of
             data and information will be processed and managed by AWIPS. Advanced models and
             analyses will be executed interactively on AWIPS. A whole new generation of products will
             be produced for use in a broad array of applications, including many that will directly impact
             major water management decisions for the Nation. WARFS has been designed precisely to
             provide predictions that will give water managers information critical for more effective
             decisions that mitigate the effects of floods or droughts.



                                                           2-11






















                                                                                                             (numerous)
                                                                                                             vlasatellite,
                                 QPF-WF0 1                                                                 LFWS Coop Obs.
                                            QPF-1 102

                                                                                     (numerous)
                                     0                 a WFO 3


                                                                                                                         Gridded Products Tabular Forecast






                              WfO NEDOUD                                                                                   Hydrograph    Text Products

                                         WFO MEM@ 2







                                 WFO NEXRM 3
                                   NMC and NOHRSC                9 New Hydrometeorological Functions
                                   Graphical and
                                   Gridded Products                Strong Hydrologic Science
                                                                 : Interactive Operation
                                                                 ï¿½ Collaborative Scientific & Developmental Activities
                                                                 ï¿½ Extended Hours of Operation
                                                                 ï¿½ Selected Products for External Users
                                                                                  @@'T







                       fture 2-6. Hydrometeorological operations of a modernized NWS River Forecast Center utilizing AHPS components,
                       including WARFS.










                  Figure 2-7 compares the type of forecast that could have been produced at St. Louis with an
                  AHRPS, including integral WARFS components, to the type of forecast that was made with
                  current capabilities. The current basis for river predictions is only the first portion of the
                  forecast hydrograph shown as the blue line in Figure 2-7. Especially important is the added
                  lead-time and the quantification of forecast uncertainty provided by the advanced prediction
                  system. Figure 2-8 contrasts the accuracy, lead-time, and resolution of current forecast
                  services with those that could be achieved with an AHPS that includes integrated WARFS
                  components.


			FINDING 2.9: Currently, RFCs				RECOMMENDATION 2.9: The
			typically issue stage forecasts for only		Federal Government should press for-
			1,2,and 3 days into the future at most		ward with implementation of WARFS
			forecast points and crest forecasts out to 	which will provide the required
			about 1 week for a few selected forecast		capabilities.
			points. Federal, state, and local groups
			indicated a need for increased lead-
			times for hydrologic forecasts. Many
			expressed the need for a range of 
			forecast stages with associated 
			probabilities of occurrence.


			FINDING 2.10: QPFs are not being			RECOMMENDATION 2.10: If
			used directly, objectively, and			Recommendations 2.6 and 2.9 are
			systematically in hydrologic modeling in		implemented, they will also satisfy the
			Central Region RFCs. In addition, not		requirements to include QPF informa-
			all WSFOs have appropriate software			tion in hydrologic forecasts. The NWS
			and computer equipment to issue QPF			should continue to support scientific
			forecasts for the RFCs. Many users			efforts aimed at producing probabilistic
			understand that QPF products have			QPFs at WSFOs and WSOs through
			inherent uncertainties. Nonetheless,		support of training and research
			many expressed a need for probabilistic		initiatives.
			river forecasts that incorporate QPFs.








									2-13










                                                    St. Louis
                          60.0   -               I              I
                                   Observed River Level
                          55.0   -                         '+L N

                    001'  50.0

                                   Flood of
                          45.0
                                    Record
                                                                MAW 0"a own                  Now .1.6
                                     C=   C@ !!!D7

                    4)    40.0


                                                                             1 St   NV.
                    4)    35.0
                                                                                       Flooding
                                                                                         Begins
                          30.0
                                   Forecast River Level
                          25.0   -


                          20.0
                               6/30           7/7           7/14           7/21           7/28
                                                              Date


              Figure 2-7. Compatison of observed stage (yellow line) at St. Louis, Missouri, during
              The Great Flood of 1993 with hypothetical forecast made on June 30 (blue line), using
              AHPS, including WARFS. Varying confidence intervals around the hypothetical forecast are
              shown by pink shading (one-hay, standard deviation above and below the forecast) and green
              shading (one standard deviation above and below theforecast).
                                                                                 d. Dev.

































                                                         2-14







                                     Gag   Ie Rainfall                                                                                                 NtXR'A6,13ased
                                                  J                                                                                                           Ra nfAl





                                        St. Louis                                                                                                            St. Louis
                                                      I                                                                   St. Louis                        observed Riv'er Le


                                                        r@ C?
                                                         R-.d
                                  >
                                  4)4nm     -Observed RIver Level-
                                                                                                                                                      _j

                                                                                                                                                        Z3.
                                  CCMO   Forecast River                                                                                                 93D Forecast River Level

                                     em    TR   7114 7=1
                                               Date                                                                                                                 Date

                                  FD- mw-4 i
                                     to=


                                                                                                                                                                 RiverG
                                  Forecast PoInt &
                                    PJvw Gage
                                                                                                                                     fit
                                                                                                                   4
                                                                                                                          7
                                                                                                                                                                  Ak-
                                                                                                                                                                            N%Ch-
                                                                                                                                                                            20% M_
                                                                                                                                                               med RIver Level
























                           Figure 2-8. Contrast between current NWSRFS Oeft side of diagram) and modernized NWS AHPS with integral WARFS
                           components (right side of diagram).












                   2.4 NEAR-TERM HYDROLOGIC OUTLOOK AND NEEDS


                   Finally, it is necessary to take all appropriate actions to prepare for the high potential of
                   additional flooding in the Upper Midwest during the spring of 1994. Above-normal soil
                   moisture conditions over large regions of the Upper Midwest and fall rains coupled with
                   winter snow accumulation increase the probability of potential spring flooding in 1994.



		FINDING 2.11: The extensive flood-			RECOMMENDATION 2.11:  The 
		ing of 1993 has created large regions		NWS Office of Hydrology and the 
		with above normal soil moisture condi-		Central Region should provide early
		tions across the Upper Midwest. Con-		and ongoing assessments of potential
		sequently, fall rains and spring snow-		spring flooding in 1994 in the areas
		melt in 1994 may substantially elevate		affected by The Great Flood of 1993.
		the potential for flooding. There is a 		This effort should draw on early experi-
		need for immediate and extended assess-		ences from the NWS modernization and 
		ments of flood potential persisting			pilot WARFS activities wherever possi-
		through at least the spring of 1994.		ble. Additionally, information and data
		Special hydroclimatological assessments		from the Midwest Climate Center and
		done monthly would be valuable.			NMCs Climate Analysis Center should
										be used to support an ongoing assess-
										ment of soil moisture conditions and
										potential future flooding across the
										Upper Midwest. Moreover, the NWS
										should support an enhanced airborne
										soil moisture data collection program
										during the late fall of 1993 and a comp-
										prehensive airborne snow water equiva-
										lent data collection program during the
										winter of 1993-94 over the region
										affected by The Great Flood of 1993.





								2-16



                                                                                                                                








                                             CHAPTER 3


                            HYDROMIETEOROLOGICAL SET17ING





           3.1 PURODUCUON


           Flood stage (i.e., the water level at which a river goes into flood) was exceeded at
           approximately 500 forecast points, and record flooding occurred at 95 forecast points throughout
           the nine-state region. Some forecast points remained above flood stage for as long as 5 straight
           months. As shown in Figure 3-1, St. Louis experienced river stages that exceeded the previous
           flood of record for more than 3 full weeks!









                     so-

                     45-       Proviom Reoord

                     40-
                OD

                     35-


                                                                         Flood Stage
                     30-


                     25


                     20-


                     is  .............

                      Jun 1         Jun 21          Jul 11         Jul 31        Aug 20


              Fligure 3-1. Hydrograph at St. Louis, Missouri. (A hydrograph shows the changes of
              river stage with the passage of time.)





                                                   3-1



























                                                                                                         . ....... .




















                                                                                  a I      I VI
                                                                                              A&


















                        Figure 3-2. Flood-affected counties which received Federal disaster assistance.





                                                                                                  3-2













             The flood event was exceptional due to the combination of several factors:

                    R.      The antecedent hydrometeorology: the scene was set for flooding across the
                            flood-impacted area long before major flooding actually developed.

                    2.      The meteorology: the meteorological pattern that caused the excessive rainfall
                            over the region from mid-June into August 1993 was uncommonly persistent.

                    3.      The magnitude of the flooding: the areal extent of the flooding was unusually
                            large.

                    4.      The severity of the flooding: major to record flooding occurred along dozens of
                            rivers, including portions of the main stems of both the Mississippi and Missouri
                            Rivers.


                    5.      The season of the flooding: major flood events in the upper Mississippi River
                            basin typically occur in spring while this occurred throughout the summer.

                    6.      The duration of the flooding: most significant floods last on the order of days-to-
                            weeks@ while this flood lasted on the order of weeks-to-months.

                    7.      The damage: preliminary estimates establish this as the costliest flood event in
                            United States history.

             All or parts of nine states were declared Federal disaster areas: North Dakota, South Dakota,
             Minnesota, Wisconsin, Nebraska, Iowa, Illinois, Kansas, and Missouri. Within these nine
             states, some 500 counties received some form of Federal assistance (see Figure 3-2).


             3.2 METEOROLOGICAL ANALYSIS


             The flood had its origins in an extended wet period starting 9-10 months prior to the onset of
             major flooding. This wet period moistened soils to near saturation and raised many stream
             levels to bankfull or flood levels. This set the stage for rapid runoff and record flooding that
             followed excessive June and July rainfall. The precipitation was the direct result of major,
             global-scale circulation anomalies which can be attributed to significant climate variations
             (see Section 3.2.4).





                                                            3-3


























                                                                                                                            (a)
















                                                                                                                           (C)                                                                                             (d)



                                                                            F-I       Extrome Drought                                                                       F-I       Unusual Moist Spell
                                                                            F-I       Severe Drought                                                                                  Very Moist Spell
                                                                            F7        Moderate Drought                                Noor Normal                                     Extremely Moist


                                        FIgure 3-3. Selected Palmer (Long-Term) Drought Severity Index maps for the weeks ending: (a) August 15,
                                        1992, (b) November 28, 1992, (c) March 27, 1993, and (d) August 28, 1993. Note the gradual increase with time
                                        in unusually moist soil conditions across the nation's midsection.











                  3.2.1 ANTECEDENT CONDMONS

                  Soil moisture conditions, as measured by the long-term Palmer Drought Index (PDI), for
                  selected times over the preceding year are shown in Figure 3-3. In August 1992, wet soil
                  conditions began to appear in the central Great Plains (Figure 3-3(a)), then increased
                  dramatically by late 1992 (Figure 3-3(b)), encompassing portions of the central, eastern, and
                  southeastern United States. As shown in Figure 3-4, July, September, and especially November
                  1992 were much wetter than normal over the upper Mississippi River basin; winter precipitation
                  was near normal.


                  By late March 1993, extremely moist conditions (PDI > 4) covered much of Kansas,
                  South Dakota, Iowa, eastern Nebraska, southern Minnesota and Wisconsin, and northern Illinois
                  as a result of the combination of the wet fall and spring snowmelt (Figure 3-3(c)). This was
                  followed by above-normal precipitation over the upper Mississippi River basin during April and
                  May (Figure 3-4). Consequently, even before the onset of heavy summer rains, most of the
                  Upper Midwest had saturated soil and well above-normal streamflows.




                                      8



                                      7....................................................................       I ...................



                                      -------------------------------       ....... I..........................     --- ------ --------



                                      5............ .................. . ..................................         ... ...... ........
                                 S

                                 .2   4............ ........    ........................................       .. .. . . ..........



                                        ........   . .. ...     .................................... ..        .. .. ... . ........


                                 CL
                                      2.........   .... ..      .. ... ................. .       ... . ..      .. .. ... . ........
                                      I.........   - __   __    ..        ... .    i   .. i.i.. ... . ..       .. .. .. . ........
                                      0            1                            1 11                           1                      -
                                                7/92       9/92       11 /9i      'I /9i     3/93         5/93      719i
                                                     8/92       10/92      12/92       2/93        4/93        6/93       8/93
                                                                                     Month




                            Figure 3-4. Comparison of average and observed monthly precipitation totals
                            for the upper Mississippi River basin.





                                                                                   3-5













                                                                Uot






                                   54

                                                                               0



                                                                     0.

                                                                                  .%
                                                                        -36

                                                    (a)                                     (b)










                                                      M









                                                                                70
                                                                        70
                                   (7)
                                                             9
                                          Q0


                                                                                (C)
                                                                        7 O@,. 0





             Figure 3-5. June-July 1993 500-mb: (a) heights, (b) anomalies, and (c) percentage of days
             when anomalies were negative (hatched) or positive.

                                                       3-6













             3.2.2 CIRCULATION PATTERNS DURING THE GREAT FLOOD OF 1993

             A highly anomalous and persistent atmospheric pattern of excessive rainfall occurred across
             much of the upper Mississippi River valley and the northern and central Great Plains during
             June, July, and the first half of August 1993, generating devastating record flooding along the
             upper Mississippi and lower Missouri Rivers and many of their tributaries. Much of the major
             river flooding originated from several synoptic-scale, copious rainfall events during mid-June
             through late July.

             This large-scale and repetitive rainfall pattern was just one of many anomalous weather features
             that affected not only most of the United States but much of the Northern Hemisphere.
             Elsewhere in the country during June and July, warmer-than-normal conditions persisted
             throughout Alaska, cooler and wetter-than-usual conditions dominated the Pacific Northwest and
             northern Great Plains states, and hot and dry weather plagued much of the southeastern and
             eastern United States. These weather patterns were all related to a highly anomalous circulation
             that covered much of the Northern Hemisphere, as evidenced by the mean June to July 1993
             500-mb height and anomaly field (Figure 3-5), with particular emphasis on the central
             North Pacific, the United States, the North Atlantic, and Europe.

             Climatologically, a low-pressure trough is located near the Gulf of Alaska during the summer
             months. In April 1993, below-normal sea-level pressures were established in the central and
             western North Pacific Ocean. This pressure anomaly pattern persisted through June. During
             June and July 1993, the mean position of the Pacific low-pressure trough moved west to the
             international dateline. Below-normal sea-level pressures also covered the western United States
             and much of the North Atlantic from Newfoundland to Scandinavia. Corresponding shifts
             occurred in the mean position of the jet stream.

             By the summer of 1993, the mean position of the jet stream had become firmly established over
             the northern portion of the Mississippi River basin with a southwest-northeast orientation. To
             the northwest lay a deep trough of low pressure, while an unusually strong, clockwise circulation
             lay over the eastern United States. Hot and dry conditions were characteristic of the surface
             conditions beneath the ridge. The quasi-stationary jet stream aloft was associated with a
             stationary surface front that allowed frequent and nearly continuous overrunning of the cooler
             air to the north by the moisture-laden air from the south (Figure 3-6(a)). The front also served
             as a preferred location for unusually strong and frequent cyclones, spawned by the combination
             of the unseasonably vigorous jet stream overhead (Figure 3-7) and the relatively strong frontal
             boundary at the surface.






                                                            3-7
















                                              SONABLY

                                               DR,4A










                                Vx






                                                                                                 t MAIM"A
                                                                                                           r 77
                                                                                             A     umt




                                                                               W



                                                                                                                (a)














                                                                    -,jANvi-Scq SONA LY
                                                                    COOL AND RY

                               T RT5,U   R WEsr
                                  UPIA,7fER-LI E
                                  EAT@ER - 0
                                   ANDDRY






                                                                                                    NEA
                                                                                          0    L RA    L







                                                                     ffo                                          (b)



                 Figure 3-6. Dominant weather pattern for the periods: (a) June-July 1993 and (b) early
                August 1993. Note the changes between (a) and (b), particularly across the central
                 United States.


                                                                    3-8































                                                           A






                                                                   Lb












                                                    10L


                                             gu



                                                    ",Oro          LO
                                                                   F1


































                                                                                        t
                                                           Y''



                                                                                                           .... . . . . . . .





                                                                      E-1    4 to 8 mls    F-I    8 ffils or more            (a)




                                                                                                   I t









                                                                                  t t I I I



                                                                                                            T     I 1  4 1




                                                                    F-I 2 to 4 mls        F-I    more than 4 rWs             (b)


                                    FIgure 3-8. Mean 850-mb flow (approximately I mile aloft) for the period
                                    June 5-July 19, 1993, of. (a) vector wind and (b) departure from normal
                                    (base period 1979-1983). Arrows represent the direction and relative
                                    strength of the wind or anomaly.


                                                                                          3-10













              North-south transport of moisture was enhanced by strong low-level advection brought about by
              the unusually large contrast between the trough of low pressure over the northwestern section
              of the Nation and the ridge of high pressure over the Southeast. Much of this low-level moisture
              originated in the subtropics in the vicinity of the warm Caribbean Sea waters (Figure 3-8). The
              increased moisture transport and the presence of the front supported production of widespread
              areas of prolonged and excessive precipitation throughout large portions of the north-central
              United States.


              Finally, by late July and early August, a change in the upper air circulation pattern brought drier
              conditions to the Midwest as the trough shifted eastward, simultaneously increasing rainfall and
              decreasing temperatures in the East while warmer weather returned to the Pacific Northwest
              (Figure 3-6(b)). Unfortunately, locally heavy thunderstorms generated some additional flooding
              problems in parts of the soaked Midwest during mid-August; however, these rains were
              associated with more typical summertime convection caused by frontal passages that were
              enhanced by strong advection of southwestern monsoonal moisture.

              3.2.3 RAINFALL PATTERNS DURING THE GREAT FLOOD OF 1993


              During the summer (June-August 1993), rainfall totals surpassed 12 inches across the eastern
              Dakotas, southern Minnesota, eastern Nebraska, and most of Wisconsin, Kansas, Iowa,
              Missouri, Illinois, and Indiana. More than 24 inches of rain fell on central and northeastern
              Kansas, northern and central Missouri, most of Iowa, southern Minnesota, and southeastern
              Nebraska, with up to 38.4 inches in east-central Iowa (Figure 3-9). These amounts were
              approximately 200-350 percent of normal from the northern plains southeastward into the central
              Corn Belt. Since the start of the growing season (April 1), precipitation amounts through
              August 31 were even more impressive (Figure 3-10): totals approached 48 inches in east-central
              Iowa, easily surpassing the area's normal annual precipitation of 30-36 inches.

              There was considerable variation, both in timing and distribution of heavy rainfall throughout
              the event. Figure 3-11 shows rainfall and the amount in excess of normal for four selected cities
              (Sioux Falls, South Dakota; LaCrosse, Wisconsin; Salina, Kansas; and Des Moines, Iowa). By
              early May, all four cities started to experience excess precipitation; in each area, the surplus
              increased as the summer wore on. For almost a month, starting in late June, the precipitation
              excess at Salina, Kansas, was especially dramatic (see Figure 3-11).








                                                             3-11

















                                                                 0
                                                          0 0





                                               Y.
                                                20-30
                                                30-40
                                                  40          0


                                                       0







                            Figure 3-9. Total precipitation (inches) across the Midwest for the
                            period June ]-August 31, 1993.



                                                        0    0
                                                        0 0    0
                                                                     CD
                                                             0              0



                                          KEY-
                                          r-71 20-30
                                              30-40      00
                                                40






                                                                                   0


                                                                                      0



                            Figure 3-10. Total precipitation      (inches) across the Midwest for the
                            period April ]-August 31, 1993.


                                                                  3-12









                      750 -    Sioux Falls, SD             30           750-     LaCrosse, WI                _U
                      625 -     Above Normal               26           625-     Above Normal                25
                                                                0     -                                           T
                                                           20         E                                      20
                      Soo -                                     9     E Soo-
                    C
                    0
                    :g 375 -                               is   0       375-                                      a
                                                                      CL                                          a
                                                           .10  RI                                           .10  211
                      250 -                                     a     9
                    IL                                          0     it 250-                   Normal
                      125 -                     Normal - s      [L      125-                                    5 IL
                        0          Below Normal               0           0      Rplow Norajal                  0
                            APR MAY JUN JUL AUG                               APR MAY JUN JUL          AUG
                                        Date               (a)                            Date               (b)



                                  Salina, KS                                     Des Moines, IA

                     1000 -                                40          1000 -                                40
                                                                T                      Above Normal
                    '9       Above Normal                       Q)    E
                    E 760-                                 30         r: 750-                                30
                                                                                                                  C
                                                                      .2
                                                                                                                  0
                      Soo-                                 20           Soo-                                 20
                                                                At
                                                                BL

                    IL                                                IL
                      260.                    Normal       10           250-                      N mal      10
                         0                                                0           Below Normal
                                                              0                                 1    1 --il 0
                            APR MAY JUN JUL AUG                                APR  MAY JUN JUL AUG
                                        Date               (C)                            Date               (d)



             Figure 3-11. Cumulative precipitation (inches) for the period April 1 -August 31, 1993,
             compared to normalfor. (a) Sioux Falls, SD, (b) LaCrosse, R7, (c) Salina, KS, and
              (d) Des Moines, LI.
                                                                                                  No   mal

                                                                                                orm
                                                                             []B@elow @Narl


                                                                 3-13


















                                                                                                   100
                                                                                                                     0         Qz










                                                                             00









                                                                      ------- ----     100





                                                                     (D




                                                                                                                                              00









                                                                                                                                    100
                                                                                                                                      100


                                                                                                                     13





                                                                                         00






                                                                      C).





                                                                                              100                                 1      100
                                                                                                                                              (b)


                                         FIgure 3-12. Monthly precipitation as a percent of nonnal for. (a) May
                                         1993 and (b) June 1993.

                                                                                                        3-14









              From a seasonal standpoint, above- to much above-average rainfall fell over the entire Upper
              Midwest from May through August 1993 (Figures 3-12 and 3-13). The May-August 1993
              rainfall amount is unmatched in the historical records of the central United States. In July, there
              were broad areas in North Dakota, Kansas, and Nebraska, as well as a smaller pocket in Iowa,
              that experienced more than four times normal precipitation. Rainfall amounts, and their return-
              interval frequencies for selected midwestern states, are listed in Table 3-1. The April-July
              values are exceptional in all states but Missouri, and the June-July values have return intervals
              of 75 years or more. The June-July precipitation amounts are remarkable not only in magnitude
              but also in their broad regional extent. Record wetness existed over 260,000 square miles. The
              Missouri July values were tempered by below-normal rainfall in the extreme south, although
              some areas of northwestern Missouri had more than 30 inches of rain in July alone. Seasonal
              rainfall records were shattered in all nine states.


              3.2.4 POSSEBLE CAUSES OF 1993 MIDWEST HEAVY PRECIPITATION

              An El Nifio/Southern Oscillation (ENSO) episode occurred during 1992 and 1993. In 1992,
              similar but less intense circulation features were observed; however, no extreme flooding
              occurred in the United States. Nonetheless, the current, long-lived ENSO event probably
              contributed to the large-scale atmospheric features associated with the persistent 1993 Mississippi
              and Missouri River valley flooding.







                 Table 3-1. Cwnulative precipitation arnounts and return periods for several
                 midwestern states.



                                                  APR11,JULY                                JUNE-JULY

                        STATE              Amount            Frequency               Amount             Frequency
                                              (in)              (years)                 (in)               (years)

                     Iowa                     27.1                 300                  18.1                  260

                     Illinois                 22.9                 45                   14.7                   85

                     Wisconsin                22.0                 200                  12.3                   75

                     Minnesota                18.9                 70                   12.2                  100






                                                                   3-15























                                                                                                                                                 .100

                                                                                                                                                                 10C











                                                                            1w




                                                                        'C









                                                                                                    00

                                                                                                                         50-200                               (a)
                                                                                                                           200
                                                                              100           100-

                                                                                                                                         loo



                                                                            100


                                                                                                                                                                 100




                                                                            100



                                                                                                                                                               I
                                                                                                                                                          100






                                                                        4DN



                                                                                                                                                                  100






                                                                            100
                                                                                                                                 100
                                                                                                                                                               (b)


                                             FIgure 3-13. Monthly precipitation as a percent of normalfor. (a) July
                                             1993 and (b) August 1993.

                                                                                                                   3-16










                 There has been some speculation that the 1993 flooding may have been associated with
                 greenhouse-gas-induced global warming and related circulation changes. Although results from
                 most numerical climate models have suggested that central North America would be drier in a
                 warmer climate, this has also been interpreted as a possible indicator of more variable and
                 extreme weather conditions. Thus, both extreme flooding and extreme drought could be
                 interpreted as being consistent with the global warming hypothesis. Accordingly, the 1993
                 floods do not add conclusive evidence to the present debate on the possibility of greenhouse gas
                 warming.

                 In like manner, the eruption of Mt. Pinatubo in June 1991 has likely affected the global mean
                 temperature, but the exact nature of the changes in circulation are not known. It would be
                 difficult to directly link the current Mississippi floods to that, or any other, volcanic eruption.
                 It is only through the entire global heat balance that volcanic aerosols could have an effect on
                 storm tracks and persistent anomalies in the atmospheric circulation. As with the global
                 warming hypothesis, experiments with numerical models in conjunction with further data
                 analysis may shed some light on the role of the Mt. Pinatubo aerosols in shaping the global
                 circulation and specific rainfall patterns.

                 It may be that the ultimate "cause" of the extreme and persistent precipitation in the central
                 United States is a combination of all the factors discussed above in conjunction with natural
                 variability in the climate system. All of these mechanisms combined, however, seem less likely
                 than the direct influence of the sea surface temperature (SST) anomaly in the tropical Pacific
                 associated with the ENSO.


                 Preliminary tests using the current ENSO-related SST anomalies in a numerical climate model
                 at the National Meteorological Center show a response in North America that resembles the
                 observed precipitation and temperature anomaly pattern to a considerable extent. It will take
                 more in-depth and thorough analyses involving both observations and coupled ocean/atmosphere
                 global circulation models to get a definitive understanding of the role of the tropical Pacific in
                 the current, extreme precipitation events.



			FINDING 3.1: The duration and 				RECOMMENDATION 3.1: 
			magnitude of The Great Flood of 1993,			Additional analyses of this situation, by
			as well as its antecedent conditions,			both research and operational 
			strongly support the premise that this 			communities inside and outside of the 
			event was a significant climate variation			National Weather Service, should be
			rather than simply a sequence of 				encouraged. The Great Flood of 1993
			meteorological incidents.					should be considered as a climate time-
												scale variation or anomaly, which may 
												be attributable to a combination of
												atmospheric, oceanic, and land factors,
												such as circulation, temperature, soil
												moisture, and their complex interactions.






									3-17









               3.3 HYDROLADGIC ANALYSIS


               Extreme flooding of major river systems like the Mississippi and Missouri Rivers seldom occurs
               in the summer because of the highly variable nature (in space and time) of convective rainfall
               in the Midwest, coupled with high rates of evapotranspiration. Typical midwestern summers
               experience a few localized heavy rain events with as much as 6-12 inches in 1-2 days extending
               over a few thousand square miles. They are usually randomly distributed, producing localized
               flash floods on streams and tributaries but are not normally sufficient to produce major river
               flooding of any consequence.

               Another common aspect of the precipitation climate of the midwestern summer involves
               atmospheric conditions capable of producing above-average rainfall over sizable (state-scale)
               areas across the Midwest. When these conditions do not occur, the Midwest has summer
               droughts; an extreme drought occurred in 1988. These "wet periods" typically persist for
               2-5 weeks and sometimes last up to 8 weeks, creating the "wet summers" found in the climatic
               record. Excessively heavy rain extending over wide, multistate areas and lasting more than
               8 weeks, however, is a rare event. The combination of long-lasting and spatially extensive wet
               conditions in the summer of 1993, along with exceptionally wet antecedent hydrologic
               conditions, were necessary to produce the massive summer flooding of this magnitude and
               duration.


               The Mississippi River flood at St. Louis approached the 100-year return period. The flood
               return period exceeds the rainfall return period (see Table 3-1) because the flood at St. Louis
               was the culmination, or combination, of the heavy, record rains on the lower Missouri basin
               being closely timed with those on the upper Mississippi basin. The floods 200 miles above
               St. Louis on each river broke historical records; when the rivers merged just above St. Louis,
               they created an even more exceptional flood.

               3.3.1 ANTECEDENT CONDITIONS AND HYDROLOGIC SETTING


               Since late in the summer of 1992, conditions were wetter than normal over much of the lower
               Missouri and upper Mississippi River basins. Minor flooding began as far back as December
               1992 in some locations as a result of very heavy November rainfall over the upper Mississippi
               basin (see Figure 3-4). Soils were very wet at the onset of winter (Figure 3-3(b)). These high
               moisture levels were locked into the soils as the ground froze.

               Although winter precipitation was near normal (Figure 3-4), with moist antecedent conditions,
               due in large part to the heavy November rains, flooding began in late March with snowmelt.
               Because of the frozen ground, and then later because of the moist soils, runoff could not be
               absorbed by the soils. Rivers in the Dakotas, Minnesota, Nebraska, Iowa, Illinois, Kansas, and
               Missouri rose rapidly. In late March, the National Hydrologic Outlook identified the impacted
               areas as having "above-average flood potential" (see Figure 3-14).




                                                            3-18

























                         Above Average
                         Average
                         Below Average
                                                                                                        __j

              Figure 3-14. National Hydrologic Outlook issued March 29, 1993, identified above-
              average flood potential for much of the area affected by 7he Great Flood of 1993.

             April saw the start of a prolonged period of very wet weather (see Figure 3-4). The period from
             April through June was the wettest observed in the upper Mississippi basin in the last 99 years.
             The moisture conditions across the north-central United States on May 1, 1993, can best be
             described as "saturated." The extremely wet, cool spring of 1993, coupled with normal to
             above-normal precipitation in the summer, fall, and winter of 1992-93, caused significant spring
             flooding in the upper Mississippi River basin. Soil moisture conditions, from the surface to a
             depth of 6 feet, across most of the nine-state region were at "field capacity" (90-100 percent
             where 100 percent equals field capacity for any given soil type) by the end of May when values
             are normally less than capacity.

             The Midwestern Climate Center, located in Champaign, Illinois, provided maps of plant
             available moisture (expressed in percentages) at the 12-inch soil depth (Figure 3-15) to illustrate
             the evolution of the wet soil conditions during the spring and summer of 1993. Values matching
             field capacity were regionwide on April 1, decreasing somewhat during April as evapo-
             transpiration from new plants and growing crops began to be realized. Note, however, that by
             June 1 most of the Midwest had values of 100 percent or higher, indicating widespread
             saturation of most soils due to the extremely heavy May rains.




                                                            3-19












                                             80                       (a)                     80                         (b)


                                                                                     80
                                                   80                                                              80
                                  80
                                                                                                                      80







                                           80                        (C)                80                              (d)
                                                  al
                                                                                    80


                                                        80
                                  80
                                                                 80                                            80

                                                                   80


                                                                                           . . . . . . ... .







                                      so                            (e)

                                80

                                                               80





                                                                      so



                                                                    80


                                                                                         8


                                               80                                            80
                                                             El    > 100910            > 120%


                  Figure 3-15. Percent of plant available moisture at 12-inch depth for.- (a) March 1, 1993,
                  (b) April 1, 1993, (c) May 1, 1993, (d) June 1, 1993, (e) July 1, 1993, and (t) August 1,
                  1993.


                                                                           3-20










                  In addition, the Midwestern Climate Center has been issuing, on a monthly basis, since the end
                  of August 1993, monthly assessments of soil moisture. When the soil moisture model is coupled
                  with historical climate data for the upper Mississippi River basin, it can provide estimates of the
                  probability of future soil moisture conditions and related flooding potential outlooks for periods
                  during the coming fall, winter, and spring. As indicated in Section 3.3.3, this information will
                  be central to providing early warning of potential flooding in the spring of 1994.
                                               

			FINDING 3.2: The soil moisture 			RECOMMENDATION 3.2: The 
			models for the Midwest, operated by the		National Weather Service and, in
			Midwestern Climate Center, can provide		particular, the River Forecast Centers,
			a constanly updated assessment of 			should obtain soil moisture information
			regional soil moisture conditions and a 		from the Regional Climate Centers to
			probability of future soil moisture			enhance near real-time monitoring of
			potential critical to an evaluation of		hydorlogic conditions and to guide
			longer-term flood potential. In addition,		preparation of flood potential outlooks
			the High Plains and Northeast Climate		The remaining Regional Climate Centers
			Centers also provide soil moisture			should be encouraged to consider
			information.						providing soil moisture information.

                  3.3.2 REVIEW OF MAJOR FLOODING

                  The record-breaking, heavy, late-spring/summer rainfall amounts and the ensuing record-
                  breaking summer floods evolved from six factors during the spring and summer of 1993. These
                  factors combined in a unique fashion to cause record-high flows on the lower Missouri and
                  portions of the upper Mississippi Rivers, as well as on many of their tributaries. On June 1, all
                  conditions in the hydrologic cycle favorable for flooding were present:

                        1.Persistence of Saturated or Nearly Saturated Soils
                             Already nearly saturated soils on June 1 (see Figure 3-15) became more saturated
                             during the month. By July 1, when typical midwestern values are 60-70 percent,
                             the plant available moisture values were at total saturation as reflected by the
                             enormous area of 120 percent or higher across Iowa, much of Missouri, central
                             and northern Illinois, southwestern Wisconsin, and southern Minnesota. Values
                             by August I were still abnormally high (50-60 percent is typical), indicating that
                             near saturated soils prevailed in a large, northwest-southeast zone paralleling the
                             upper Mississippi River.

                        2.High Incidence of Rain Events
                             A critical factor affecting the record flooding was the near continuous nature of
                             the rainfall. Many locations in the nine-state area experienced rain on 16-22 days
                             in July, compared to an average of 8-9 days with rain. There was measurable
                             rain in parts of the upper Mississippi basin on every day between late June and


										3-21
 








                               late July. The persistent, rain-producing weather pattern in the Upper Midwest
                               (see Figure 3-6), often typical in the spring but not summer, sustained the almost
                               daily development of rainfall during much of the summer.

                    3.      Large-Sized Rain Areas
                               The semi-stationary nature of the convectively unstable frontal conditions across
                               the Upper Midwest from June through early August not only caused the near
                               continuous occurrence of daily rains but also frequently created extensive areas
                               of moderate to heavy rains. Frequently, a day in June or July 1993 would have
                               rain areas that were 100-200 miles wide and 400-600 miles long (typically about
                               75,000 square miles) across parts of the nine-state area. Most of these rain areas
                               included zones with 1-2 inches of rain over 5,000-15,000 square miles. An
                               excellent example of such rain areas is the isohyetal map of July 7 rain across
                               central Missouri (Figure 3-16). A few such large-sized areas of convective
                               rainfall normally occur in most midwestern summers, but their high frequency in
                               1993 (at least 73 such cases) with quite large dimensions capable of affecting both
                               the Missouri and Mississippi River basins was exceptional.

                    4.      Orientation of Rain Areas
                               Several multi-day periods in June and July had large rain areas (see previous
                               section) that were oriented along the major rivers. In late June, several large rain
                               areas were aligned northwest-southeast over the Mississippi River from northern
                               Illinois into central Minnesota. Then, in early July, similar systems became
                               aligned southwest-northeast along the Mississippi's course from Quincy, Illinois,
                               to southern Wisconsin, at the time the flooding was maximizing in this reach of
                               the river. In early to mid-July, several large rain areas were oriented west-east
                               along the Missouri River and across Missouri. Such alignments deposited
                               enormous amounts of water directly into the main stems of the rivers without any
                               delay for runoff and in-stream storage in the tributaries.

                    5.      Extremely Large Number of Localized Heavy Rains CV-able of Producing Flash
                            Floods
                               Intermixed with the frequent incidence of large areas of moderate to heavy
                               rainfall, as described in (2) and (3) above, were many intense rainstorms having
                               "flash flood" characteristics. These rainstorms are defined here as discrete areas,
                               typically 1,000-5,000 square miles in size, where as much as 6-12 inches of rain
                               falls in 24 hours or less. The isohyetal map of the large July 7 rain area across
                               central Missouri (Figure 3-16) contains three such intense, 6-inch centers.
                               Another version of this type of storm is depicted in the isohyetal map for a 4-hour
                               rainstorm that occurred in south-central Wisconsin on July 18 (Figure 3-17). The
                               early count of such storms indicates that at least 175 occurred in the nine-state
                               area of excessive flooding from early May through August. This number of
                               intense, short-lived rainstorms is probably a record for the Upper Midwest.



                                                               3-22




















                                                     %
                                                                     I.............
                                                               ...........I
                                                                                . .........                                      Miles


                                                       ..........
                                                                            ........              ............              0       25 50
                                                                ...........

                                        ...........   ...........
                                                ..........
                                                                                           ----------- %.-L
                                                                                                                ...........


                                                                                                ..........
                                                                  IN                                             L*             . .....
                                            2

                                            4- -----
                                                          ............. '.6
                                                                                                 '6
                                                                                                                                    2
                                                                                                      7-
                                                               6
                                          41%
                                                                                                          . .. .......
                                                                                                                                             2
                                            2




                                                                                                                                       ------- ---- -
                                                                                                                ...............

                                                                   is .... .........                                           ..........
                                                ...... . .....



                                                                    ........       ...
                                                                                     ..............................
                                                ------------                                                                  ----------

                                                                                                                     ----------

                                                            4

                                                1 2                2'1



                    Figure 3-16. Analysis of total observed precipitation in central Missouri for the 24-hour
                   period ending 7 a.m. CDT, Juty 7, 1993.



                          6.         Seasonal Evapotranspiration Below Normal
                                          The near continuous cloud cover of the June-August period (50 percent of the
                                          days were cloudy compared to a normal of 20 percent), coupled with
                                          temperatures which were 2-3 degrees below average and a very moist lower
                                                      e
                                          a
                                            tmosph     re,   reduced actual evapotranspiration to below-normal levels. This
                                                I
                                                I

































                                          reduced the upward movement of moisture from the soil and increased the flood
                                          potential.



                                                                                       3-23













                                                                                                                                            Marquette

                                                                                                         Adams
                                                                                                                                                                          -----------
                                                                                                                                                        Monfello
                                                                                                                                                                                     Green Lake
                                                                   Juneou





                                                                                               Wisconsin     Dells




                                                                                                                          ------- --                    rt096         Fordeeville
                                                                              Reeclsburg
                                                      .............. . .....
                                  .......... . ...............                                                               '_* @19                            4
                                                                                                                    Baraboo                          6
                                                                                                                                                                            2

                                                                                                                                0;
                                                                                                                                                                            Columbia
                                                                                                                        12
                                                                                                                                     8
                                                                                                                                                                 neffe


                                         Richland
                                                                                    Sauk                                                                                        ...............
                                                                                                                              ... . . .. ... ......................................... . .... . .......... ...........
                                                                                                                                                               ... .. ... .......................

                                                                                                                       1 Pairis du Sac

                                                                                                                                                                                                         ............. ------

                                                                                                                                                           Done


                                                                                                                                                                                                  Miles


                                                                                                                                                                                          0          5         10



                                Figure 3-17. Analysis of 24-hour precipitation event ending at 7 a.m. CDT on July 18,
                                1993, in south-central Wisconsin. Most rain fell in 4 hours or less.


                                In summary, the genesis of The Great Flood of 1993 had been set by June 1 with saturated soils
                                and filled streams across the Upper Midwest. The water from the ensuing persistent heavy rains
                                of June, July, and August had no place to go other than into the streams and river courses.
                                Record summer rainfalls with amounts achieving 75- to 300-year frequencies thus produced
                                record flooding on the two major rivers, equalling or exceeding flood recurrence intervals of
                                100 years along major portions of the upper-Mississippi and lower Missouri Rivers.

                                3.3.2.1 MAJOR FLOODING IN JUNE

                                Rainfall during the first half of June was typical of late-spring conditions in the upper
                                Mississippi and lower Missouri basins: scattered pockets of heavy, convective precipitation.
                                As discussed throughout Section 3.2 above, in mid-June a stable, high amplitude, upper-level






                                                                                                                           3-24








             pattern, more typical of late-winter or early-spring conditions, created persistent, excessive rain
             over much of the Upper Midwest. Major flooding began after a particularly heavy rainfall
             period (June 17-20; see Appendix B, Section B. 2.2. 1) in southwest Minnesota and northwest
             Iowa. This included record flooding on the Minnesota River.

             The next major precipitation impulse occurred June 23-25. This water combined with flood
             flows from the Minnesota River to initiate the first major flood crest that moved down the
             Mississippi.

             3.3.2.2 MAJOR FLOODING IN EARLY JULY

             Following a short, dry period, a prolonged siege of heavy rainfall extended from June 30 to
             July 11. This included extreme precipitation on July 9 in Iowa, which resulted in record
             flooding on the Raccoon and Des Moines Rivers (see Appendix B, Section B.2.2.2). Just as the
             crests from these two rivers reached Des Moines, a relatively small, convective pocket dumped
             several inches of rain on the crests rapidly boosting the river levels and flooding a water
             treatment plant. This rainfall event also led to record flooding on portions of the lower Missouri
             River and combined with the crest already rolling down the Mississippi, ensuring record river
             stages from the Quad Cities area, through St. Louis, and as far south as Thebes, Illinois.

             3.3.2.3 MAJOR FLOODING IN LATE JULY

             Another major precipitation impulse occurred July 21-25 (see Appendix B, Section B.2.2.3).
             The heaviest rains were focused farther south than the earlier events, with especially heavy rain
             falling over eastern Nebraska and Kansas, leading to second major crests on both the Missouri
             and Mississippi Rivers. An example of the river stages at Kansas City is shown in Figure 3-18.
             The hydrograph at the Quad Cities (Figure 3-19) shows only a single crest, demonstrating the
             generally southern focus of this second event. At St. Louis, both crests are clearly evident in
             the hydrograph (see Figure 3-1). While flooding did not extend as far upstream on the
             Mississippi, new record crests were observed at many locations downstream, as well as on much
             of the portion of the Missouri River that flows through the state of Missouri.

             The crests on the Missouri and Mississippi Rivers are summarized in Figure 3-20. The solid
             squares in both Figure 3-20(a) for the Missouri River and Figure 3-20(b) for the Mississippi
             River show the previous floods of record. The highest stage reached on each river during the
             first record-breaking crest in early to mid-July is indicated by the solid line. Similarly, the
             dashed line is the highest level reached during a second flood wave that occurred in the later part
             of July and into early August. On the Missouri River, the second flood wave was higher than
             the first at most locations south of Omaha, where many new records were set. The river levels
             of the two flood waves were more similar on the Mississippi River. Every gage, from the
             Quad Cities to below St. Louis, set new, all-time record stages!





                                                            3-25













                              65-

                              so-       148.92 Fed on Juh@f @27:0@993
                              45-                                         Previous Record (46.2 Feet) on July 14,1951

                              40-


                              35-


                              30-


                              25-


                              20-


                              Is                                                   .........

                                jull 1                 Jul2l                  Aug 10                  Aug 30


                     Fgure 3-18. Hydrograph for Missouri River at Kansas City, Missouri.




                            24-                       1 MO Fed on

                            22-                                        Previous Record (22.5 Feel) on April is-, I @gw

                            20-






                            16-
                                                                                          Flood Stage


                            14-



                            12-


                            10                   . ..............                    ...........

                             Jun I           Jun 21           Jul 11          Jul3l           Aug 20
                     1          --                        -                                                       I
                     Figure 3-19. Hydrograph for Mississippi River at Quad Cities.



                                                                 3-26

























                                                           6-



                                                                                                                                                              U)
                                                           4-                                                                                                 9
                                                                                             4j
                                                                                                                                                      -10     8
                                                           3-


                                                           2-


                                                           1
                                           ND

                                                           0-                       - - - - - - - - - - - - - -                                            0
                                                                - 7@'- -
                                   8D                      .1-         Omaha                  A  Kane' ,City ' Jffro,n City
                                                                                        St. Joseph              Miami                  St. Charles
                                           NE              IA               Previous Record            First Crest       -Second Crest'
                                                  8L we"           IL
                                                           wani
                                            K9 Mw@ r.,
                                                           j.ft.. CRY
                                                                M0
                                                                                                                                                             (a)



                                 MN

                                                                                                                                                      -26

                                                                                                                                                      -20     (D
                                    2.1         W1              (D 0-
                                                                CD
                                           C@
                                                                4-
                                      IA                                                                                                              -10
                                           ou.d ju@                                         A
                                                  IL            2
                                                                E                                                                                             0
                                                                0
                                        Mo     T                                     - - - - - -                                                           0
                                                                0                                                                       7/ N17
                                               N_    , KY
                                                                                                                                        7,-'s-             -6
                                                     T          -2-
                                                                                                                                                           10
                                           AR                   -4          A               A      A               A                 A     A      A
                                                                     Minneapolis     Quad Cites St. Louis           Memphis       Red R. LandIng
                                                  Ms                          LaCrosse        Hannibal Now Madrid              Vicksburg New Orleans
                                        LA,I.     rq                                              -- -; First Crest      -Second-dr-est
                                      R FL LaAin                            Previous Record








                    Figure 3-20. Swwnary offlood crests on the (a) Missouri and (b) Mississippi Rivers during
                    7he Great Flood of 1993.

                                                                                              3-27









                A stffl&g feature of Figure 3-20(b) is the rapid drop in the flood crest about 200 miles south
                of St. Louis. The large channel capacity of the Mississippi below the confluence with the Ohio
                River contributed to this dramatic reduction as the crests moved into the lower part of the
                Mississippi River (see Figure 3-21). The first four bars in Figure 3-22 show the normal
                seasonal variation of discharge in the Mississippi River system and the relative contributions of
                the major tributaries to flow at the mouth of the river as it empties into the Gulf of Mexico.
                While flows in the upper portion of the Mississippi basin were record brealdng (about five times
                the seasonal norm at St. Louis on August 1, as shown in the right bar in Figure 3-22), the
                discharge on the lower Mississippi was only modestly higher than typical springtime flows but
                more than twice the seasonal average.















                                          MISSWO





                                                              00                   No













               Figure 3-21. Schematic shoudng typical relative contributions toflow of large rivers in the
               Mississippi River system.




                                                              3-28











                    40000                                                                  F__1
                                                                                           ottw
                                                                                           EM
                    35000-                                                                 Ohio
                                                                                           Em
                                                                                           Upper W3sl3sippi

                                                                                           h0lissourl
                  0


                  V1
                    '2,05000000
                  CD
                  E 20000-
                  .2
                  -0


                    15000-

                  U)


                    10000-
                  Ma



                     5000


                        0          Jan.       Apr.      my        Oct.    Est. 8/1/93
                                                       Month


                Figure 3-22. Normal annual variation of discharge near the mouth of the lower
                Mississippi River compared to the discharge on August 1, 1993 (fight bar), which
                includes the exceptional flow from both the Missouri and upper Mississippi Rivers.



            3.3.2.4 FLASH FLOODING


            Flash flooding is a rapid, localized rise in water levels in smaller streams or in low spots.
            While flash flooding can be caused by ice jams and dam breaks, it most commonly occurs as
            a result of intense, shorter-duration, convective rainfall. As mentioned above, The Great Flood
            of 1993 included numerous precipitation events that would typically be associated with flash
            flooding. However, as is the case in quite a few major floods, the distinction between flash
            flooding--short duration (6-12 hours) and smaller areal extent (several hundred square miles)--
            and major river flooding becomes blurred. During the summer of 1993, many of the events with
            rainfall intensities typical of flash flooding were far more widespread and lasted considerably
            longer than "classical" flash floods. Indeed, The Great Flood of 1993 (and other historical
            floods) can be considered to result from the cumulative effect of unusual numbers of substantial
            flash flood events (combined with anomalous antecedent climatological conditions). There were
            at least 15 flash floods that caused dam breaks; the majority occurred in Wisconsin during
            The Great Flood of 1993.





                                                          3-29

























                                                                                                                                                           . . . . .. . . . . . .


                                                                                         . . . . ...                    St   Paul


                                                                                                                        . . . ... . . . .
                                                                                      ma   a
                                                                                  0 h*
                                                                           ..................


                              .. .................

                                                                                                                        Rock
                                                                                                                                 is


                                                                                                            . . . . . . . . . . ..




                                                                                         . . . .     ansas Ci

                                                                                                                                       St. Louis

                                    ...........
                                                 . .........
                                                           ..........................
                                                                                     -------------------------------------------------                  ...........
                                                                                                                                                 ..........
                                                                                  ...............                                 ...............
                                                                                                                        t--------------
                                       Miles

                                                                                                                                              . .........  --------------
                                 0       100     200



                      FIgure 3-23. Corps of Engineers Districts and their boundaries.



                      3.3.2.5 WATER CONTROL STRUCTURES


                      Flood Control Reservoirs


                      Throughout the upper Mississippi and Missouri River basins, 66 flood control reservoirs exist.
                      Many of the reservoirs were developed for flood control purposes but were not designed for the
                      magnitude of The Great Flood of 1993. For example, inflow into the U.S. Army Corps of
                      Engineers (COE) Coralville Reservoir, located in Iowa, during the summer of 1993 was several
                      times its total storage capacity. Reservoir storage was quickly maximized during the early
                      portion of The Great Flood of 1993. Persistent, heavy rain led to uncontrolled discharges over
                      spillways of some reservoirs during the later stages of the flood.

                      A major exception to the pattern of overfilled reservoirs occurred in the upper reaches of the
                      main stem of the Missouri River basin, where the COE operates six enormous reservoirs for
                      multiple purposes. When operated for flood control, these projects provided relief to the


                                                                                         3-30









            downstream reaches of the Missouri River by releasing less water than normal. One benefit
            associated with The Great Flood of 1993 was that additional ainounts of water retained in the
            upper reaches of the Missouri River refilled the main projects ending the long-standing drought
            effects.


            Levees

            Many people made valiant efforts to prevent levees from overtopping on the Red River of the
            North, upper Mississippi, and Missouri River basins. Farmers, residents of both small and large
            towns, COE employees, out-of-state volunteers, Emergency Management Agencies, and
            contractors spent countless hours struggling to protect homes, farms, towns, bridges, and cities.
            in spite of these efforts, as shown in Table 3-2, 18 percent of Federal levees and 78 percent of
            the non-Federal levees failed or were overtopped. The districts identified in Table 3-2 are
            shown in Figure 3-23. The difference in the failure rate is due to the fact that most Federal
            levees are designed to withstand a 100-500 year flood, while non-Federal levees, predominantly
            protecting agricultural lands, are frequently designed for a flood with return periods of 50 years
            or less. Such a failure rate for a flood such as The Great Flood of 1993 is not surprising.



            Table 3-2. Distribution of levee failures by Corps of Engineers Districts.




                                             NUMMER OF FAILED OR OVERTOPPED LEVEES
                    COE DISTRICT                        Federal                     Non-Federal

                    St. Paul                             I of 32                         2 of 93

                    Rock Island                         12 of 73                       19 of 185

                    St. Louis                           12 of 42                        39 of 47
                    Kansas City                          6 of 48                     810 of 810
                    Omaha                                9 of 31                     173 of 210

                    Totals                            40 of 226                    1043 of 1345



                        Note: In some cases, a single levee has been divided into a series of levees according to
                        local levee district and is counted as more than one levee.






                                                            3-31









               It is noteworthy to mention the flood-fighting efforts that took place in the COE Rock Island
               District. Major levee systems were saved by scalping dirt landward of the levee and compacting
               it on top of the levee. Flash boards made of plywood and supported on the dry side of the
               levees provided an additional 4 feet of protection.

               The COE has begun damage assessment directed by Public Law 84-99 to determine the cost of
               rehabilitating levees governed by this law. Under this authority, the COE may rehabilitate
               publicly sponsored flood control projects damaged or destroyed by floods to their pre-flood
               condition. Congress has appropriated $120 million to perform Public Law 84-99 activities.

               3.3.3 FUTURE FLOOD POTENTIAL


               A central issue for responding to and recovering from The Great Flood of 1993 is the potential
               for ftiture flooding in the flooded areas. Floods of almost any dimension would be detrimental
               to efforts in rebuilding levees, highways, homes, towns, and even in raising crops in 1994.

               At the end of August 1993, soil moisture remained well above normal throughout most of the
               nine-state area. VVhile some grain crops were harvested in 1993, the summer's grain production
               was seriously depressed. Evapotranspiration and surface runoff were inadequate to restore
               conditions to normal as winter approached.

               Flooding could easily occur if a period of heavy rain develops in parts of either basin. The
               onset of winter with above-normal soil moisture conditions presents a situation very conducive
               to spring snowmelt floods. If the amount of winter precipitation is normal or above, spring
               flooding in the Upper Midwest in 1994 is quite likely.
























                                                           3-32









                                                    CHAPTER 4


             HYDROLOGIC AND HYDRAULIC FORECAST METHODOLOGY




             4.1 IN71 LODUCTION

             Operational software systems required to generate hydrologic forecasts for river basins of the
             magnitude of the Missouri and upper Mississippi Rivers, as wen as the Red River of the North,
             are extremely complex. The National Weather Service River Forecasting System (NWSRFS)
             contains a variety of models, procedures, and techniques. This chapter describes the hydrologic
             and hydraulic components included in operational river forecasting systems, the methodology
             used to forecast river stages during The Great Flood of 1993, and the forecast methodology that
             is planned for the future.


             4.2 PHYSICAL DESCRUMON OF MAJOR RIVER BASINS AFFECTED BY
                    THE GREAT FLOOD OF 1993


             The upper Mississippi River basin, located in the north-central United States, extends about
             775 miles south from its headwaters in Minnesota and stretches in width about 650 miles from
             northeastern South Dakota to northwestern Indiana (see Figure 4-1). The length of the upper
             Mississippi River is 1,366 miles with a drainage area of 189,000 square miles. The basin covers
             parts of eight states (Minnesota, Illinois, Iowa, Wisconsin, Missouri, Indiana, South Dakota, and
             Michigan) but does not include the Missouri River and its tributaries. From its headwaters in
             Lake Itasca to Minneapolis-St. Paul, the Mississippi River drops at an average rate of almost
             2 feet/mile. From Minneapolis-St. Paul to Cairo, Illinois, the Mississippi has an average slope
             of only 0.6 foot/mile. Table 4-1 lists the major tributaries of the Mississippi River and their
             drainage areas. The North Central River Forecast Center (NCRFC) in Minneapolis, Minneota,
             is responsible for forecasting the upper Mississippi River basin.

             The Red River of the North is formed at the confluence of the Otter Tail and Bois de Sioux
             Rivers below the cities of Wahpeton, North Dakota, and Breckenridge, Minnesota. The river
             flows north for about 400 miles before reaching the United States-Canadian international
             boundary where it continues north into Canada. Drainage into this river includes parts of
             North Dakota, South Dakota, Minnesota, and Manitoba, with 40,200 square miles of the basin
             located in the United States. Most of the basin is extremely flat. The NCRFC is responsible
             for forecasting the parts of the Red River basin located in the United States.





                                                            4-1




















                                                                                                                                                                                                            . .. . .........
                                                                                                                                                                                                                                           ...........

                                                                                                                                                                                                                                                                              Red Basin







                                                                                                                                                                                                Missouri Basin
                                                                                                                                                                                                                                                                                                     T-1

                                                                             ..........
                                                                                                                                                                                                                                                                                                                                Upper                       Mississippi
                                                                                                                                                                                                                                                                                                                                                     Basin
                                                                                                                                                                                                                                                                                                                                                                                                                              .... ......
                                                                                                                   ..............









                                                                                                                                                                                                                                                                                                                                                                         7,
                                                                                             . . . . . . . . . . . . . . . . . .
                                                                                                                                 . . . . . . . . . . . . . . . . . .
                                                                                                                                                                                            . . . . . . . . . .
                                                                                                                                                                                                                                              . . . . . . . . . . .  . . . . . . . . . . . . . . . . . . . . . . . . . . .
                                                                                                                                                                                                             .. . . . . . . . . . . .. . .                                                                                                                             . . . . . . . .            ." . . . . . . . .
                                                                                                     Miles


                                                                                                                                                                                                                                                                                                                                                                                                 ----------
                                                                                      0                  100                    200



                                                            Figure 4-1. Areal extent of the Missouri River, Red River of the North, and upper
                                                            Mississippi River basins.


                                                            The Missouri River flows over 2,460 miles from its beginning at the confluence of the Gallatin,
                                                            Madison, and Jefferson Rivers in Montana to its confluence with the Mississippi River just above
                                                            St. Louis, Missouri. Draining all or parts of 10 states (Montana, Wyoming, Colorado,
                                                            North Dakota, South Dakota, Nebraska, Kansas, Minnesota, Iowa, and Missouri), it has a total
                                                            drainage area of 529,350 square miles, which represents more than 42 percent of the total area
                                                            drained by the Mississippi River system. Table 4-2 lists the major tributaries of the Missouri
                                                            River and their drainage areas. With a total fall of 3,630 feet, the slope of the Missouri River
                                                            is mild (0.2-4.3 feet/mile) with an average of 1.5 feet/mile. Except for the Milk River, every
                                                            major tributary in the upper and middle portions of the basin is a right bank (looking
                                                            downstream) tributary flowing to the east or the northeast. Storms that typically move in an
                                                            easterly direction can potentially cause a large concentration of flows. The Missouri Basin River
                                                            Forecast Center (MBRFC) in Kansas City, Missouri, is responsible for forecasting the Missouri
                                                            River basin.




                                                                                                                                                                                                                                                   4-2








             Table 4-1. Major tributaries of the Mississippi River and their drainage areas.



                                        DRAINAGE                                           DRAINAGE
                                      AREA (SO.NH.)                LR@ffl@                AREA (SQ.NH.)

                Minnesota                    16,920                Rock                         10,850
                Cannon                        1)420                Skunk                         4,325
                Chippewa                      9,480                Des Moines                   14,540
                Zumbro                        1,402                Fox                              502
                Black                         2,390                Wyaconda.                        458
                Root                          1,670                Fabius                        1,570
                Iowa                          41770                Salt                          2,920
                Cedar                         7,870                Illinois                     28,200
                Wisconsin                     11,705               Kaskaskia                     5,840
                Turkey                        1,696                Big Muddy                     2,360
                Maquokata                     1,903                Meremac                       3,980
                Wapsipinicon                  2,563






             Table 4-2. Major Missouri River tributaries %dth drainage areas of 6,000 square miles or
             more.



                                            DRAINAGE                                            DRAINAGE
                TRIBUTARY                 AREA (SO.NH.)            D@UBARY                   AREA (SQ.MI.)

                Jefferson River                     9,277          South Platte River                  24,300
                Milk River                          22,332         Loup River                          15,200
                Powder River                        13,194         Elkhorn River                       6,900
                Yellowstone River                   69,103         Platte River                        85,800
                Little Missouri                                    Republican River                    24,542
                   River                            8,310          Smokey Hill River                   19,261
                Cheyenne River                      24,500         Big Blue River                      9,640
                James River                         21,500         Kansas River                        60,060
                Big Sioux River                     9,810          Grand River                         7,883
                Niobrara River                      12,600         Osage River                         14,500
                North Platte River                  34,900






                                                              4-3









                The Red, upper Mississippi, and Missouri River basins have a number of hydraulic structures
                including reservoirs for flood control, water supply, power generation, and recreation; locks and
                dams for navigation; transmountain diversions; and flood control levees. The upper Mississippi
                River, from St. Anthony Falls in Minneapolis-St. Paul to St. Louis, has a 9-foot minimum depth
                navigational channel. This depth is maintained by a system of 27 locks and dams, which have
                minimal effect on flood control efforts. Of the 14,000 dams in the Missouri River basin, 70
                have a significant affect on streamflow and, consequently, are accounted for by MBRFC in its
                forecast schemes. Major reservoirs operated by the U.S. Army Corps of Engineers (COE) on
                the Missouri River ensure flows sufficient to maintain navigation from its confluence with the
                Mississippi to Sioux City, Iowa. A total of 226 Federal and 1,576 non-Federal flood control
                levees are located throughout the three basins. Because the Red River drainage is so flat,
                diversion structures are necessary to carry water from agricultural land into drainage ditches
                which carry the water to the river.

                The Red, Mississippi, and Missouri River systems encompass several complex hydrologic and
                hydraulic conditions, including some created by The Great Flood of 1993, that challenge river
                forecasters' abilities. Heavy rainfall in concentrated areas may cause flash flooding. On very
                flat rivers (e.g., the Red) small changes in stages may cause overland flow for miles. In a
                system where levees are being overtopped and/or breached throughout, it is very difficult to
                account for the volumes of water (which determine the discharge to downstream points) that are
                in the rivers at any given time. Additionally, backwater conditions along tributaries, changes
                in the river bed from sedimentation, and locally stored water in inactive floodplain areas may
                also cause significant forecasting problems.


                4.3 RIVER FORECASTING OVERVIEW


                The basic steps in forecasting streamflow can be simplified as:

                        1.     Use observations (precipitation, temperature, etc.) to estimate the net amount of
                               water entering the basin from rainfall and/or snowmelt. If precipitation forecasts
                               are available, they may also be used as input. Larger basins are typically broken
                               into smaller subbasins where the assumption of uniformity of the precipitation,
                               temperature, and basin hydrologic characteristics is more likely to be valid.

                       2.      Convert the net input of water (from rainfall or snowmelt) into a volume that
                               enters the stream (runoff), accounting for surface slope, soil characteristics, soil
                               moisture, infiltration, evaporation, etc. The inflow into a stream causes it to rise.
                               A plot of the time variation of the stream level or volume of water flowing past
                               an observation point is called a hydrograph (e.g., Figures 3-1, 3-18, 3-19).

                       3.      Calculate the volume rate of water (discharge) that flows from a point in the
                               stream to points farther downstream. The process of calculating this flow from
                               one point along a stream to another is called routing.

                                                                4-4

























                               NWRFC


                                                                      NCRFC



                            CNRFC
                                                                                          CAR
                                          CBRFC
                                                                                0 FC


                                                                     BRF



                                                               ABRFC


                                                                                   SERFC

                                                             WGRFC

                                                                       LMRF


                                                                                          40



                                      AKRFC






                 FIgure 4-2. Locations of, and areas served by, the 13 NWS River Forecast Centers.


             4.3.1 NATIONAL WEATHER SERVICE RIVER FORECASTING SYSTEM


             The objective of river forecasting is to predict water levels (stages) at specific locations along
             a river by simulating various components of the hydrologic cycle. A river forecasting system
             should include: (1) hydrometeorological data analysis procedures to determine the areal
             distribution of precipitation, temperature and evaporation; (2) hydrologic models to compute the
             amount of runoff; and (3) hydraulic models to account for the movement of water down the
             channel system. For large areas (such as those forecast by the NCRFC and MBRFQ with many
             data collection stations and forecast points, a river forecast system also requires efficient
             procedures for managing large amounts of information, as well as a user interface that allows
             the forecaster to easily select from available options and to adjust the models based on
             observations and hydrologic insight.

             The National Weather Service (NWS) supports, at a national level, an operational river
             forecasting capability known as the NWSRFS. The NWSRFS was released in the mid-1980s
             for implementation by the 13 River Forecast Centers (RFQ shown in Figure 4-2. The
             NWSRFS is now being used completely by seven RFCs for operational forecasting, while the
             other six offices are in varying stages of making the transition from their locally developed


                                                            4-5










               Table 4-3. Selected models available in the NWS River Forecast System.




                                      FUNCTION                             TYPE OF          NWSRFS
                                                                           MODEL          OPERATION

                   Unit Hydrograph                                         Empirical      UNIT-HG


                                                      Runoff Models

                   Sacramento Soil Moisture Accounting                     Conceptual     SAC-SMA
                   Xinanjiang Soil Moisture Accounting                     Conceptual     XIN-SMA
                   Continuous API*                                         Empirical      API-CONT
                   Central Region API Rainfall-Runoff                      Empirical      API-MKC
                   Ohio RFC API Rainfall-Runoff                            Empirical      API-CIN
                   Middle Atlantic RFC API Rainfall-Runoff                 Empirical      API-HAR
                   Colorado RFC API Rainfall-Runoff                        Empirical      API-SLC
                   Baseflow Generation                                     Empirical      BASEFLOW
                   Snow Accumulation and Melt                              Conceptual     SNOW-17


                                                     Routing Models
                   Dynamic Wave Routing                                    Physical       DWOPER
                   Musldngum Routing                                       Empirical      MUSKROUT
                   Tatum Routing                                           Empirical      TATUM
                   Lag and K Routing                                       Empirical      LAG/K
                   Layered Coefficient Routing                             Empirical      LAY/COEF
                   Channel Loss                                            Empirical      CHANLOSS
                   Single Reservoir Simulation                             Empirical      RES-SNGL


                                                  Rating Curves/Tables
                   Stage-Discharge Conversion                              Empirical      STAGE-Q

                           API stands for antecedent precipitation index


                                                            4-6








              systems to NWSRFS. The NCRFC uses NWSRFS for river and flood forecasting and uses local
              procedures to issue spring flood outlooks. The MBRFC uses NWSRFS to generate mean areal
              precipitation and mean areal temperature data sets and uses local procedures for river and flood
              forecasting and generating spring flood outlooks. There are four major components of the
              NWSRFS operational forecast system:

                      I .     Data analysis procedures are used to compute mean areal estimates of
                              precipitation, temperature, and potential evaporation from point observations.

                      2.      Modules (referred to as operations) are used to compute and display runoff, river
                              discharges, and stages. These operations include hydrologic and hydraulic
                              models, data manipulation algorithms, and display procedures.

                      3.      Utility programs and databases are required to manage the large volumes of data
                              used by an RFC. In addition to observed data, information on numerous other
                              parameters must be maintained. This parametric information includes rating
                              curves, unit hydrographs, rainfall-runoff curves, channel routing constants, etc.
                              (See below for discussion of these terms.)

                      4.      An operational forecast program command language is required to allow the
                              forecaster to deflne modeling options, to make adjustments to model state
                              variables (i.e., current state of the river, soil moisture, etc.) and data values, and
                              to recompute forecasts.

              Selected models available in the NWSRFS are shown in Table 4-3. The RFCs decide which
              models are most appropriate to forecast their basins and determine the hydrologic parameters
              needed in the models. The RFC forecast procedures are normally executed once a day in the
              morning, after all available precipitation and stage data have been received. Generally, the
              models simulate hydrologic conditions every 6 hours at synoptic times'. During flooding
              situations, the RFC forecast system is executed at other times during the day as conditions
              change and new data are received.

              4.3.1.1 RUNOFF


              Streamflow is an integral part of the hydrologic cycle and is driven by precipitation. Rain that
              falls can become surface runoff as it travels overland or horizontally through the upper layers
              of soil to the stream channel; it can sink into the soil and enter the channel as ground water
              flow; or it can evaporate either directly or indirectly through plant transpiration. Surface runoff
              is the most significant component for river forecasting. The amount of surface runoff depends
              on soil moisture content, soil type, terrain slope, and vegetation. The two primary methods of


                   1 Synoptic times are 6-hour intervals, starting at 00:00 UTC (Universal Coordinated Time). By convention,
              hydrometeorological observations are simultaneously made around the globe at these times to allow creation of
              "synoptic maps" that provide a "snapshot" of the state of the atmosphere at the observation times.

                                                               4-7









                estimating surface runoff use: (1) conceptual models that simulate the physical processes and
                (2) empirical methods based on time of year, storm duration and intensity, and initial soil
                moisture content.


                Because of the complexity of the physical processes, most current models are "lumped
                parameter" models. These models assume that a single value can adequately characterize the
                quantity within the modeled area. For example, an average precipitation value can be used to
                determine runoff volumes over a small basin. The assumption is that the small spatial and time
                variations do not adversely affect model computations. For this reason, large basins are usually
                divided into smaller subbasins.


                Conversion of rainfall-runoff to the volume rate of water (discharge) that flows into a stream is
                commonly done using "unit hydrograph" theory. A unit hydrograph specifies at a particular
                location the typical time variation of the discharge resulting from 1 inch of runoff averaged over
                a drainage basin. It assumes that the basin characteristics are homogeneous and that runoff is
                uniformly distributed over time.

                Unit hydrographs may be developed on the basis of observations. Because of limited availability
                of data and the need to match storm durations with river forecast model time-steps, a different
                unit hydrograph is needed for each storm duration. The most common unit hydrographs
                developed and used by the NWS are for 6-hour durations. Figure 4-3 shows an example of a
                unit hydrograph. RFCs generally develop a unit hydrograph for each basin (and subbasins, if
                any) in their areas.

                Unit hydrograph theory assumes that the discharges generated by runoff amounts other than
                I inch can be produced by using the ratio of computed runoff to the 1-inch storm. As shown
                in Figure 4-3, a total storm hydrograph results from adding the properly scaled unit hydrograph
                volumes to base flow. Base flow results from rainfall that infiltrates deeply into the soil and
                moves laterally within the ground to the stream channel. Because of the retarding effects of flow
                through the ground, base flow varies slowly and continues long after the rainfall has stopped.
                As shown in Figure 4-3, during heavy rainfall events, base flow is only a small percentage of
                the total flow. However, during dry periods, groundwater-driven base flow sustains river levels.

                While surface characteristics of a basin, such as soil types (affects infiltration rates), slopes
                (controls speed of surface runoff), depressions, etc., generally do not vary from storm to storm,
                soil moisture does. Because soil moisture measurements are not normally available, runoff is
                adjusted based on estimates or model calculations of soil moisture.

                For storms lasting longer than the duration of the standard unit hydrograph (normally 6 hours),
                successive calculations as described above are made. Each 6-hour interval uses precipitation
                from previous intervals to ad ust soil moisture. The total discharge from a long-duration storm
                is the summation of hydrographs resulting from the application of the unit hydrograph theory
                to a series of 6-hour segments that span the total storm duration.



                                                               4-8















                                                                           Base flow  ------

                                                                           Unit Hydrograph
                                                                           Storm Hydrograph  -----


                                                           %













                                                       ...........................
                                                                             -----------------
                               .... ...................



                                                              Time


                    Figure 4-3. An example of a unit hydrograph, a base flow hydrograph, and
                    the resulting storm hydrograph.



             4.3.1.2 RATING CURVES AND TABLES


             While hydrologic modeling is based on flow volumes, most public forecasts are made for river
             levels or stages. The relation between river stage and flow volume is called a rating curve or
             a stage-discharge relation. These stage-discharge relations are critical to forecasting the river
             stages at gaged locations along rivers.

             Rating curves are influenced by inertial effects creating unsteady flow (e.g., backwater, water
             flowing overbank into or out of the main channel, etc.) and by roughness effects (e.g., seasonal
             changes in vegetative growth, bedform changes, scouring, and sedimentation). When inertial
             effects become dominant, the relation between stage and discharge can be quite variable. Water
             within the channel's banks flows faster than overbank flow due to roughness differences.

             Roughness effects generally cause rating curves to shift. For example, a given stage will have
             a larger discharge in early spring when vegetative growth in the channel is minimal than in the
             summer when heavy growth retards discharge. Also, discharges in rivers heavily laden with
             sediment, that are continuously scouring and filling, generally produce lower stages during
             scour.



                                                            4-9















                           X - Observed                                      x


                                                             x x          x
                                                       x            x
                   t
                   0)
                   co                         X X
                                                       Single Value Curve






                                               Discharge..*                  (a)










                                              Discharge.+                  (b)


            Figure 4-4. Exwnples of rating curves: (a) observation points and smooth line representing
            best estimate of rating curve and (b) loop rating curve.


                                                  4-10








             Stage-discharge relations are usually developed from a series of field measurements. To
             measure streamflow, water velocities are measured at a number of locations along a line
             transversing the river width (cross-section) in the stream using a current meter. The
             discharge is computed by multiplying segments of the cross-sectional area of the stream
             channel by the segment average water velocity. A series of measurements are made at many
             different stages. The measurements are plotted and a smooth line, drawn through the
             observations, is considered the best estimate of the rating curve. When this information is
             presented in tabular form, it is called a "rating table." An example of a rating curve, drawn
             through a typical series of observations, is shown in Figure 4-4(a).

             The official rating curve at a gaged location is a single-valued curve which implies a one-to-
             one relation between stage and discharge. Unfortunately, the discharge associated with a
             given stage may differ depending on whether the river is rising or falling. For a given stage,
             the discharge will generally be greater for the rising stage (when the water surface slope is
             greater than the channel slope) than for the falling stage (when the reverse is true). This
             effect is particularly pronounced on very mild sloping rivers. Under these conditions,
             modest changes in stage or current can lead to dramatic differences in discharge. This gives
             rise to a "looped" rating curve as shown in Figure 4-4(b). The middle curve is intended to
             represent the single-valued "official" rating curve, while the upper and lower lines show the
             actual discharge as the river rises and falls. Another reason for lower discharge as the river
             falls is that the flood crest fills the channel and impedes the flow associated with the falling
             stages.

             The U.S. Geological Survey (USGS) has responsibility for measuring streamflow throughout
             the United States. The USGS makes discharge measurements and develops most official
             rating curves used by the NWS. When significant rises occur, the USGS often makes
             additional discharge measurements and provides this information to the NWS, the COE, and
             other cooperators. These measurements are used to update rating curves.

             4.3.1.3 RIVER ROUTING


             As a flood wave travels down a stream that has no intervening tributary flow, the peak flow
             may be delayed and attenuated. Figure 4-5 schematically shows these effects at three
             locations along the stream (Location I is upstream, Location 3 is downstream). Note that,
             in this idealized case, the total volume in each hydrograph is constant; as the peak falls, the
             hydrograph broadens.

             While computer models have been developed to simulate the volume and momentum of water
             as it moves down a stream, the significant amount of information needed to implement such
             models currently limits their operational use in most cases. Instead, empirical information
             is used to develop procedures that describe flow from one point along a stream to another.
             This process is referred to as "storage routing" and relates inflow, outflow, and storage by
             a "storage function." The determination of the routing constants used in the storage function
             is based on observations from a range of flow conditions.


                                                           4-11















                                                                                Location 1


                                                                                Location 2   ------

                                                                                Location 3   -----
                       t
                       4D

                       US                                               ---------













                                                                Time-o.


                   Figure 4-5. Schematic showing reduction inflood crest asflood wave moves
                   downstream.



               4.3.1.4 RESERVOIR OPERATIONS


               When dams and reservoirs exist along a stream, the forecast procedures cannot be applied as
               described above. Typically, forecasts are made at inflow points for major reservoirs. This
               information can be used to manage flow through the reservoir.            To forecast at points
               downstream, reservoir releases must be known. The needed information exchange occurs
               between the NWS and operators of many major reservoirs.


               4.4 CURRENT FORECAST METHODOLOGY AT THE NORTH CENTRAL
                       AND XHSSOURI BASIN RIVER FORECAST CENTERS


               The NCRFC uses the NWSRFS as its operational forecast system. The MBRFC uses the
               NWSRFS for data analysis and runoff calculations and uses a locally developed forecast system
               for channel routing, reservoir control, and stage-discharge relations. For runoff, both RFCs use
               an API model to compute storm runoff using precipitation amounts, an index to antecedent
               moisture conditions, time of the year, and rainfall duration (API-MKC, see Table 4-3). Mean
               areal precipitation is computed and runoff calculated on a 6-hourly basis. The storm runoff is


                                                             4-12









             converted to discharge using a unit hydrograph. Baseflow amounts are added to the storm runoff
             hydrograph to get total discharge.

             Although the RFCs use different river modeling systems, both rely primarily on the same
             procedures to route the discharges and obtain river stages. Both RFCs rely on the Tatum routing
             procedure that is based on storage-routing methodology. River stage is obtained by using the
             routed discharge and a stage-discharge relation (rating curve), which is generated using observed
             data. While NCRFC uses a log-log interpolation/extrapolation procedure to manipulate the
             rating curve (STAGE-Q, Table 4-3), MBRFC uses a linear technique to handle rating curve
             extensions. Reservoir operations are handled by NCRFC using a procedure that has several
             schemes and utilities to simulate reservoir conditions (RES-SNGL, Table 4-3). MBRFC uses
             a technique developed by Goodrich for reservoir operations.

             Both RFCs can make various types of adjustments to simulated variables. Runoff volume errors
             are typically accounted for by changing the volume computed by the runoff model before the
             unit hydrograph computations. Discrepancies between observed and simulated discharge
             hydrographs may be handled by blending the two hydrographs together. Rating curves are
             constantly being adjusted during flood to accommodate the changing hydraulic conditions in the
             river. Currently, these adjustments are accomplished manually.


             4.5 WEATHER SERVICE OFFICES WITH HYDROLOGIC
                    RESPONSIBILITIES


             While hydrologic guidance is provided by the RFCs, hydrologic forecasts based on this
             information are issued to the public by selected NWS offices (generally WSFOs) having
             hydrologic service area (HSA) responsibilities. See Figure 4-6 for HSA areas of responsibility.

             HSA offices currently have very limited forecasting tools. Most RFCs provide their HSA
             offices with headwater tables. These tables provide estimates of the flood peak for any specified
             amount of precipitation and an index that characterizes soil moisture conditions. These tables
             can be used on selected basins to generate preliminary forecast crests on fast-responding streams
             before the RFC hydrologic forecast is provided to the HSA offices. Although some HSA offices
             have simple crest-stage forecast techniques, there are no sophisticated hydrologic procedures for
             routing flow or for handling complex systems.

             HSA offices provide the RFCs with information used in the river forecast system. This includes
             observations of precipitation and river levels. HSA offices also provide other key hydrologic
             information including gage locations, historical flood (and low-water) records, impacts of floods
             at various levels, etc. Much of this information comes from other agencies and is summarized
             on a standard NWS form E-19. The HSA office is responsible for keeping the E-19s current.
             Much of the E-19 information must be updated as a result of the altered conditions produced by
             The Great Flood of 1993.



                                                           4-13


















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                    Figure 4-6. Locations of, and areas served by, the NWS offlces with Hydrologic Service
                    Area responsibilities.






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                                                                                   4-14











            4.6 FORECASTING CHALLENGES DURING THE GREAT FLOOD OF M


            The Great Flood of 1993 presented many challenges to NWS river forecasters. The following
            sections highlight limitations in the current data and procedures used by the NWS.



            4.6.1 DATA INPUT

            Precipitation is one of the most important input quantities to any hydrologic forecast system.
            To date, precipitation observations are obtained from point sources or rain gages. The area of
            a representative runoff zone (i.e., subbasin) forecast by NCRFC and MBRFC is 300-500 square
            miles. Typically, an average of 3-5 rain gages are used to represent the amount of precipitation
            over that area. Because of the comparatively few rain gages, heavy precipitation areas can be
            missed (especially in convective thunderstorm patterns that occurred during The Great Flood
            of 1993).

            Another important consideration is the lag between times when precipitation occurs and when
            it is available to the forecast system. Forecast preparation at the NCRFC and MBRFC is closely
            tied to precipitation measurements made by the cooperative network at 12:00 UTC every
            morning (7 a.m. CDT). These measurements represent a 24-hour period between 12:00 UTC
            the previous day and 12:00 UTC for the current morning. It is at this time when forecast
            models have the maximum amount of precipitation data available. Forecast models can be
            executed at other times during the 24-hour period, usually on synoptic 6-hour periods; but
            precipitation observations for these periods are far fewer.          Taking observations in the
            cooperative network is a manual process, requiring a person to take and transmit an observation.
            Remote Observation System Automation (ROSA--see Section 5.2. 1) has helped in transmitting
            these data and in reducing manual intervention but not in improving the frequency at which
            observations are taken. Observations made more than once a day (12:00 UTC) currently are
            very limited over much of the area affected by The Great Flood of 1993. This hinders the
            forecasters' ability to use the forecast system to prepare updated forecasts.

            The NCRFC and MBRFC can also receive precipitation data from automated data collection
            platform (DCP) sites (see Section 5.2.2. 1). These automated sites are equipped with "tipping
            bucket" rain gages and transmit precipitation data often accompanied by river stage data. Both
            RFCs indicated that rainfall data received from tipping buckets were suspect and difficult to use.

            River stage observations are also very important input to the forecast system. Many river stage
            locations are now automated (e.g., DCPs) and provide more timely data. Some DCPs, however,
            are still not programmed to transmit randomly, or on significant events (see Section 5.2.2. 1).






                                                           4-15












                     4.6.2 RATING CURVES

                     Changes in the river bed caused by sedimentation and scouring, backwater conditions' along
                     tributaries, and locally stored water in inactive floodplain areas may result in the continuous shifting
                     of the rating curves.

                     Rating curves play an important part in the forecast methodology used by NCRFC and MBRFC.
                     The NWS river forecast system routes volumes of water to locations downstream. These discharges
                     are converted to river stages using rating curves. RFC forecasters can also use stage measurements
                     to estimate discharge as an aid in evaluating volumes predicted by the models. The official rating
                     curve at a gaged location (based on USGS measurements) is a single-valued function that describes
                     a one-to-one relationship between stages and discharges. Unfortunately, in many cases, the
                     relationship between stages and discharges is not one-to-one. Generally, the relationship on very
                     mild sloping rivers shows a looping effect where, for a given flow, the stage on the rising limb of
                     the hydrograph may be different from the stage on the recession side (see Figure 4-4(b)).

                     Any extension of a rating beyond measured flow values can result in inaccurate stage-discharge
                     relationships. The NCRFC and MBRFC use log-log and linear extrapolations, respectively, to
                     extend rating curves. Neither of these techniques take into account the channel conditions (e.g,
                     cross-sectional geometry, roughness, etc.) and, if used without adjustment, would probably
                     overestimate the stage. A more appropriate way to extend the rating curves would be to apply a
                     hydraulic extension procedure. Both a hydraulic extension and a loop rating option are being
                     developed for the procedure that relates stage to discharge (STAGE-Q) in NWSRFS.

                     During The Great Flood of 1993, rating curves underwent continuous, manual adjustments that were
                     primarily based on special or emergency stage-discharge measurements and the hydrologists'
                     experience and intuition. At times the hydrologists felt as though they were forecasting rating curves
			   instead of stages.


				FINDING 4.2: The number of sites where		RECOMMENDATION 4.2: Loop rating
				backwater or loops in ratings affected		curves are an indication that a dynamic
				forecasts was unprecedented.				wave routing technique is required. Each
												RFC and the Office of Hydrology should
												investigate the input data, model cali-
												bration, and simulation results associated
												with implemention of a dynamic wave
												model in any affected area.	
                     
                               
                           2 Backwater effects result from a downstream build up that prevents normal flow of water. A common
                     situation leading to the backwater phenomena occurs when a main stem stream experiences high stages. In the
                     vicinity of tributaries that flow into the main channel, the water level in the main channel can be higher than stages
                     of the tributaries. This results in flow out of the main channel into the tributaries. The flow is in the opposite
                     direction to normal flow on the tributaries, resulting in a backwater effect.

                                                                                     4-16
 

			FINDING 4.3: In many of the flooded				RECOMMENDATION 4.3: In The
			areas on the Missouri and Mississippi			Great FLood of 1993, levee effects and
			Rivers, the stages exceeded those of prior		unknow ratings are probably the dominant
			records while the corresponding volumes of 		causes of discrepancies between the river
			flow often did not. Assessment of the 			stages and volumes of flow. The 
			causes of this factor are important to the		Hydrological Research Laboratory should use
			objective of applying the best river hy-			the dynamic wave model to determine the
			draulics in future river modeling and fore-		causes for these discrepancies. Addition-
			casting.								ally, new ratings must be established for
												many forecast points.



                 4.6.3 FLOOD ROUTING

                 The Great Flood of 1993 encompassed many hydraulic conditions that made the operational
                 routing procedure inadequate. Backwater effects were a serious problem throughout the flooded
                 area. These effects were due to a multitude of reasons including channel constrictions (e.g.,
                 since the levees held around the city of St. Louis along the Mississippi River, the water
                 converged there and caused backwater effects upstream); inflows from large tributaries (e.g.,
                 the confluence of the Missouri and Mississippi Rivers); and off-channel storage of water trapped
                 behind levees. Levee overtopping and failures (discussed in Section 4.6.5) made it very difficult
                 to account for the volume of water (discharge) in the system. Sedimentation (which causes
                 changes in the channel geometry) in the Missouri River also made forecasting of river stages
                 difficult. Storage routing models are not able to handle situations where flows were subject to
                 such complex hydraulic conditions.

                 4.6.4 RESERVOIR EFFECTS


                 Numerous, multipurpose reservoirs maintained by the COE and several Bureau of Reclamation
                 reservoirs were highly effective in reducing stages during The Great Flood of 1993. The
                 magnitude of the reductions depended on many factors including location of storms and
                 reservoirs, available reservoir storage, type of reservoir, and intervening local area between
                 damage center and reservoir. Although the actual stage reductions have not been finalized, the
                 volume of water stored in many midwestem reservoirs during The Great Flood of 1993 set
                 records.


                 Flood control operations at projects in the Missouri and Mississippi River basins helped regulate
                 the contributions by those basins to the Mississippi River at St. Louis and downstream.
                 Missouri River main stem and tributary projects also significantly reduced stages along. the
                 Missouri River itself. Other projects closer to damage centers provided reductions at key levees
                 and other critical locations. With approved deviations from standard operating procedures, many
                 projects were regulated to further reduce downstream stages.



                                                                               4-17
 








                Detailed analyses of the effectiveness of these flood control operations is beyond the scope of
                this survey report and generally falls to the agency directly responsible for facility operations.
                For example, the COE plans to publish a post-flood report in approximately 4-6 months detailing
                project operations, downstream stage reductions, and resulting beneffis of COE projects. The
                effectiveness of the NWS forecast and warning service and the associated coordination between
                the NWS and water control facility operators is, however, an important part of this survey.

                The COE uses NWS river forecasts to plan the regulation of their reservoirs. In some instances,
                contingency forecasts were made by the NWS for the COE based on quantitative precipitation
                forecasts (QPF) (see Sections 5.2.4.2 and Appendix B). At present, NWS forecasts at both the
                NCRFC and MBRFC do not normally use QPF directly to account for future rainfall. Upon
                request from the COE, forecasts were run at the MBRFC with bands of 1 or 2 inches of
                potential rainfall so that the COE could look at alternative reservoir operations.



                4.6.5 LEVEE EFFECTS


                The Great Flood of 1993 was influenced (and to some extent, caused) by more than 1,500 levees
                throughout the Mississippi and Missouri River basins. While the effects of specific levees and
                their failures during the flood can be argued, general effects can be briefly discussed.

                As water leaves the channel and flows into the overbank (floodplain) areas on the rising limb
                of the hydrograph, levees prohibit floodplain storage. This concentrates greater volume in the
                higher velocity channel segment and produces a higher peak discharge downstream since the
                flow cannot be stored in the overbank area protected by the levees. At the same time, however,
                levees restrict the amount of flow passing a point on the river, thus tending to increase the
                velocity and deepen the channel.

                Again, depending on location and configuration, a levee breach could occur and make significant
                storage suddenly available. The breached levee could "regulate" flow by rapidly removing water
                from the channel and reducing downstream discharges. The magnitude of this effect obviously
                depends on many factors. Some of these include the levee elevations and breach widths, the
                height of the water level (head) over the breach, and the storage volume available behind the
                levee.


                All of these effects occurred, to some degree, along the lower Missouri and upper Mississippi
                Rivers during this record event. Other effects occurred, including multiple breaches of levees,
                that dramatically decreased the flow in the river by forming high-flow relief channels in the
                floodplain behind the levees. This significantly reduced both upstream and downstream flood
                heights.







                                                              4-18










                 When levee breaches occurred, RFC forecasters generally assumed that water flowing into areas
                 behind the levees would only temporarily reduce the discharge on the rising limb of the flood
                 hydrograph. As the area behind the levees filled, the effect of the breaches on river stages
                 decreased. This was followed by water returning to the channel once the flood peak had passed.

                 To better define the specific effects of levees and their breaches during this flood, it is necessary
                 to use dynamic routing models that account for unsteady flow effects, levee breaching, flow
                 conveyance on the floodplains behind breached levees, and floodplain storage. Such models use
                 the continuity and momentum equations and account for both the conveying (carrying) capacity
                 and the available storage of the floodplain (see Section 4.7.2). Two major, undefinable factors
                 during this flood were: (1) the location and size of levee breaches, particularly before the failure
                 occurred, and (2) the ability to quantify the available storage behind the levees and the amount
                 of return flow over time.

			FINDING 4.4:  Levee effects on			RECOMMENDATIONS 4.4: The use of
			overbank storage and downstream fore-		airborne photographic reconnaissance to
			casts were difficult to analyze. The size		pinpoint levee failures should be an
			and type of failures were highly variable.	option readily available to RFCs. The
											Hydrologic Research Laboratory and the	
											RFCs should investigate more effective
											ways to model levees and levee failures.

			FINDING 4.5: St. Louis District COE			RECOMMENDATION 4.5: The NWS
			has profiles of Federal levees with top-of-	should coordinate with the COE to obtain
			levee elevations for non-Federal levees.		levee information for use in forecast
			Some levee profiles may change in the		procedres, especially when imple-
			aftermath of the extensive flooding.		affected by the flood.

		



			4.6.6 USER INTERACTION WITH FORECAST SYSTEM
                        
                 Currently, river forecasts are typically made on a mainframe computer at the NOAA Central
                 Computer Facility (NCCF) in Suitland, Maryland. Input information is prepared at each RFC
                 and submitted via phone lines for batch processing at the NCCF. Once the batch job is
                 executed, model output is returned via phone line to the RFCS.
                                                                                               







                                                                                 4-19
 















                       ST LOUIS   NO            - MISSISSIPPI       R            NOV 1993 CST           EADM7                    ENGLISH UNITS

                             0 =  EADM7       OIN  (CFS   )         F= FLOW STAGE                                 NWS-ID =         EADM7
                             * =  EADM7       QINE (CFS   )         U= RATING UPPER LIMIT                         DATUM =          379.94
                             * =  EADM7       SQIN (CFS   )         N= MAX OF RECORD
                             A =  ALNRTD      SOIN (CFS   )
                             M =  MOCONRTD    SQIN (CFS   )

                             FLOOD STAGE      =    30.0             FLOOD FLOW      = 497599.9              MAX OF RECORD STAGE = 43.2
                             WARNING STAGE = -999.0                 BANKFULL STAGE  =    -9999.9                             FLOW z1300000.0
                             PLOT STAGE       =    30.0             FCST CRITERIA   = DANA       SOOP                        DATE = 4-28-1973


                       COMMENTS: RATING INPUT ON 7-25-93... PN


                                        STAGE-7.0           2.7        12.7         19.5       25.0         30.1
                       DA HR SSTG EADM7G EADM7.000 100000.0 200000.01               300000.0 400000.0       500000.0    ADJQ(*)      SINQ(+) RO ROO
                       BF( 868.)
                       11 18     13.9   13.67     0.00    1   MIA            +*          I           I      F1  215367.    209377.    0.00       0.   1.
                       12  6     13.8   13.39    13.85    1   MIA            +0          1           1      F1  215353.    207691.    0.00       0.   1.
                       12 18     13.8   13.78     0.00    1   MIA            I*          I           I      F1  214239.    210671.    0.00       0.   1.
                       13 6      13.7   13.72    13.72    1   MIA            10          1           1      F1  213660.    214306.    0.00       0.   1.
                       13 18     13.9   13.83     0.00    1         MA       I*          I           I      F1  216012.    215126.    0.00       0.   1.
                       14  6     15.4   15.16    15."     1         14A      1 0         1           1      F1  235860.    233236.    0.30   2850.    1.
                       14 18     18.7   18.59    18.75    1         1A       I      + 0  1           1      F1  288255.    263003.    0.28   5960.    1.
                       15  6     20.8   20.81    20.85    1         1AN      I       +   10          1      F1  324134.    287640.    0.00   5330.    1.
                       15 18     22.8   22.84    22.84    1         1AN      I           +   0       1      F1  359921.    304312.    0.00   4500.    1.
                       16  6     23.2   23.27    23.25    1         1A N     I           1+    0     1      F1  367353.    318102.    0.00   4190.    1.
                       16 18     22.8   22.62     0.00    1         1A  M    I           I +         I      F1  358633.    324443.    0.01   3415.    1.
                       17 6      22.4   22.38    22.39    1         1A   M   I           I + 0       1      F1  351786.    333151.    0.10   3510.    1.
                       17 18     23.8   23.39     0.00    1         1A       M           11  +       I      F1  376510.    346430.    0.01   2850.    1.
                       18  6     25.3   25.35    25.35    1-----    I --- A----- IN --------I---------0------ F1 405780.   3630".     0.00   1800.    1.
                       18 18     26.3    0.00     0.00    1         1A       I M         I       + I  *     F1  424007.    381804.    0.00   1220.    1.
                       19  6     27.0    0.00     0.00    1         1A       I N         1        +1 *      F1  437214.    395546.    0.00    780.    1.
                       19 18     27.1    0.00     0.00    1         1A       I   M       1        +1 *      F1  437955.    396821.    0.00    600.    1.
                       20  6     26.2    0.00     0.00    1         1A       I M         I       + I  *     F1  422093.    381493.    0.00    420.    1.
                       20 18     24.7    0.00     0.00    1         1A       IN          I   +     *1       F1  394645.    354579.    0.00    245.    1.
                       21  6     23.0    0.00     0.00    1         1A     NI            I+          I      F1  363597.    324065.    0.00    120.    1.
                       21 18     21.5    0.00     0.00    1         1A  M    1        +1             1      F1  335538.    296541.    0.00       10.  1.
                       22  6     20.2    0.00     0.00    1         IAM      I      +    I*          I      F1  311878.    273415.    0.00       0.   1.
                       22 18     19.0    0.00     0.00    1         JA N     I   +    *1             1      F1  292420.    254491.    0.00       0.   1.
                       23  6     18.1    0.00     0.00    1         IAN      I +    *    I           I      F1  276974.    239580.    0.00       0.   1.
                       23 18     17.4    0.00     0.00    1         IA       I+     *    I           I      F1  265668.    228808.    0.00       0.   1.
                       24  6     16.9    0.00     0.00    1         14A      I+  *       I           I      F1  257872.    221546.    0.00       0.   1.
                       24 18     16.6    0.00     0.00    1         14A      J+  *       I           I      F1  252457.    216665.    0.00       0.   1.
                       25  6     16.4    0.00     0.00    1   MIA            I+  *       I           I      F1  248801.    213543.    0.00       0.   1.
                       25 18     16.2    0.00     0.00    1   MIA            I+  *       I           I      F1  246384.    211661.    0.00       0.   1.
                     1 26  6     16.1    0.00     0.00    1   MIA            I+  *       I           I      F1  244636.    210447.    0.00       0.   1.


                     Irigure 4-7.       Example of current NWSRFS batch output available at RFCs.



                     A forecaster must examine forecast output on large amounts of printer paper or, in the case in
                     the NCRFC, on a monitor (CRT). An example of the type of output provided for a single
                     location is shown in Figure 4-7. This output format typically does not show enough detail or
                     other information that would be useful to the forecaster. The forecaster may have to flip line-
                     printer output (or CRT screen images) "back-and-forth" to examine upstream basins that may
                     affect the downstream forecasts.


                     If the forecaster determines that data-input or model variables need to be altered, it can be a
                     cumbersome and time-consuming process to resubmit the job to the NCCF, wait for the results,
                     and work through a second pile of line-printer output. Additionally, the current mainframe,


                                                                                    4-20








                 batch-oriented technology supported by the NCCF and used to make operational hydrologic
                 forecasts at the MBRFC and the NCRFC does not facilitate real-time interaction between
                 forecasters. The ability of forecasters to review visually the graphic, hydrometeorologic data
                 sets between RFCs would have dramatically facilitated inter-RFC communications.

			FINDING 4.6: Coordination between			RECOMMENDATION 4.6: The NWS
			the MBRFC and NCRFC for the				should aggressively pursue installation of
			Missouri River forecast at Hermann,			modernized facilities at RFC (see
			dinate over the telephone were somewhat		required to support the NWSRFS, the
			successful, but muchof the information		Interactive Forecast System, and inter-
			exchange was hampered by technoogical		RFC communications.
			limitations. Limitations in the current
			RFC technology do not allow the
			Herman forecaster at the MBRFC and
			the St. Louis forecaster at the NCRFC
			simultaneously to view all of the graphic
			and hydrologic information (including
			WSR-88D, hydrograph, satellite, and
			derived data sets) used by the other fore-
			caster as input to his/her forecast
			procedures.





                                                                
                 4.7 MODERNERNIZED RFC/WSF0 HYDROLOGIC FORECAST METHODOLOGY


                 The forecast methodology in the modernized NWS at both the RFCs and WSFOS will change
                 dramatically (see Chapter 2). Changes will occur in all functions of the River Forecast System
                 shown in Figure 2-1.

                 4.7.1 INPUT


                 One of the most significant changes will be in the way precipitation observations are processed
                 and used in the forecast system. Point precipitation observations will be merged and processed
                 with precipitation estimates from multiple Weather Surveillance Radar 88 Doppler (WSR-88D)
                 radars and information received from satellite observations. The result will be frequently
                 updated, multisensor, high-resolution precipitation estimates. It is anticipated that RFCs will
                 have these high resolution data sets for their entire areas of responsibility. The availability and
                 use of these data sets will change the way hydrologists interact with and use hydrologic forecast
                 models. Many of the problems associated with having only "point-source" precipitation data will
                 be reduced or eliminated. Forecasters will change their "mind-set" from executing forecast


                                                                                 4-21
 







                    systems based on 12:00 UTC, or at 6-hourly intervals, to running interactively the model in near
                    real-time as estimates of precipitation fields change hourly or even more frequently. RFCs will
                    also have access to gridded QPF estimates for use in their forecast systems.

                    4.7.2 MODELING


                    After modernization and associated restructuring (MAR) of the NWS is complete, RFC
                    Advanced Weather Interactive Processing Systems (AWIEPS) will have sufficient computing
                    power to run NWSRFS locally. RFCs will be able to run NWSRFS with time steps smaller than
                    the 6-hour intervals currently used. This will allow effective integration of WSR-88D rainfall
                    estimates. With MAR, NWSRFS will run in an interactive mode, allowing RFC hydrologists
                    to easily change input to the hydrologic models and make river and flood forecasts in a more
                    timely manner.

                    High-resolution precipitation data will allow the hydrologist to reexamine how models are
                    implemented. Rainfall/runoff models and runoff distribution models (e.g., unit hydrographs)
                    will eventually change from "lumped parameter" models to distributed parameter models based
                    on gridded data. This will be a gradual evolution, nevertheless feasible due to the eventual
                    availability of gridded precipitation estimates.

                    A major challenge along the way to implementing distributed, physically based
                    hydrologic/hydraulic models that take maximum advantage of the new observation systems (e.g.,
                    WSR-88D radars) is the massive amount of time and effort needed to assemble the information
                    required to calibrate these models. The complex spatial variations across the soil surface and
                    within the soil zone are integral to the solution of the hydrologic modeling problem. It is
                    imperative that resources be found to accomplish the transition from statistical/empirical
                    modeling to modeling the relevant physical processes.                        Otherwise, the quantum leap in
                    observation systems, communications links, and computer power provided by MAR will never
                    be fully realized by the NWS hydrology program.

                    The Dynamic Wave OPERational (DWOPER) model is a physically based, distributed,
                    hydraulic routing model that simulates flow along a river using equations describing mass
                    continuity and momentum of the water for unsteady flow. It allows the flow rate, velocity, and
                    water level to be computed as functions of time and distance along the river, rather than time
                    alone as in the hydrologic method. Calibration' of the model requires a large amount of



                         3  Almost all models, whether empirical or physically based, are not able to account fiffly for all aspects of the
                    phenomena being modeled. This comes about either because we do not completely understand all the relevant physical
                    processes or, if known, adequate mathematical representation cannot be found. In addition, the mathematical represen-
                    tation of the processes may be so complex that current computational capabilities may not be adequate to make the needed
                    calculations. Finally, data needed to adequately define the darting conditions to be modeled are often not available.
                    Because of these problems, most models can only approximate the phenomena being modeled. The process of applying
                    a model to real data and adjusting the difference between the prediction and actual observations by modifying model
                    parameters is called calibration. Depending on the sophistication of the model, calibration can be a difficult process.

                                                                             4-22










                  historical data, including stages, discharges, and cross-sectional geometry. Roughness
                  coefficients are Obtained in the calibration process. Additional capabilities that are unique to the
                  dynamic wave method include: routing flows through hydraulic structures, such as bridges and
                  dams (including breaches); routing water over floodplains, levee overtopping, and failure
                  (including storage or flow of water behind levees); backwater effects due to channel
                  constrictions, dams, bridges, tributary inflow, mildly sloping river beds, and tides; off-channel
                  storage of water due to ponding; and flow diversions. Implementation of the DWOPER model
                  on portions of the river systems affected by The Great Flood of 1993 would enhance NWS
                  forecasting capabilities.

                  Since the DWOPER model in NWSRFS computes water levels and discharges simultaneously
                  at every location along the rivers in the system for each time step, the rating curves generated
                  include all of the hydraulic effects that are incorporated in the model. Although DWOPER is
                  capable of simulating rating curves beyond the period of record and at ungaged locations, the
                  forecaster must exercise judgment when using the results.

                  The DWOPER model has levee capabilities; however, it is not currently designed to forecast
                  levee failures in real-time or on rivers with levee systems as extensive as those on the
                  Mississippi and Missouri Rivers. The levee option in DWOPER is being enhanced to improve
                  its forecast capabilities. These enhancements include storage routing in the floodplain once a
                  levee has been overtopped or failed and adding run-time modifications to allow the breaching
                  characteristics to be changed in real-time.

                  The accurate calibration of the NWSRFS hydrologic/hydraulic models, including DWOPER, is
                  critical to their effective use in hydrologic forecasting. Many of the procedures use spatial data
                  sets for calibration and implementation. The advanced techniques and procedures provided by
                  Geographic Information Systems (GIS) make available valuable tools that can be used in the
                  hydrologic model calibration and implementation process.

			FINDING 4.7:	Portions of the Mississippi and Missouri River basins
						have many complex hydrologic and
						hydraulic elements that require appli-
						cation of advanced modeling approaches
						to handle such effects as backwater at
						river junctures, overbank flows, levee
						failures, and changing ratings.


		RECOMMENDATION 4.7:	The RFC's
						and the Office of Hydrology should
						accelerate the implementation of the 
						dynamic wave routing model on those
						river reaches where its capabilities are
						required.







                        
                                                                                  4-23
 














                                                                    ..............................................................................................            ........ .....................    ....................................    I.....................................................
                                                                                                                                                                                                     C-.OT
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                                                                   94.                                                                                                  UP'Tal'".                   plot







                                                                   Ica





                                                        C

                                                                   156








                                                                                                                      77



                                                                                          r7--'
                                                                                          @140to* *de                               cwozsom
                                                                                                                                                                   rk


                                                    U
                                                        ndo I
                                                        - - me series chan



                                             Figure 14-8. &=Ple of modernized forecast system output that 'K411 become available at
                                             RFCs in the future.
                                                                                                                                                                                                                                           Vie"
















                                                                                                                                                                               4-24













             4.7.3 HUMAN INTERACTION W][TH THE FIORECAST SYSTEM

             The way a forecaster interacts with the forecast system win also be changed dramatically with
             MAR. Forecasters will be able to interact easily and quickly with the forecast system. The
             forecast system will run on local workstations using a local database management system to
             handle observations and parametric data. Forecasters will interact with the system using
             interactive "point-and-click" technology in a windowed environment. If changes are needed in
             data input or adjustments needed to model variables, they can be made easily with an on-line,
             interactive forecast system. During rapidly changing hydrometeorological events (e.g., heavy
             precipitation events, dam breaks, or levee failures), forecasters will be able to interact quickly
             with the forecast system and to produce updated forecasts. Output will be graphical and provide
             much greater detail and more information than is currently available, as shown in Figure 4-8
             (compare with Figure 4-7). A pictorial view of modernized RFC hydrometeorological
             operations is shown in Figure 2-6.

             Another major change will occur at the Weather Forecast Office (WFO). These offices will
             have on-site, local processing enabling them to produce and update forecasts for most headwaters
             in their areas. Hydrologists and meteorologists at the WFO will be able to interact with the
             local hydrologic models using point-and-click technology. They will be able easily to view and
             to use the latest forecasts received from the RFCs and to disseminate these forecasts to their

             users.


             In summary, the hydrologic forecast methodology will change in many ways in the modernized
             RFC and WFO. High-resolution precipitation data, the use of QPF, the change to distributed
             hydrologic/hydraulic models, and the use of an interactive forecast system will greatly improve
             the way that hydrologic forecasts are made.          Forecasters will have much more spatial
             information, e.g., inundated floodplain areas along rivers, rather than a single water elevation
             that currently represents the flooding situation along many miles of the river. In addition, the
             forecaster will be able to convey far more information to the end-user. Forecasts with explicit
             probabilities, or confidence bands, will convey to the end-user the confidence, or level of
             certainty, that the forecaster has in any specific forecast. In this way, the modernized
             hydrologic forecast methodology will provide not only the forecaster with a mechanism to impart
             more hydrologic forecast information to the end-user but also will provide more information to
             the end-user to construct a risk analysis for alternative hydrologic scenarios.










                                                            4-25











                     FINDING 4.9:: Current limitations in            RECOMMMATION 4.9: The RFCs
                     operational implementation of                   should move as quickly as possible to
                     hydrologic/hydraulic models, computer           implement advanced hydrologic/hydraulic
                     hardware, and software contributed to the       models and planned, modernized methods
                     inability of the RFCs to incorporate QPF        to objectively and routinely incorporate
                     amounts into river forecasts on an              QPFs.     Since these planned methods
                     objective, routine basis.                       require AWIPS-type technology, the
                                                                     RFCs should also investigate ways in
                                                                     which QPFs may be objectively incor-
                                                                     porated into the river forecasts in the
                                                                     near term (see Finding 2. 10 above)
                                                                     without damaging the integrity of the
                                                                     forecast (e.g., issuing a banded forecast
                                                                     based on potential rainfall).

                     FINDING 4,10: The forecasters and               RECONUVIENDATION 4,10: As soon
                     end-users expressed frustration with the        as possible, the NWS should: (1) install
                     limited amount of information contained         AWIPS and AWIPS-type equipment at
                     in the river forecasts. Sufficient infor-       the RFCs (see Recommendafion 4.6,
                     mation is not provided to do a proper risk      5.15, and 5.16) and (2) implement the
                     analysis.     Forecasters compute total         Water Resources Forecasting System
                     hydrographs and: have some feel for the         (known as WARFS) to provide the
                     potential effects - of various hydrologic       required hydrologic forecast capabilities
                     contingencies, such as levee failures and       (see Recommendation 2.9).
                     rating shifts. There is currently no way
                     routinely to convey this additional infor-
                     mation to the !sophisticated end-users
                     capable of benefiting from the added
                     information.






















                                                                 4-26










                                                                CHAPTER 5


                  DATA ACQUISITION, TELECOMMUNICATIONS, FACILITIES,
                                                       AND COMPUTER SYSTEMS





                5.1 INTRODUCTION

                This chapter describes the data acquisition systems used by the National Weather Service (NWS)
                and their performance throughout the flooded area. It also outlines the status of the facilities,
                telecommunications networks, and computer systems used by NWS offices.

                Maintaining reliable precipitation and river stage data was a major problem affecting forecast
                operations in the flooded area. NWS offices unanimously expressed the desire to increase the
                number of stream and precipitation gages in their areas. There has been a continuing decline
                in both the number of these gages and the resources available to maintain them. Although the
                offices often had access to data from non-NWS acquisition systems, the data were often in
                different formats requiring manual manipulation of the data. The posting, data management, and
                quality control of hydrometeorological data, in general, was slow, laborious, nonsystematic, and
                incomplete.

                The magnitude of the flood demonstrated the dependence of NWS River Forecast Centers (RFC)
                on a number of electronics systems. Many of these systems are based on obsolete computer and
                communication architectures and required considerable support and maintenance to keep them
                operational.

                Section 5.2 describes the primary data acquisition systems used by NWS offices in the flooded
                area and their performance during the flood event. Sections 5.3 and 5.4, respectively, review
                the status of telecommunications services and facilities used by the NWS. Sections 5.5 and 5.6
                contrast the current RFC and Weather Service Forecast Office (WSFO) computing capabilities
                with those that will be available in the modernized NWS and supported by Advanced Weather
                Interactive Processing System (AWIPS) and other advanced technologies.

FINDING 5.1: Most NWS offices
indicated that a shortage of steam and 
percipitation gages hindered their ability
to produce accurate and timely forecasts.
The Des Moines case study in Chapter 6
dramatically illustrates the major impace
that the loss of just one steam gage can 
have on hydrologic forecast procedures.

RECOMMENDATION 5.1: NWS field
offices should continue to provide support
to cooperating agenices in their effort to
obtain resources for the maintenance of
existing gages and the installation of
additional steam and precipitation gages
in stategic locations.


5-1


                                                                                                                           .............-
                
 












                                          160-


                                          140   - ---------   ---- ----       -----------   ------------------------------------


                                                  ---------   ---- ----       -----------   -----------      ----------------------
                                      u
                                          120-
                                      Q

                                      a)  1100  - --------    ---- ----       -------- -    --------------
                                                                                                       ---- ----------------------


                                      0                       ---- --
                                                                                            ---- -----       ----------------------
                                      "
                                            80  - --------
                                      d

                                            60  - -------                                                                  ---------
                                      E


                                                                                                                       - ----------
                                      Z     40---

                                            20-


                                              0-
                                                          IL     A       KS     MN     MO ND           NE      SD     Wl


                                                                                ROSA M Manual



                     FIgure 5-1. Distribution of cooperative observers.. by state.


                     5.2 DATA ACQUEMON

                     5.2.1 COOPERATIVE OBSERVER NETWORK


                     The NWS Cooperative Observer Network provides hydrometeorological data to NWS offices at how
                     spatial resolutions dw would be available using only standard surface observations. The network in the
                     affected area consists of about 1,700 observers; their distribution, by state, is summarized in Figure 5-1.
                     Data collected by the cooperative observers are used by RFCs as input into their river fore= models,
                     by WSFOs in producing summaries of hydrometeorological conditions for their forecast area , and by
                     various other agencies in deterrnining local climatology.

                     Cooperative observers manually collect data such as precipitation, river stage, snowfall, and maximum
                     and mmimum temperatures. Observed data are routinely reported to the local WSFO or Wmther Service
                     Office (WSO) each morning. Some observers provide additional precipitation measurements during times
                     of significant rainfall based on prescri!)ed critak Approximately 45 percent of the cooperative observers
                     in the Central Region Ininsmit their data to NWS offices using a system called Remote Observation
                     System Automation (ROSA). ROSA is a telephone keypad data entry system dig allows cooperative
                     observers to enter their reports automatically into a centml ROSA computer. These data axe then



                                                                                  5-2





automatically coded in Standard Hydrometeorological Exchange Format (SHEF) and routed to RFC's and 
used as input to their computer models.

Other observers who are not in the ROSA program must telephone thier report to an NWS employee
who, in turn, must manually encode the observations in SHEF and transmit them through the Automation
of Field Operations and Services (AFOS) system, the current NWS operational communications network.
Coding errors occurred as a consequence of significant operational stress and because some of those who
were pressed into service were not familiar with SHEF. Although parse/post software prints messages
identifying SHEF errors, these messages must be manually processed if the data are to be used.  Data
were sometimes lost because forecasters were often too busy to process error corrections.  There were
also some types of errors that the software was unable to detect.

WSFO's had high praise for the Cooperative Observer Program throughout this event.  Offices reported
that they encountered very few problems with ROSA reports.  Those few problems were the result of
errors in coding.  Early in the event, a considerable number of supplemental observations were received
from the cooperative observers.  As the flooding continued, however, these nonroutine observations
decreased in number.  This was due, at least in part, to the fact that some of the copperative observers
were personally impacted by the flood.  The number of river gage observations also decreased as
observers became increasingly threatened by the rising flood waters.

A widespread convern amoung NWS personnel in the affected area was the declining number of
cooperative observers during the last decade.  Vitually all of the offices in the area expressed a desire
to increase the number of observers in their respective cooperative networks.


FINDINGS 5.2: There were a number of
errors in SHEF- coded data.

RECOMMENDATIONS 5.2: The Office of
Hydrology and regions should increase the 
emphasis on training in the use of SHEF for
data exchange.  Additionally, the NWS
should increase the use of automated, quality-
control procedured for data entry including
those appropriate for ROSA.

FINDING 5.3: The number of stations in
the NWS cooperative program has been de-
clining.  There is a need to recover lost 
stations. 

RECOMMENDATION 5.3: Local NWS
offices should explore ways to enhance their
cooperative programs. The importance of the
Cooperative Observer Program should be
stressed to all current and prospective
members of the cooperative network.

FINDING 5.4: Most offices would like to 
see teh ROSA system expanded to include
more cooperative stations.

RECOMMENDATIONS 5.4: Advantages of
ROSA should be emphasized, and NWS
should fund increased deployment of ROSA
systems.

5-3












                5.2.2 AUTOMATED SYSTEMS


                A common data format is critical to effective, automated data exchange. SHEF is widely used
                by the hydrologic community at the Federal level. In addition, many state, regional, and local
                agencies also use SHEF.

                One of the primary software systems supporting real-time data exchange in the NWS hydrology
                program is the Hydrometeorological Automated Data System (HADS). HADS, which is a
                software system running on the National Oceanic and Atmospheric Administration (NOAA)
                Central Computing Facility (NCCF) in Suitland, Maryland, puts data received from satellite
                communications links into a database and generates products for transmission over AFOS and
                over remote job entry (RJE) to RFCs.

                5.2.2.1 DATA COLLECTION PLATFORMS


                The greatest amount of automated hydrologic data is provided through data collection platforms
                (DCP): electronic devices connected to hydrometeorological sensors that observe and report
                through a geosynchronous satellite communications system at predetermined times (usually at
                3-, 4-, or 6-hour intervals). Some DCPs are also capable of reporting at random times in
                response to changing conditions. Several Federal agencies in the flooded area, most notably the
                U.S. Army Corps of Engineers (COE) and the U.S. Geological Survey (USGS), own and
                maintain DCP systems. DCPs transmit a wide variety of data elements, including precipitation,
                river stage, reservoir pool elevation, and ambient air temperature. The DCPs observe data at
                frequent time intervals (as often as every 15 minutes) and store these data for subsequent
                transmission throughthe geostationary satellites to a ground station in Wallops Island, Virginia.
                From there, the data are immediately transmitted to the NWS Telecommunications Gateway and
                on to the NCCF where they are ingested into HADS. These data are made available to RFCs
                through their RJE system and over AFOS. WSFOs have access to the data through AFOS.

                While NWS offices across the affected area had a variety of opinions regarding the accuracy of the
                DCP data, most of the offices expressed concern that the data were not received in a timely manner.
                Often the data were a few hours old when they were received. These delays were caused by a
                variety of factors including delays in assigned transmission windows for DCP data, inadequate DCP
                programming capabilities (i.e., no random channel), obsolete communications architectures,
                inadequate data management and quality-control software, and incomplete or improper use of HADS
                capabilities. The DCP river stage data were generally considered reasonably accurate. More
                fi-equent cases were noted, however, when rainfall data were found to be unreliable. As a result,
                some offices were reluctant to accept these data without additional checking and thus reduced the
                amount of rainfall input to the hydrologic models during this flood event.





                                                               5-4











                  FINDING 5.5: RFCs and WSFOs found            RECOMMENDATION 5.5: DCP data
                  the DCP river stage data to be generally     should be carefully scrutinized daily.
                  useful, but cases were noted when            When errors are detected, the agency
                  significant formatting, decoding, and        owning that particular DCP should be
                  other errors occurred. One RFC felt that     contacted immediately. If the problem is
                  rainfall information from tipping bucket     not corrected within a reasonable time,
                  gages was so unreliable as to be unusable    proactive, follow-up contacts should be
                  with current quality-control procedures.     made when time permits. RFCs should
                  Consequently, the DCP precipitation data     improve their capabilities to display,
                  in the RFC's area were not used in the       verify, and quality control DCP rain gage
                  river and flood forecasts.                   data automatically to make maximum use
                                                               of this valuable data source.

                  FINDING 5,6: Once transmitted, DCP           RECOMMENDATION 5.6: NWS must
                  data take too long to reach the RFC and      ensure that the increased computing
                  WSFO databases.                              capabilities planned as a part of NWS
                                                               modernization include adequate tele-
                                                               communications and a robust data man-
                                                               agement system to alleviate these
                                                               problems. The NWS should implement
                                                               Automated Critical Reports in HADS as
                                                               soon as possible to help alleviate this
                                                               problem.
                  FINDING 5.7: In one instance, the            RECOMMENDATION 5.7: The NWS
                  RFCs had difficulty receiving data from      should provide an in-depth training
                  HADS. The problem stemmed largely            program to HADS focal points at RFCs
                  from the imprecise specification of the      and WSFOs. The NWS should imple-
                  Time Periodic Report capabilities and        ment Automated Critical Reports 1
                  occurred when retrieving COE DCP data        HADS to facilitate data transfer.
                  from the Rock Island District.              1




             5.2.2.2 LIM1TED AUTOMATIC REMOTE COLLECTORS

             Limited Automatic Remote Collectors (LARC), most of which are owned and maintained by the
             NWS, are connected to certain river and rain gages. They transmit river stage and precipitation
             data through a computer modem and voice telephone lines when interrogated. The Centralized
             Automated Data Acquisition System (CADAS) polls LARCs and supplies these data to NWS
             offices through HADS every 6 hours. LARCs can also be interrogated directly by telephone
             dial-up from individual offices.




                                                             5-5













                                                                                                                                Marque
                                                                                                                                            tte

                                                                                                                                                   Monfello
                                                                                                 Adams                                         0
                                                                                                                                                         . .. . . .......
                                                                                                                                                                     Green Lake
                                                              Juneau




                                                                                                                                                          . . . .. . ...........
                                                                                    Wisconsin    Dells



                                                                                                                                                   Pardeeville
                                                                                                                                     Portage
                                                                                                         Barabo
                                                                      Reeclsburg
                                                 . . ... ........ ......
                               . ........... - - ------                                                                                            4
                                                                                                                  9 LARC                6
                                                                                                                                                             2
                                                                                                                        I
                                                                                                                    101
                                                                                                              12                                             Columbia
                                                                                                                          8                    Poynette


                                       Richland
                                                                             Sauk                                                                                   .............. .......... ..
                                                                                                                 . . . . . .. . . .................................. . . . .. .................
                                                                                                                Pairie du Sac

                                                                                                                                                                                             ...............


                                                                                                                                              Dane


                                                                  ..................
                                                                                                                                                                                 Miles
                                      F"'
                                       1                                                           1                                                                      0        5        10

                            Figure 5-2. Analysis of excessive rainfall (in inches) event near Baraboo, Wisconsin, for the
                            24 hours ending at 7 a.m. CDT on July 18, 1993. Most rain ftIl in 4 hours or less. Also
                            shown is the location of the LARC.



                            For the most part, LARCs performed well and were reliable throughout this event. There were
                            several problems, however, which developed as flood waters escalated. Some offices reported that
                            an upper stage limit of 32.7 feet had been programmed into certain LARCs. Consequently, when
                            the river stage exceeded this limit, the LARC did not provide accurate river stage readings.
                            Although NWS offices in North Dakota made a software modification in 1989 to remedy this
                            problem, not all other offices were aware of the problem prior to this event. Other LARC-related
                            problems included cases where manometers (used to measure river stages) connected to the LARCs
                            flooded and where telephone lines were destroyed by flood waters.

                            LARCs were a valuable asset, not only to river forecasters but also to meteorologists involved with
                            flash flood operations. One noteworthy example occurred on July 18, 1993. A LARC gage alerted
                            forecasters at WSFO Milwaukee/Sullivan to heavy rainfall along the Bamboo I;Uver in the vicunty
                            of a major public camping facility. This enabled the forecaster to issue a Flash Flood Warning with
                            enough lead-time to allow people to evacuate. Massive flash flooding inundated the campground


                                                                                                               5-6









              after 12 inches of rain had fallen 4 hours later. Figure 5-2 illustrates the rainfall distribution and
              the location of the LARC which prompted this timely warning. Without the LARC gage, the
              forecaster would have been unaware of the heavy rainfall. Many NWS offices expressed a desire
              to increase LARC coverage in their areas. There may not be sufficient CADAS capacity, however,
              to handle a large increase in the number of LARCs.


                   FINDING 5,8: Some NWS LARCs were                RECONDIENDATION 5.8: Electronics
                   unable to report data when the river stage      Technicians should program LARCs so that
                   exceeded 32.7 feet. The data register in a      they can accept and report data only to the
                   LARC can accept and report information          nearest one hundredth of a foot (resulting
                   from a total of 32,767 increments. If the       in a total range of 00.00-327.67 feet).
                   decimal point is set to read out to one         Electronics Technicians should also set up
                   thousandth of a foot, the unit has a range      all appropriate LARCs so that the data
                   of only 0.000-32.767.                           range is broad enough to cover well
                                                                   beyond the greatest flood of record, as well
                                                                   as below the lowest low flow on record.
                                                                   The NWS Training Center should provide
                                                                   the necessary training to program and set
                                                                   UP LARCs,
                   FT'41DING 5.9; Information obtained from        RECONPAENDATION 5.9:                     High
                   LARCs demonstrably increased the ability        priority should be placed on the installation
                   of forecasters to issue accurate and timely     and maintenance of additional LARCs with
                   forecasts and warnings.                         attached, automated rain gages. The NWS
                                                                   should place a high priority on the
                                                                   Equipment Replacement Program needed to
                                                                   restore, to maintain, and, in some strategic
                                                                   locations, to add LARCs required to sup-
                                                                   port the NWS hydrology program.
                   FINDING 5,10: Currently there are two           RECONEMDENDATION 5.10: CADAS
                   CADAS computers.         System A collects      should be modified to        led data from
                   data from LARCs located in the Eastern          more LARCs. Additionally, the CADAS
                   and Central Regions, and System B collects      interrogation programs should be updated
                   data fi-orn LARCs located in the Southern       to include newer telemetry systems such as
                   and Western Regions.        Each system is      Sutron 8200 data loggers with modems and
                   currently designed to coiled data from 5 10     Campbell CR-10 recorders. The NWS
                   LARCs. System A presently collects data         regions and the Office of Hydrology should
                   from 503 LARCs, and System B presently          establish an advisory board to recommend
                   collects data fi-om 350 LARCs. A better         to the CADAS Program Manager appro-
                   balance between the two systems may be          priate modifications to the CADAS re-
                   po    le to ensure that System A has room       quired to support the NWS hydrology
                   for more than the seven free spaces that        program.
                   now exist.                                     I                                       --J1

                                                                5-7











                    5.2.2.3 TELEMARKs/TALKAMARKs


                    Telemarks and Talkamarks are old telemetry equipment connected to some river gages and allow
                    the gage data to be accessed over telephone lines. Inconsistencies and unexplained fluctuations in
                    gage readings, and in some cases outright failures, were noted with Telemark/Talkamark equipment
                    at some locations. Some of these variations appear to result from gage-mounting strategies and
                    related hydraulic effects that had a considerable impact on Telemark and Talkarnark readings. This
                    effect seemed to be exacerbated as the magnitude of the flood increased.

                    Ile St. Charles County Emergency Management Agency (EMA) reported that the St. Charles
                    Telemark gage regularly registered 0.2-0.8 foot lower than the adjacent staff gage during normal
                    flow. During the flood. event, the EMA reported that the Telemark gage read up to 2.5 feet below
                    the staff gage. The degree of the drawdown effect' was loosely related to the river's rate of flow,
                    but the relation could not be established using a simple coffection factor. Consequently, the EMA
                    increased the NWS stage forecast by the difference between the Telemark reading and the staff gage
                    reading. This undoubtedly caused confusion among the residents of St. Charles County.

                    The St. Charles Telemark river gage apparently flooded out at near-record stage on or about
                    August 1. Complete gage failures and inaccuracies in operational gages due to drawdown and other
                    environmental problems made the official crest stage at St. Charles uncertain. The crest stage is
                    important for future flood planning, levee construction, levee maintenance, and historical flood data.

                    Data from sites with multiple gages were often conflicting. Inconsistent data and hardware
                    differences resulted in readings taken from more than one gage. There was confusion as to
                    what value represented the "real" stage.

FINDING 5.11: Steam gage
observations from mulitple gages at single
locations sometimes created confusion.

RECOMMENDATION 5.11: NWS
policy should clearly designate the pri-
mary and secondary gages at those sites
where multiple gages exist.

FINDING 5.12: In many cases, steam
gages are mounted on the downsteam
side of piers and bridge pilings. At high
flows, drawdown effects may lead to er-
rors and inconsistencies in stage obser-
cations.

RECOMMENDATION 5.12: In a
cooperative effort with the other agencies
involved, the NWS should study the 
drawdown effect to better quantify this
problem.

 The drawdown effect results from the positioning of the stream gage on the downstream side of a bridge pier
 or support to protect it from debris flow in the river. As the river rises and the current increases, an increase in
 velocity behind the obstruction tends to lower the stream level.

                                                                                    5-8
 











                 5.2.2.4 BACKUP OBSERVERS FOR AUTOMATED GAGES


                 For the most part, NWS offices had human observers available to back up automated equipment.
                 Typically, these backup observations were reported to the WSFO/WSO by telephone. Some
                 gages, however, are located at sites that became difficult or unsafe to access. Many observers
                 were themselves flood victims and forced to evacuate the area. The only access to some gages
                 was by boat, but this became hazardous as flows increased.

FINDIGN 5.13: There were numerous
automated steam gage outages
throughout the flood, as well as other
cases with blased observations, that
caused forecasting difficulties.  Although
backup procedures were often in place,
they were not always adequate to meet
the needs for a flood of this magnitude.

RECOMMENDATION 5.13: NWS
offices should ensurd that the backup
plans for steam gages in their areas are
as complete and thorough as possible.
Guidelines should be established and 
tested to provide a smooth transition to 
the backup gage when a site's primary
gage fails.

    5.2.3 RADAR DATA


                 From 1990 to 1992, as part of the modernization and associated restructuring (MAR)
                 demonstration, the NWS installed Weather Surveillance Radar 1988 Doppler (WSR-88D) radars
                 at eight locations in the affected area: Goodland, Dodge City, Wichita, and Topeka, Kansas;
                 Kansas City and St. Louis, Missouri; Chicago, Illinois; and Hastings, Nebraska (Figure 5-3).
                 In addition to demonstrating its effectiveness in severe weather detection, the WSR-88D also
                 proved helpful in forecasting flash floods and floods along rivers with rapid response times.

                 The primary hydrologic products currently available from the WSR-88D are the accumulated
                 precipitation displays. These products use empirical relations to estimate rainfall amounts based
                 on low-level precipitation echo intensity. The estimated precipitation amounts are summed over
                 time periods of I hour, 3 hours, and for the entire time in which low-level precipitation echoes
                 are detected (i.e., storm total). Figure 5-4 depicts a typical WSR-88D accumulated precipitation
                 product.

                 Forecasters were generally pleased with the precipitation products generated by the WSR-88D.
                 While the rainfall estimates were not perfect, they provided a good representation of the rainfall
                 patterns when compared to rain gage measurements. In several cases, forecasters used these
                 products to compose flash flood or flood warnings and provided longer lead-times than would
                 otherwise have been possible. Since the precipitation products give estimates of rainfall in
                 locations without rain gages, some of the flood events for which warnings were issued could
                 possibly have gone unwarned without the WSR-88D data.



                                                                                5-9
 















                                              --------------









                                                        ..........................................
                          ...............
                                 ...............................





                         .... ...                                                     Ch icago
                                           Hastings

                        Goodland




                                                  Topeka@
                                                               nsas City
                                                                                  ouls



                ---------------
                                Dodge  Ci
                                                                                                 ----------
                                                               -------------- .......  ...........
                                                                          ..................





                                                                                              Miles

                                          .. . ....                                     0      100    200 1

               FIgure 5-3. Locations of WSR-88D ra&rs in serwce in area affected by The Great Flood
               of 1993.




               Figure 5-4 illustrates the value of the accumulated precipitation product. The event occurred
               in northwestern Missouri during the night of August 11-12. The 1- and 3-hour precipitation
               estimates from the Kansas City WSR-88D suggested that flash flooding was eminent over Clay
               and Ray Counties, northeast of Kansas City. Flash Flood Warnings were issued well before the
               onset of flooding. Although property was damaged in the counties, no fatalities resulted. The
               maximum radar-estimated rainfall totals of 8-9 inches compared favorably with rain gage
               readings taken on the morning of August 12.

               Although forecasters found the WSR-88D precipitation data useful, some areas for improvement
               were noted. Lightning strikes caused extended system outages at four radar sites. Forecasters
               at WSO Kansas City stated that during flooding or severe weather episodes, two people were
               needed to operate the WSR-88D Principal User Processor (PUP) efficiently. Additionally, the


                                                           5-10








            WSR-88D does not have the same map backgrounds delineating drainage basins used for NWS
            forecasts. At the Missouri Basin RFC (MBRFC), because of sparse observer reports in the
            evening, WSR-88D precipitation data were used to estimate mean areal precipitation (MAP) for
            input to the NWS River Forecast System (NWSRFS) model. This was a difficult and imprecise
            process because the basin boundaries are not identical to those used by the RFC. Additionally,
            hard copies of precipitation estimates from the PUP are not the same scale as MBRFC base
            maps.







                 W                                                                         108/12/93 15:59
                                                                                           STM PRECIP 80 STP
                                                                                            124 NM 1.1 NM RES
               L.                 A.                                                       08112x93 13:49
                                                                                           ROA:KEAX 38x48x35'H
                                                                                           1097 FT    94/15x5OW
                                                                                                   8.1 IN'
                               TV
                                                                                           :MODE A     21
                                                                                           CNTR    15DEG   31NN
                                                                                           3EG=38z11/93 00:41
                                                                                           .7ND=08/12/93 13:51
                                                               IOU                                 NO
                                                                                                   0.0 IN
                                                                                                   0.1
                                                                                                   I.0
                                                                                                   2.0
                                                                                                   3.0
                                                                                                   4.0
                                                                                                   5.0
                                                                                                   6.0
                                                                                                   7.0
                  W"                                                                               8.0
                                                                                                   9.0
                                                                                                   1
                                                                                                   0
                                                                                                   0.
                                                                                                   11.0
                                                                                                   13.0
                                                                                                   15.0
                                                                                           MAG=4X FL= I COM=1
                                @W'



                                                              L

                                                                                           QUEUE EMPTY



                                                                                           12/1535 LINE 3
                                                                                           ENABLED
                                                                                            4RDCOPY

                      j"8                                                                   )RDCOPY REQUEST
                                                                                            @CEPTED





            Figure 5-4.   Kansas City, Missouri, WSR-88D image showing storm total precipitation in
            northwestern Missouri ending at 8.51 a.m. CDT (13.51 UTC) on August 12, 1993.




                                                           5-1 R









                     FINDING 5,14:: Some WSR-88Ds in the           RECOMMENDATION 5.14: Lightning
                     flooded area (Chicago, Illinois; Hastings,    protection and other system improve-
                     Nebraska; St. Louis, Missouri; and            ments for the WSR-88Ds required to
                     Topeka, Kansas) experienced extended          achieve the contract-specified 96 percent
                     downtime as a result of lightning strikes     operational availability must be given
                     and other system failures.              The   high priority.
                     operational availability of the WSR-881)s
                     must be increased to the 96 percent level
                     specified in the NEXRAD Technical
                     Requirements to provide the continual
                     time series of rainfall estimates needed
                     for input to flood and flash flood models.
                     Improved methods for lightning pro-
                     tection are being tested using the
                     WSR-88D at Norman, Oklahoma.

                     FINDING 5,15: The WSR-88D PUP                 RE!QONEMT2i1DAT1ON 5,15: The NWS
                     does not support digital output or provide    should aggressively pursue installation of
                     sufficient capabilities to make effective,    AWIPS and AWIPS-type facilities for
                     quantitative use of the WSR-88D precipi-      WSR-8813-equipped offices and for RFCs
                     tation estimates.   Without the planned       with significant coverage of their areas of
                     AWIPS interactive processing facility and     responsibility by WSR-88D systems.
                     the additional precipitation processing
                     stages planned for AWIPS-era operations,
                     the usefulness of WSR-88D precipitation
                     data for quantitative hydrologic forecast
                     applications is quite limited.
                     FWDING 5.16: To use the WSR-88D               RECONUMMNI)ATION 5.16: Improved
                     precipitation products as input into the      computer technology at the RFCs, which
                     river forecast models, RFC staff had to       is a part of NWS modernization, will
                     manually estimate MAP values using            help remedy this problem. Every oppor-
                     hard-copy printouts.     This method is       tunity should be taken to accelerate the
                     imprecise and time-consuming.                 implementation of computer processing
                                                                   capabilities at the RFCs.     Also, map
                                                                   backgrounds outlining MAP areas should
                                                                   be added to the WSR-88D database.











                                                               5-12












                 5.2.4 OTHER DATA SOURCES

                 The systems listed above served as the primary means of data acquisition. Additionally, other
                 systems also provided valuable information. The following subsections describe these additional
                 data sources.


                 5.2.4.1 SATELLITE INFORMATION

                 Both geostationary and polar-orbiting satellites continue to provide worthwhile information that
                 is used at a number of points in the forecast system. Geostationary satellites provide a continual
                 view of the atmosphere from the global scale down to flash-flood scale. Hemispheric images
                 are useful in preparing synoptic analyses, for example, by identifying such features as water
                 vapor plumes that are not commonly detected by other observing systems. Satellite information
                 is  routinely used in the preparation of quantitative precipitation forecasts QPF)
                 (see Section 5.2.4.2).

                 Mesoscale convective systems are monitored by the Synoptic Analysis Branch (SAB) of the
                 National Environmental Satellite, Data and Information Service (NESDIS). Graphic estimates
                 of rainfall are generated on the Interactive Flash Flood Analyzer (IFFA) in the SAB. During
                 periods of heavy precipitation, the SAB provides quantitative rainfall estimates that are
                 transmitted over AFOS to support operational forecasting in field offices. Currently, IFFA-
                 derived graphical products showing isohyetal precipitation estimates are not available over
                 AFOS. While not all WSFOs relied to the same degree on these estimates, some offices found
                 them quite useful. Neither the NCRFC nor the MBRFC routinely use satellite precipitation
                 estimates in their operational models.

                 Soil moisture monitoring techniques based on data from polar-orbiting satellites are being
                 developed. This information received wide publicity during a briefing by Vice President Gore
                 in mid-July. It is possible that satellite-derived soil moisture estimates could help to specify soil
                 moisture states in the hydrologic modeling system. Details of satellite-derived precipitation and
                 soil moisture estimates are given in Appendix C.


FINDING 5.17: Graphical represen-
tation of satellite-derived isohyetal pat-
terns are not available over AFOS.

RECOMMENDATIONS 5.17: The NWS
and NESDIS should make IFFA-derived
precipitation estimates routinely available
over AFOS during flash flood events.



                                                                           5-13
 




FINDING 5.18: The operational use of 
satellite percipitation estimates has not yet
reached its full potential.

RECOMMENDATION 5.18: The NWS
and NESDIS should develop a procedure 
to intergrate IFFA-dervied rainfall esti-
mates with radar and rain gage observa-
tions.  The procedure should be flexible
enough to compensate for missing 
obervations.

FINDING 5.19: Satellite soil moisture
estimates are not currently used in opera-
tional river forecasting.

RECOMMENDATION 5.19: NOAA
should implement techniques to use re-
motely sensed (i.e., airborne and
satellite) and in situ soul mositure obser-
vations in river and flood forecasting.

 5.2.4.2 QUANTITATIVE PRECIPITATION FORECASTS

                     While RFCs did not objectively and routinely use QPFs as direct input to river forecast models
                     during this flood, the NCRFC did subjectively use QPF information. QPF values were broken
                     down subjectively as an MAP value by RFC staff and incorporated in the hydrologic modeling
                     process. This approach was used extensively over Iowa where the state maps were used by
                     WSFO forecasters to plot QPF. Additionally, WSFO and RFC forecasters used QPFs as
                     guidance to large-scale precipitation patterns. The development of QPF products and their
                     potential skill and use in hydrologic forecasting are discussed in detail in Appendix B.

                     5.2.4.3 ALERT SYSTEMS


                     A Local Flood Warning System (LFWS) is a community or locally based system consisting of
                     rainfall, river, and other hydrologic gages; hydrologic models; a communications system; a
                     community flood coordinator capable of issuing a flood warning; and, in some cases, volunteer
                     personnel. . The purpose of the system is to provide emergency service officials with advanced
                     flood information that can be readily translated into response actions. The Automated Local
                     Evaluation in Real-Time (ALERT) system is a typicalautomated LFWS that was developed by
                     the NWS Califomia-Nevada RFC. Several municipalities in the flooded area were equipped with
                     ALERT systems. ALERT systems are designed to meet the needs imposed by small, fast-
                     response river systems. The basic components of the ALERT LFWS consist of-

                                                            I .Automated event and/or periodic reporting precipitation and river gages,
                                                            2. Automated data collection and processing equipment (base station),
                                                            3. Computerized hydrologic and meteorologic analysis techniques, and
                                                            4. Dissemination of warnings and forecasts.




                                                                                      5-14
 









                     ALERT systems may also contain a hydrologic model, as well as some form of
                     hydrometeorological data analysis techniques and procedures. These systems proved their value
                     in several cities. In at least one case, however, it was not technically possible to transfer NWS
                     products to the ALERT base station.

FINDING 5.20: In at least one case, the 
hardware configuration of the ALERT
system made it technically impossible to 
transfer NWS river forecasts and
warnings to the ALERT system.

RECOMMENDATION 5.20:  NOAA
Wheather Wire is the primary method of 
NWS product distribution. Nonetheless,
NWS forecast offices should ensure that
appropriate memoranda of agreement are
in place withlocal parties for appropriate
two-way exchange between ALERT sys-
tems and the NWS. Where technically
feasible, ALERT systems should be mod-
ified to facilitate exchange of hydro-
meteorological data, forecasts, and
warnings between ALERT systems and 
NWS offices.  Additionally, local hydro-
meteorological detection systems, such as
ALERT, should be tested periodically to 
ensure that they are functioning properly.

 5.2.4.4 SKYWARN SPOTTERS


                     Across the affected area, thousands of amateur radio operators, law enforcement and fire
                     officials, and members of the public serve as volunteer weather spotters in the NWS SKYWARN
                     program'. Spotters played an important role in reporting significant weather events, especially
                     in North and South Dakota, where the spotters seemed well-versed in flood reporting
                     procedures. In other areas, however, the SKYWARN program was less effective in providing
                     flood-related information.




                      2   In general, SKYWARN spotters are a group separate from cooperative observers. The primary
                     responsibility of SKYWARN spotters is to monitor their areas for signs of severe weather (e.g., tornadoes,
                     lightning, high winds, flash flooding) and to report to a local NWS office when such conditions are observed.
                     Reporting is done only as a result of a given event and typically does not include quantitative weather observations.
                     Many SKYWARN observers report over HAM radios. Cooperative observers, however, usually report quantitative
                     information (e.g., river stages, precipitation, temperature, etc.) on a regular basis while sometimes providing
                     supplemental reports of unusual conditions. Many cooperative observers report over telephone lines. The
                     remainder mail in their observations, which are not used for operational forecasting but for climatological purposes.

                                                                                                         5-15
 





FINDING 5.21: There was variation in 
the effectiveness of reporting flood
conditions by SKYWARN observers.

RECOMMENDATION 5.21: NWS
Headquarter should include in the 
SKYWARN spotter training syllabus
material on flood reporting.  Local
offices should educate observers about
effective flood-reporting procedures.
Spotters should be encouraged to submit
reports when heavy rain and/or flooding
occurs (which may require making
affordable rain gages available).

  5.2.4.5 STREAMFLOW MEASUREMENTS


                     Other government agencies are sources of valuable streamflow and precipitation data.
                     Excellent coordination is imperative to ensure that these data are received in a timely manner
                     to allow for thorough analyses. The COE contracted with the USGS to collect several
                     hundred special discharge measurements to better quantify volumes of flow and stage-
                     discharge relations at key locations. Most of these extremely valuable special measurements
                     were made available to RFCs and some WSFOs. The efficiency and timeliness of the data
                     transfer, however, was slowed by the lack of adequate communications links. Nevertheless,
                     the special discharge measurements were used by the RFCs whenever available to assess
                     existing river conditions for input to their river forecast procedures.


FINDING 5.22: Existing stage-
discharge relations were exceeded at
approximately 100 sites.  During the
most severe flooding, flow mearure-
ments were too sparse.

RECOMMENDATION 5.22: Through
collaborative efforts with principal 
NOAA cooperators, resources (in-
cluding thos to updat steamflow
measurements and/or perform analyses)
need to be made avail-able so that new
stage-discharge relations can be devel-
oped for these sites.

                                                                                   5-16
 




FINDINGS 5.23: There were periodic coor-
dination and communications problems
associated with data exchange between
Federal agencies. For example, appropriate
NWS offices did not always receive, in a
timely manner, the specila streamflow mea-
surements made by the COE or USGS.
Additionally, appropriate NWS offices were
not always made aware of the steamflow
measurement schedules; consequently, it
was impossiblee to infer when NWS offices
did no have specific steam discharge mea-
surements.  Computer hardware limitations
sometimes made it difficult to distribute
NWS products to end-users. Consequently,
NWS offices were, in occasion, required to
fax forecasts and products to end-users.

RECOMMENDATION 5.23: The COE,
USGS, and NWS should improve 
communications links among themselves 
and with oter Federal, state, and local
agencies. Specifically, the three agencies
should ensure that the data collection
schedules and the data distribution mecha-
nusms for steam discharge measurements
and other valuable hydrometeorological
data sets are well understood and 
documented. In some cases, computer-to-
computer links must be developed and/or
upgraded (see Recommendation 6.19).

  5.2.4.6 STRANGER REPORTS


                 "Stranger reports" include information not normally used in the forecast process. Frequently they
                 are precipitation and river stage observations received from unofficial sources. In addition to
                 providing valuable information to such products as Special Weather Statements and Flash Flood
                 Statements, they can be a source of supplemental information that can improve RFC forecasts.
                 Precipitation data from stranger reports cannot, however, conveniently be input into NWSRFS in
                 its present form. RFC personnel must input these reports at defined, nearby missing stations, or
                 manually estimate affected MAP areas. Because of tins labor-intensive process, stranger reports
                 provided by WSFOIWSOs are not usually used.

FINDING 5.24: Precipitation from
stanger reports cannot conveniently be
input into NWSRFS in its present form.
RFC personnel must input these reports at
defined nearby missing stations, or manu-
ally estimated affected MAP areas.  Because
of this labor-intensive process, stranger
reports provide by WSFOs/WSOs are not
usually used.

RECOMMENDATION 5.24: The OH
should make the necessary effort to modify
the MAP preprovessor so it can accom-
modate stranger reports.

                   5-17
 
















                5.2.4.7 AIRBORNE SNOW AND SOIL MOISTURE SURVEY

                The Office of Hydrology and the National Operational Hydrologic Remote Sensing Center
                maintain an Airborne Snow Survey Program. Low-flying aircraft are used to make airborne
                measurements of natural terrestrial gamma radiation along selected flight lines. The gamma
                radiation data are used to infer snow water equivalent with an error of less than I cm.
                Additionally, the airborne technique is also used to infer soil moisture to a depth of 20 cm
                under snow-free conditions. The Airborne Snow Survey Program maintains a flight line
                network covering large portions of 26 states and 7 Canadian provinces. The airborne snow
                water equivalent data collected in the winter, and the soil moisture data collected in the late
                fall, are used by NWS hydrologists in RFCs and WSFOs when assessing the potential for
                significant spring snowmelt flooding and when making water supply forecasts in the West.

                Airborne snow surveys were conducted over the Upper Midwest during the winter of 1993.
                Based partly on the airborne snow water equivalent data collected over the Upper Midwest
                in February and March 1993, the NCRFC issued a spring flood outlook on March 25 that
                called for moderate to major flooding across large regions of Iowa. In a few limited cases,
                however, inadequate late-winter and early-spring, ground-based, snowpack observations in
                remote areas of the Upper Midwest led to false assumptions that much of the snow water
                equivalent had run off or had been absorbed into the ground. In reality, much ice and snow
                water equivalent remained. Runoff into some rivers was much higher than expected and
                resulted in significant flooding. Spring snowmelt in the Upper Midwest primed the region
                for the major flooding which was to follow. Airborne gamma radiation snow surveys
                provided essential information in evaluating water content of the snowpack and subsequent
                runoff.


                Airborne snow surveys depend on an accurate knowledge of soil moisture to determine the
                amount of water contained in the snowpack. The Great Flood of 1993 left above-normal soil
                moisture conditions. To ensure accurate airborne snow water equivalent measurements in
                the spring of 1994, airborne soil moisture measurements should be   'made in the fall of 1993.
                Soil moisture information is also critical in operational river forecasting. The soil moisture
                information collected in support of airborne snow estimation will provide information used
                in routine forecast operations both this fall and in the spring.









                                                            5-18









                  EMING 5.25:. Much of the early                   RECOMMENDATION 5.25'.
                  flooding (March, April, and May) in the          Hydrologists in the regional, RFC, and
                  Upper Midwest was aggravated by above-           WSFO offices should request airborne
                  normal snow cover conditions that devel-         snow surveys over specific areas within
                  oped during the winter and spring of 1993,       their respective regions of responsibility
                  WSFO Sioux Falls indicated that additional       when snow water equivalent is expected to
                  snow water equivalent data would have            be a major factor associated with spring
                  been valuable before the onset of the 1993       flooding in the Upper Midwest.
                  spring snowmelt flooding.         The NWS
                  maintains a dense network of airborne
                  flight lines in the Upper Midwest. The air-
                  b<x= snow survey program provides reli-
                  able, real-tirne airborne snow water equiva-
                  lent measurements over the flight line net-
                  work for use by NWS field offices when
                  assessing the potential for spring snowmelt
                  flooding.

                  FWDING 5,26: The Great Flood of 1993             RECONUWENDATION 5.26: The Office
                  left large regions of the Upper Midwest          of Hydrology should make a comprehen-
                  with much above-average sod moisture             sive airborne soil moisture survey over the
                  conditions in the fall of 1993. The existing     existing flight line network in the Upper
                  network of airborne flight lines can be used     midwest to provide an assessment of soil
                  to make airborne soil moisture measure-          moisture conditions in the late fall of 1993.
                  ments in the late fall of 1993. Fall air-
                  borne soil moisture measurements are used
                  by NWS hydrologists at the NCRFC when
                  assessing. ft powntial for future flooding
                  during each winter and spring.




             5.3 TELECOMMUNICATIONS


             While much of the telecommunications activity associated with the flood involved the dissernination
             of information to emergency managers and other users, telephone systems were used for the
             acquisition and relaying of some data as well. Cooperative observers and LARCs were accessed
             by telephone (see Sections 5,2.1 and 5.2.2.2); and, in some cases, EMAs relayed flood and
             evacuation information to NWS offices by phone. 'Telephone service was generally satisfactory
             during the event, but there were some flooded areas in which the telephone lines were destroyed.
             As a result, contact was lost with some key agencies and data sources.




                                                                5-19









                There is no existing, high-speed, wide-area communications network between NWS offices and
                other key governmental water agencies. RFCs have a "Gateway System" which provides two-
                way communication between the RFCs and selected Federal cooperators. The current system
                runs on a mid-1970s minicomputer. The system is so old, for example, that the maximum
                asynchronous baud rate attainable is 4800.

                As discussed in Chapter 4, operational forecasting is typically done on computer systems located
                at the NCCF in Suitland, Maryland. The RFCs are connected to the NCCF via RJE by low-
                speed, 9600-baud communications circuits. During extreme flooding, such as experienced in
                The Great Flood of 1993, the number of required forecasts and updates becomes enormous.
                Current communications links supporting RJE were often not fast enough to meet the elevated
                operational needs of the RFCs. Major improvements in both the level of independence from the
                NCCF and the communications capacity for the RFCs in the modernized NWS should alleviate
                most communications problems with the NCCF.

                Over the weekend of July 9-11, significant communications problems occurred in Suitland as a
                result of a power outage caused by an automobile accident that knocked down a utility pole.
                The resulting power outage affected communications equipment housed in a building separate
                from the NCCF itself and effectively severed RFC RJE communications. Auxiliary power had
                to be used during this event. There were significant periods, however, when there was no
                9600-baud dedicated link between any of the RFCs and the NCCF during the time when backup
                power was being brought on-line. During those periods, the RFCs were required to use slower
                (4800-baud) backup lines to connect with the NCCF. The two RFCs in the area affected by
                The Great Flood of 1993 (MBRFC and NCRFC) were given highest priority for the available
                backup lines and experienced a complete outage of NCCF telecommunications for only a
                4.5 hour period; other RFCs were without NCCF telecommunications for as much as 22 hours.
                Although this event did not have a serious service impact, it clearly illustrated the dependence
                of the RFCs on the NCCF and the vulnerability of the NWS Hydrologic Service Program should
                a disastrous failure occur.


                AFOS is the operational communications system currently used by the NWS and is based on
                early 1970s minicomputer technology.          The AFOS system at the RFCs is used as a
                communications system for disseminating forecast products to WSFOs. While there are
                concerns about its inability to move information rapidly, in spite of its age, it proved remarkably
                reliable. The System-Z AFOS upgrade increased system stability.

                The telecommunications path for certain Canadian information routes data from the National
                Center in Toronto, through NMC, to NWS WSFOs. These data are often delayed or unavailable
                by this pathway, but WSFO Bismarck dials directly into Environment Canada, thus bypassing
                the national route.








                                                               5-20












                  FINDING 5.27; Telephone lines to               RECOMMENDATION 5.27: The use
                  certain key stream gages were destroyed        of alternative data acquisition systems for
                  by the flood.                                  stream gage data (e.g., radio, satellite, or
                                                                 meteorburst transmission technology)
                                                                 should be explored to build redundancy
                                                                 into the system at key locations.

                  FINDING 5,28:          The current tele-       RECONEMWNDATION 5.28: The NWS
                  communications environment for inter-          should implement plans for modem tele-
                  agency data exchange relies on limited,        communications and information ex-
                  voice-grade, two-way links. This tele-         change with major water management
                  communications approach did not provide        cooperators and conduct a demonstration
                  an adequate level of service to the COE        of these capabilities as soon as possible.
                  and other Federal, state, and private co-
                  operators during The Great Flood
                  of 1993. Moreover, it is completely in-
                  adequate to support even higher rates of
                  data exchange. Higher levels of service
                  can be achieved now with available tele-
                  communications technology.

                  FINDING 5,29: WSFO Bismarck dials              RECONEMIENDATION 5,29: NWS and
                  directly into the Environment Canada           Environment Canada field offices should
                  system for data.      There are frequent       continue their good working relations.
                  problems, however, in routing data from        The National Meteorological Center and
                  the 'National Center in Toronto through        Environment Canada's National Center
                  the National Meteorological Center to the      should investigate the possibility of im-
                  WSFO. These data are often delayed or          proving the interface between their com-
                  unavailable.                                   puter systems.
                  FINDING 5,30; There is no backup               RECONEMIENDATION 5.30:                    As
                  should there be a disastrous failure of the    quickly as possible, NOAA should devel-
                  NCCF for those RFCs that are still de-         op disaster contingency plans to use dis-
                  pendent on the facility.                       tributed AWIPS-type RFC systems to
                                                                 provide backup for NCCF-dependent
                                                                 RFCs until AWIPS is deployed.









                                                              5-21









                     FMING 5.31:. Despite the limited             RECONEMW24DATION 5.311 AFOS
                     capabUities, of AFOS and the fact that       must be maintained as a highly reliable
                     those capabilities were pushed to their      operational NWS system until replaced
                     lin-dts throughout the flood event, AFOS     by AWIPS at the earliest possible date.
                     generaUy perfbrmed in a reliable and
                     stable manner. Concern was expressed
                     that. AFOS, which, has exceeded its
                     original life expectancy, will not be able
                     to continue reliable performance.

                     FINDING 5.L2:.            Communications     RECOMMENDATION 5,32: The NWS
                     between RFCs and the NCCF are critical       must evaluate its backup procedures to
                     to RFC operations and are a weak link mi     ensure there is sufficient communications
                     the current.river forecast system.           capacity to support operations during
                                                                  major flooding.

                     FINDING 5,33:             Current RFC        RECONUVIENDATION 5.33: All RFCs
                     communications capabilities are too slow     should be made aware of the potential use
                     for extreme loads generated at times of      of the dial backup RJE circuit as an
                     widespread major flooding. During The        emergency, temporary boost to their
                     Great Flood of 1993, a workaround was        NCCF telecommunications capabilities.
                     developed to operate both the dedicated
                     9600-baud circuit simultaneously with the
                     4800-baud dial backup circuit for the
                     North Central RFC. This was effective
                     in increasing the communications capacity
                     by 50 percent, but it is expensive and has
                     no backup.





               5.4 FACELITEES


               RFCs, WSFOs, and WSOs conduct their operations in a wide variety of facilities. The size of
               the staffs and the programs maintained by the various offices are the primary factors used to
               determine the space and resources available at a particular facility. While most NWS staff felt
               that their facilities were adequate for conducting their operations, concerns were voiced
               regarding a lack of flat workspace for oversize topographic maps and other bulky materials
               needed for the proper analysis of hydrometeorological conditions.






                                                               5-22




FINDING 5.34: Some offices lack large
workspace areas for use of bulky items
such as topographic maps.

RECOMMENDATION 5.34: The 
layout of new facilities being built as part
of MAR should be configured to consider
the requirement for flat workspace.
Where parctical, current offices should be
rearranged to accommodate this
requirement.

                                                                                   
                5.5 CURRENT HYDROLOGIC FORECAST SYSTEM CAPABILITIES AND
                         LIMITATIONS AT THE RFC AND HYDROLOGIC SERVICE AREA
                          OFFICES


                The ability of an RFC to produce timely and accurate hydrologic forecasts hinges on the quality
                of the hardware, hydrologic software, and communications systems available. Similarly, the
                ability of a Hydrologic Service Area (HSA) office to disseminate locally, to update quickly, or
                to produce its own forecasts is closely tied to the availability of local, interactive processing
                capabilities. Neither RFC nor HSA offices in the affected area have the necessary software and
                hardware to systematically support on-site, local processing and interactive execution of the latest
                hydrologic software necessary to carry out their missions effectively.

                5.5.1 CURRENT HYDROLOGIC HARDWAREISOFTWARE SYSTEMS AT THE RFC

                For the most part, both the MBRFC and NCRFC have old and outdated hardware, hydrologic
                software that executes primarily on remote mainframe computers, and communications circuits
                that are limited and slow. One RFC did not have an Electronics Technician on staff to keep
                systems operational. Often forecasters were required to perform Electronics Technician duties.

                At both RFCs, hydrologic forecast systems are executed in a 1960s batch-oriented environment.
                RFCs submit forecast runs known as "jobs" to a mainframe computer located at the NCCF, via
                RJE. Hydrologic forecast model output is returned to the RFC in a text format that is either sent
                to a line printer or displayed (rotated by 90 degrees) on a CRT (monitor). The display of the
                forecast hydrograph lacks the detail necessary to discern many hydrologic features. If even one
                simple change is needed, the forecaster must create a "run-time modification," submit the
                modification to the mainframe computer via RJE, and wait. The entire process is slow and time-
                consuming.

                The MBRFC has a PRIME minicomputer that is used to manage hydrologic data locally and to
                exe  cute part of the RFC's hydrologic software. Although useful, the PRIME is currently
              
		    8-10 years old and has an extremely slow processor. For example, some data-processing tasks
                take up to 2 hours.



                                                                          5-23
 








                 The NCRFC has implemented a local network of microcomputers that is used to help expedite
                 forecast operations. This network served well during the flood but does not include the
                 processor for executing hydrologic models. The NCRFC still relies on a batch-oriented RJE
                 with remote processing on the mainframe computer for its forecast operations.




                      FINDING 5,35: The posting, data                  RECOMNUNDATION 5.35:                     T be
                      management, and quality control of               AWIPS system (which wW employ
                      hydrometeorological data, in general, is         sophisticated graphics, database, and
                      too slow, laborious, nonsystematic, and          computing capabilities that far exceed
                      incomplete.                                      those currently in use) should eliminate
                                                                       system reliability problems and facilitate
                                                                       data management tasks. It is essential
                                                                       that AWIPS be implemented as soon as
                                                                       possible.

                      FINDING 5,36: Users indicated a need             RECONEMW2-IDATION 5.36: The NWS
                      for more frequent river forecast updates.        should move as quickly as possible to
                      The RFC model update cycle is depend-            install   on-site,   interactive      forecast
                      ent on batch computer operations over a          systems in RFCs to speed up production
                      communications link to the NCCF. This            of forecast products, including updated
                      problem was less acute for the MBRFC             river forecasts and contingency forecasts
                      because some forecast operations are run         based on various precipitation scenarios.
                      locally on a minicomputer. Batch-mode            Although the AWIPS system will
                      operations not only contribute to delays in      ultimately support this interactive RFC
                      forecast updates but also inhibit the fore-      environment          completely          (see
                      caster from gaining the level of insight         Recommendation 5.35), opportunities to
                      into hydrometeorological conditions that         take advantage of AWIPS-type facilities
                      is possible with local, interactive pro-         and/or early AWIPS platforms must be
                      cessing. This contributed to delays in           maximized. Additionally, HSA offices
                      forecast release times.                          should work with the RFCs to coordinate
                                                                       event-driven updates that provide users
                                                                       with timely flood warning information.
                      FINDING 5.37:             Various system         RECONEMWENDATION 5.37:                   Con-
                      hardware problems and      the lack of tech-     tingency plans should be developed by
                      nician support required hydrologists to          the Office of Systems Operations and the
                      perform electronic maintenance functions         NWS regions to ensure that all RFCs
                      to eep systems operating.                        have adequate electronic systems support
                                                                       during critical flood events.






                                                                   5-24












             5.5.2 CURRENT HYDROLOGIC HARDWARE AND SOFTWARE SYSTEMS AT THE
                    HSA OFFICES

             The main computer and communications system at offices with HSA responsibility is AFOS.
             This technology is old, outdated, and does not provide the appropriate computer architecture to
             develop or to execute data-intensive, interactive hydrologic forecast models. Moreover, AFOS
             does not contain a robust database management capability needed to run hydrologic models.

             The Central Region has provided a microcomputer to each Service Hydrologist to support the
             Service Hydrologist Information Management System, known as SHIMS. This has greatly
             helped the HSA office to organize the administrative part of the Service Hydrologist Program.
             There is no current national or Central Region program, however, for providing microcomputers
             to HSA offices in support of automated data collection and/or automating simple hydrologic
             procedures. Most HSA offices indicated the need for additional computer capability to help
             support the NWS hydrology program.


             5.6 MODERNIZED HYDROLOGIC FORECAST SYSTEM CAPABILITIES AT
                    THE RFC AND HSA OFFICES


             Many of the limitations and problems associated with the current hydrologic forecast systems
             at RFC and HSA offices will be resolved when the offices receive the modem technologies
             associated with MAR. Users requested more accurate, more site-specific, and more timely
             hydrologic forecast service. The implementation of advanced technology, such as the AWIPS,
             the WSR-881), and the Automated Surface Observing Systems, known as ASOS, coupled with
             components of new hydrologic software, will allow Weather Forecast Offices (WFO) the ability
             to satisfy these needs.


             5.6.1 MODERNIZTD HYDROLOGIC FORECAST SYSTEM CAPABILITIES AT THE RFC

             The hydrologic forecast system capabilities at an RFC in the modernized NWS will increase
             dramatically. The most significant change will be the use of an on-site, interactive forecast
             system in real-time coupled with high-resolution precipitation data. The interactive system will
             execute in a distributed network environment and will provide forecasters a graphical user
             interface for easy access and flexibility. Other features of the system will allow a choice of
             models and procedures, user control for selection of models and methods used, and procedures
             for easily adding new models to keep up with scientific and technological changes. Each RFC
             will be able to process large amounts of data and quickly produce forecasts for hundreds of
             locations.





                                                          5-25









                The ability to process precipitation data automatically will constitute another dramatic change.
                The ability to derive and to use spatially and temporally detailed precipitation estimates in
                advanced hydrologic models will revolutionize the science of surface water hydrology. The
                precipitation processing system win ingest, merge, and mosaic precipitation estimates from
                multiple WSR-88D radars, observed precipitation data from rain gages, and satellite precipitation
                estimates. The result of this processing will be timely estimates of gridded precipitation fields
                used as input to the interactive forecast system.

                The use of a modem database management system will be another significant change that will
                provide an efficient means to manage real-time and historic data, model parameters, forecasts,
                rating tables, and gage and station information.


                5.6.2 MODERNMED HYDROLOGIC FORECAST SYSTEM CAIPABELMES AT THE
                        HSA OFFICES


                In the modernized NWS, the WFO will have HSA responsibility. The hydrologic forecast
                system capabilities at the WFO will increase dramatically'. WFOs will receive real-time advice
                and counsel along with improved support products from the RFCs and will use the vast
                hydrometeorological. databases and capabilities produced by new technologies. WFOs will be
                able to issue timely, site-specific warnings and follow-up statements for floods and flash floods,
                as well as other hydrologic products.

                WSFOs did not have the data and tools necessary to produce local forecasts or to update and
                customize RFC guidance. (See also Chapter 2 and Section 4.7.3.) One of the most important
                advancements at the WFO will be the capability to produce hydrologic forecasts and warnings at the
                local site. The HSA offices will have an interactive hydrologic forecast model running locally.
                Although RFCs will be responsible for maintaining the integrity of the local forecast model, the HSA
                office will be the principal user in real-time situations. Another significant improvement will be the
                availability of high-resolution precipitation data from the WSR-88D radars.


















                                                                5-26









                                                           CHAPTER 6


                                    WARNING AND FORECAST SERVICES





               6.1 INTRODUCTION


               The Great Flood of 1993 made unprecedented demands on the NafiorW Weather Service (NWS) for
               warning and forecast services. Thousands of forecasts were produced and issued under extremely
               complicated hydrometeorological conditions. There were long penods of widespread, heavy rains.
               Massive levee breaks occurred at random. In addition, complicated backwater situations made it difficult
               for personnel to "keep up" with timely information. In spite of the complexity and scope of the event
               and the outdated technologies in most NWS offices, NWS personnel provided outstanding service.

               The magnitude of the event prohibits a full and detailed description of the services provided by the NWS.
               A summary of the forecast and warning services is represented by an overview of products issued from
               all offices. More detailed analyses of the forecast service are provided for several selected forecast points
               on the upper Mississippi and Missouri Rivers. Technical details of the forecast service are provided in
               two caw studies.



               6.2 RESPONSIBELMES OF RIVER FORECAST CENTERS


               The Missouri Basin River Forecast Center (N[BRFC) and the North Central River Forecast Center
               (NCRFC) prepare river forecasts in their respective areas of responsibility (see Figure 6-1). Forecasts
               are prepared for site-specific locations called "river forecast points." A river forecast point represents a
               "reach" along a river above and below the gaged site. In most cases, it has an associated straim gage
               and a stage4scharge rating (see Section 4.3.1.2). The River Forecast Centers (RFC) also produce flash
               flood and other hydrologic guidance products for their areas. Guidance products are dawminated to
               Wmther Service Forecast Offices (WSFO) and Weather Service Offices (WSO) that have Hydrologic
               Service Area (HSA) responsibility.

               The NCRFC is responsible for prepafing river forecasts for the Mississippi River drainage from its
               headwaters to Chester, Illinois, excluding the Missouri River basin. Its area of responsibility encompasses
               the Red River of the North to the Canadian border, including the Souris basin in North Dakota and the
               Roseau River in Minnesota; the Rainy River in Minnesota; the mouth of the Big Muddy in Illinois; and
               the Great Lakes tributaries in Michigan, Minnesota, Wisiconm, Illinois, and Indiana, except the Maumee
               basin. The "hand-off" point to the Lower Mississippi River Forecast Center (LMRFC) is at Chester,
               Illinois, on the Mississippi River. The NCRFC has 456 river forecast points in its area of responsibility.
               Of these, 298 points are located in the Mississippi drainage and 44 are in the Red River of the North.



                                                                   6-1





















                                    NWRFC


                                                                         14CRFC
                                                                                               N


                                 CNRFC
                                                                                           ;AR
                                              ceirc
                                                                                 0 FC


                                                                       BRF



                                                                 ABRFC

                                                                                    SERM

                                                               WORM

                                                                         LMR





                                          AKRFC







                     Figure 6-1. Locations of, and areas served by, the 13 NWS River Forecast Centers.
                        CP_



                The MBRFC prepares river forecasts for the main stem and all tributaries of the Missouri River
                down to St. Charles, Missouri. The forecast point at Hermann, Missouri, is the hand-off point
                to the NCRFC. MBRFC is responsible for 446 river forecast points. A summary of the number
                of forecast points for each HSA office, by RFC, is shown in Table 6-1.


                6.3 OFFICES WITH HYDROLOGIC SERVICE AREA RESPONSIBILITY


                Selected NWS offices, usually WSFOs, are assigned HSA responsibility. The HSA office takes
                the numerical river forecasts, produced by the RFCs, adds local information (e.g., current river
                stage information, "call-to-action" statements, flood stage, levee elevations, and expected areas
                of inundation), and issues river forecasts, flood warnings, and other hydrologic products. These
                products are disseminated to the general public, specialized users, and the media through various
                means (see Chapter 7). The HSA office must also be alert to hydrometeorological situations that
                have a potential for flood-producing rains. Due to rapidly changing conditions, they actively
                collect data and issue preliminary forecasts and warnings when RFC guidance is not available.
                WSFOs (usually having HSA responsibility) also issue flash flood watches and other
                meteorological forecast products.



                                                              6-2







            Table 6-1. Number of riverforecast points by RFC and HSA.



                   NWS OFFICE                         NCRFC           N[BRFC           ADAPTIVE
                   WrM HSA                HSA FORECAST FORECAST                       FORECAST
                   RES19NSIUBU,ITY        ID          p0im            POINTS          POE.4TS*

                   Bismarck               BIS             60               23               0
                   Chicago                LOT             104                -              0
                   Des Moines             DMX             69               32               0
                   Minneapolis            MSP             57                 -              a
                   Milwaukee              MKE             40                 -              0

                   Omaha                  OMA               -              98               6

                   St. Louis              LSX             30               64               0

                   Sioux Falls            FSD               -              42               0
                   Topeka                 TOP                              99               0


                      * Adaptive forecast points are points where hydrologic relationships are developed using
                      information from nearby official river forecast points. Once developed, these relationships
                      enable NWS offices with Hydrologic Service Area responsibility to issue adaptive forecasts
                      at those points to better serve the public.





            Although they do not have HSA responsibility, about 20 WSOs in the area impacted by
            The Great Flood of 1993 are responsible for issuing flash flood warnings for designated counties
            in their county warning areas. In addition, WSOs collect hydrologic data and serve as the local
            contact for the public and media and provide forecasts and warnings.

            The offices with HSA responsibility and their areas of responsibility are delineated in
            Figure 6-2. A brief synopsis of the hydrologic features contained in each of the HSAs follows:

            Bismarck (BIS):            Rivers in North Dakota, including the Red River of the North main
                                       stem and tributaries in Minnesota from the Canadian border to the
                                       South Dakota border.


            Chicago (LOT):             Rivers in Illinois, including the main stem of the Mississippi from
                                       below Dubuque, Iowa, to below Dam 19 near Keokuk, Iowa, and the
                                       Calumet basin in northwest Indiana, except the main stem Ohio River
                                       along the Illinois-Kentucky border.


                                                           6-3








                   Des Moines (DNW:              Rivers in Iowa, including the main stem of the Des Moines River along the
                                                 Iowa Missouri border, except the main stein Mississippi River along the
                                                 Idwa-Wisconsin-Illinois borders, except the main stem Missouri River along
                                                 the Idwa-Nebraslm border, and except the Big Sioux along the
                                                 South Dakota-Iowa border.

                   Milwaukee (MKE):              Ux Montreal, Bnde, and Menominee Rivers along the Michigan-Wisconsin
                                                 border, and all streams in Wisoonw, except the St. Croix River along the
                                                 Wisconsin Minnesota border and except the Mississippi River along the
                                                 Wisconsin-Minnesota border.

                   Minneapolis (MSP):            The St. Croix River along the Minnesota-Wisconsin border; the Mississippi
                                                 River, to and including Dubuque, Iowa, and all rivers in Minn=ta, except
                                                 the Red River of the North main stein and tributaries.


                   Omaha (0MA):                  Rivers in Nebraska, including the main stem Mmm River along the
                                                 Nebraska-lowa-South Dakota-Missouri borders.

                   Sioux Falls (FSD):            Rivers in South Dakota, including the Big Sioux along the South Dakota-
                                                 Iowa border , except the main stem Missouri River along the South Dakota-
                                                 Nebraska border.


                   St. Louis (LSX):              Rivers in Missouri; the Mississippi River from below Dam 19 near Keokuk-,
                                                 Iowa, to and including Carutherwille, Mmm; the Missouri River from the
                                                 Missouri-Kansas border to the confluence with the Mississippi River, and the
                                                 Ohio River from Cairo, Illinois, to its mouth. (Kansas City WFO has
                                                 forecast responsibility for eight forecast points on the reach of the Blue River
                                                 that flows through the Kansas City intoopolitan area.)

                   Topela (TOP):                 Rivers in Kansas, except the main stein Missouri River along the Kansas-
                                                 Missouri border.



                   6.4 HYDROIDGIC SERVICES FOR THE MPER NIISSISSIM RIVER BASIN


                   6.4.1 OVERVIEW OF FURECAST FRODUM

                   During The Great Flood of 1993, 189 locations within the NCRFC area of responsibility exceeded flood
                   stage (41 percent of the total number of locations). Of dime, 44 locations within the upper Mississippi
                   River basin exceeded the previous flood of record. Appendix D lists locations and associated stage
                   inforination for those stations which exceeded record crests.


                   Locations obsemng (preliminary) new record stages in the upper Mississippi River and Red River of the
                   North basins, together with locations experiencing record and near-record stages in the Missouri River


                                                                       6-4





Figure 6-2. Locations of, and areas served by, the NWS Offices with Hydrologic
Service Area responsiblities.

basin are shown in Figure 6-3. New record stages are indicated by filling triangles; gages that approached
existing records are shown as filled circles.  Numbers idientifying each location correspond to the index
number listed in the first column of Tables D-1 (new records in the Mississippi drainage: numbers 1-44),
D-2 (new records in the Missouri drainage: numbers 45-93, D-1 (near records in the Missouri drainage:
numbers 94-116), and D-4 (new records in the Red River of the North drainage: numbers 117-118).

HSA offices in Minneapolis, Chicago, Milwaukee, Des Moines and St. Louis issued thousands of
hyfrologic forecast and warning products during the flooding episode.  Over 16,000 specific river
forecasts (1) were issued for the upper Mississippi  River basin during the event.  Tables detailing products
issued by each WSFO with HSA responsiblity are included in Appendix E. Figure 6-4 shows the total
number of these products issued during The Great Flood of 1993 by HSA offices.  The same information,
broken down chronologically, is shown in Figure 6-5. In the figure, each bar represents the total number
of products issued by all HSA offices for each week, from June through mid-August.




(1) In many cases, a single product contained forecasts for multiple locations along one or more rivers.  This
accounts for the much larger number of specific forecasts than producats issued.

6-5



























                                                                 117,                                                   %-A







                                                            4k





                                                                      41


                                                                                        42
                                                   46


                                                                       53


                                                96                                                                           40&
                                                                                                    24,
                                                                                      32  21*19     5   2
                                                         1010                                 34                  7         17
                                                                            51L            31               2:k   &
                                                                                                        20           3
                                                                                                        35        2
                                                                 4 104      52  5!k              79&
                                                                     1  a   M                                3    5      Ilk
                                                                          110                                 a
                                                                                                                  7
                                                               70A &73            82         6
                                                                                  &58           77
                                                         11    71L                                                    10
                                                    10  105                 6                                            16
                                                           66                       83 84                            11 1    3
                                                     112  110 7                                                   2    9     14
                                                    109                               11;6              90    91
                                                      106

                                                                                                                               5




                         I


                         Figure 6-3. Locations of (preliminary) record and, for the Missouri River basin, near-
                         record river stages, during The Great Flood of 1993. The labels for each point
                         correspond to index numbers listed in Appendix D. Triangles show newfloods of record
                         and circles are locations that approached theflood of record.


                                                                               6-6















                           2500-





                           2000-





                           15w-
                        a.

                        -91000-
                         E

                        z
                             Sw-
                                           M
                               0-          0
                                           MSP               KE            DSM             TOP
                                   BIS             FSD             CHI             OMA             STL
                                                              HSA Office


                     Figure 6-4. Total number of products (forecasts, warnings, statements) issued
                     by offices with HSA responsibility during The Great Flood of 1993. HSA IDs are
                     listed in Table 6-1.



                          law-



                          1400-



                          1200-
                        7'S 1000-
                        (L
                           sw_



                           OW-
                        E
                        z  400-

                           2W-



                              0-
                                         SwMS        QW/20         7/4    -    7/ 8          all
                                  6/1          W13          6/27         7/11         7/25          wa
                                                                Week
                                                                                   dim



























                     Figure 6-5. Total number of products (forecasts, warnings, statements) issued
                     each week by all offices with HSA responsibility during The Great Flood of 1993.
                     HSA IDs are listed in Table 6-1.



                                                                6-7




















                                                                 so-
                                                                 40-       Previous Record

                                                                 40-


                                                                 36-




                                                                 25-




                                                                 10, 1
                                                                 Jun I                  Juw@ 21                                          Jul 81                 Aug 20
                                                                                                                                                                               Fa-1

                                                                 Go-
                                                                 45-       Previous Record

                                                                 40-

                                                  IL             36-
                                                                 30-          x

                                                                 2951-


                                                                 20-


                                                                 101

                                                                 Jun I                 Jun 21                   Jul il                  Jul 31                  Aug 20




                                                                 46-       Previous Record                                                               x


                                                                 36-
                                                                 40-




                                                                 30-
                                                                                                                                           Flood StagWr
                                                                 20-



                                                                 101
                                                                                                                                              ...................     ......
                                                                 Jun I                  Jun 21                  Jul 11                   Jul 31                 Aug 20       1-61



                                         Figure 6-6. St. Louisforecast (k) and o                                     bserved (solid line) stages for.
                                         (a) I day, (b) 3 days, and (c) 7 days.


                                                                                                                6-8












             6.4.2 ANALYSIS OF SELECTED HYDROLOGIC FORECASTS FOR THE UPPER
                    AIISSISSIPPI RIVER

             The NCRFC makes routine hydrologic forecasts for 27 points along the main stem of the upper
             Mississippi River from Minneapolis, Minnesota, to Chester, Illinois. Every day, the RFC
             typically issues 3-day forecasts for each of the 27 forecast points. Every Wednesday, the RFC
             issues special long-term forecasts for 4, 5, 6, 7, 8, 9, 10, 12, 14, 21, and 28 days for 4 of the
             27 points. The long-term forecasts are generated by special request from specific end-users,
             including the U.S. Army Corps of Engineers (COE) and the navigation industry. A principal
             use of the long-term forecasts by the navigation industry is to provide an estimate of low-flow
             conditions that could occur as much as 28 days in the future and that could consequently impact
             river barge traffic. It is possible to evaluate the skill of the forecasts by comparing them with
             the observed river stages at various forecast points along the main stem of the upper Mississippi
             River.

             The NCRFC provided the survey team with forecasts and observed stage data for June, July,
             and August 1993 for many of the Mississippi River forecast points. A series of hydrographs
             was generated using the daily stage observations and the future forecasts for lead-times out to
             28 days. Figures 6-6 and 6-7 show the stage observations along with the forecasts for specific
             dates during the summer as a function of selected lead-times for St. Louis. For example,
             Figure 6-6(a) gives the observed stage and forecast stage for each day. The forecast is plotted
             in the figure on the date for which it applies, i.e., the forecasts in Figure 6-6(a) were made
             I day earlier than the date on which they are plotted. In Figure 6-6(b), the forecasts were made
             by the RFC 3 days before the date on which they are plotted. Similarly, Figure 6-6(c) shows
             the 7-day forecast comparison. The flood stage and previous flood of record are also shown on
             the hydrographs. Figure 6-7 shows similar comparisons for 14-, 21- and 28-day forecasts.

             Figures 6-6 and 6-7 graphically depict the skill associated with the forecast as a function of lead-
             time for the St. Louis forecast point. One should expect a degradation in skill as forecast lead-
             times extend into the future. A principal reason for the decreased skill with lead-time is
             associated with the fact that precipitation that falls after the forecasts are made is not accounted
             for in the forecast. Consequently, hydrologic forecasts tend to underforecast if significant,
             subsequent precipitation falls in the drainage area of the forecast point.            A systematic
             underestimate or overestimate is referred to as "bias." This systematic underestimate, or bias,
             is clearly shown in Figure 6-7 that gives hydrographs with longer forecast times. The 28-day
             hydrologic forecasts for the St. Louis forecast point (Figure 6-7(c)) tend to severely
             underestimate the observed stage because of the massive amount of precipitation that fell after
             the forecasts were made.








                                                             6-9





















                                                 so-
                                                 46-       Previous Record

                                                 40-                                                                           x
                                                                                                                   X

                                                 as-
                                                                                                    x       x
                                                 so-
                                                 Sm                                    x           Flood Stag-

                                                 Sto.               x             x



                                                  Jun                Julr@ StIl         jul III             Jul *I           Amu 20

                                                                                                                                              F-a]

                                                 go-

                                                 - -       Previous Record                      Z

                                                 40-


                                                                                                                         x     X
                                                 30-                                               Flood ft        e

                                                                                                                   X
                                                                                              x     x       x
                                                 20-
                                                                           x      x
                                                 195 -
                                                                                       x

                                                 10
                                                  Jun I              J.@ 21             Jul 11              Jul 81            AuG 20

                                                                                                                                              FbI

                                                 go-

                                                 46        Previous Record

                                                 40-



                                                 go-



                                                 20-                                                                     x
                                                                                                                   X
                                                                                                    x
                                                                                  x    X                    x
                                                                                              x
                                                 10                      1--
                                                  Jun I              Jun 21             Jul 11              Jul 31            AUG 20



                                                                                                                                              MC
                                                                                                                   x
                                                                        @x@x                       @xx@









                                  FIgure 6-7. St. Louis forecast (x) and observed (solid line) stages for:
                                  (a) 14 days, (b) 21 days, and (c) 28 days.


                                                                                          6-10

















                            5



                             0-



                             .5-



                           -10-




                        W


                           -20-






                           -30



                           -36 -
                                 1   2    a    4                            10 1'2 14 21 28
                                                         Forecast Days



                    Migure 6-8. Bias and associated error for each forecast duration at St. Louis.



             In addition to the tendency to systematically underforecast the future river stage (bias) during
             periods of extended precipitation, there is also a tendency for the forecast errors to increase in
             major flood events. Uncertainties associated with rating curve shifts, channel scour and fill,
             possible levee overtopping, and observed precipitation estimates can cause major errors in long-
             term forecasts. Figure 6-8 depicts the bias and error associated with the river forecasts for the
             St. Louis forecast point as a function of lead-time, or forecast days. The bias for the June-July
             forecast period was calculated as the average of the forecast minus observed river stage for each
             day in which there was a forecast. The error was calculated as the standard deviation of the
             forecast minus observed river stages. For example, in Figure 6-8, the bias and error for
             I forecast day at St. Louis are 0.02 and 0.50 foot, respectively. The bias and error for forecasts
             made out to 28 days increases dramatically, for a variety of reasons, to -21.67 and 10. 17 feet,
             respectively. Figure 6-8 clearly shows that forecast bias and error increase dramatically with
             forecast lead-time.


             A similar analysis was completed for the Mississippi River at Chester, Illinois, and is presented
             in Appendix F. The bias and errors of the long-term forecasts at Chester are summarized in
             Figure 6-9. The increase in both bias and forecast error with increasing forecast duration is
             generally similar to that shown for St. Louis in Figure 6-8.




                                                           6-11

















                                 5

                                  0-         +    IT
                                                       t   t





                                 _10-



                              9-20-




                                -30-


                                                                     8       10 1'2 14 @1 @9
                                                           Formast Days



                        Figure 6-9. Bias and associated error for each forecast duration at Chester,
                        Illinois.


                In addition to analyzing forecast accuracy as a function of lead-time, it is also possible to look
                at accuracy as a function of the upstream-downstream location of the forecast point in the river
                system. The NCRFC makes 3-day forecasts each day for a number of forecast points along the
                upper Mississippi River. There were eight forecast points selected for error analysis. They are,
                in downstream order, St. Paul (STP), LaCrosse (LAC), Guttenburg (GUT), Burlington (BUR),
                Dam 24 (D24), Grafton (GRF), St. Louis (STL), and Chester (CHS). Figure 6-10 gives the
                Mississippi River forecast biases and errors for the 3-day forecasts for the aforementioned
                forecast points. The biases and errors are plotted in the figure for each of the forecast days
                (I through 3) and each of the forecast points in downstream order. For example, ST? refers
                to the St. Paul bias and error and the figure shows the 1-day forecast, 2-day forecast, and 3-day
                forecasts in left-to-right order. Again, expected patterns emerge. Biases and errors increase
                with- forecast lead-times. A common pattern shows a decrease in forecast error for any fixed
                forecast lead-time in a downstream direction, e.g., ST?-LAC-GUT. This pattern, however, can
                be broken by the contribution of significant flows from tributary streams. Figure 6-10 certainly
                shows this effect from the Mississippi tributary inflows in Iowa, Illinois, and, ultimately, the
                Missouri River for the St. Louis forecast. The St. Louis 3-day forecast shows the greatest
                forecast error with a bias of -0. 13 and an error of 1. 24 feet.








                                                              6-12






Figure 6-10. Mississippi River forecast errors.


6.5	HYDROLOGIC SERVICES FOR THE MISSOURI RIVER BASIN

6.5.1 OVERVIEW OF FORECAST PRODUCTS

During The Great Flood of 1993, 211 locations within the MBRFC area of responsibility were
at levels that exceeded flood stage (47 percent of the total number of locations). Of these,
49 locations exceeded the flood of record while stages at 24 locations creasted near the flood of
record. Appendix D gives a list of locations and associated stage information for those stations
which exceeded or approached record crests in the Missouri River basin.  Figure 6-3 shows the
locationss of these points.

HSA offices in Bismarck, Sioux Falls, Omaha, Des Moines, Topeka, and St. Louis issued
thousands of hydrologic forecast and warning products to cover the flooding episode. Tables
detailing products issued by each WSFO with HSA responsibility are included in Appendix E.
Figure 6-4 and 6-5 show the distribution of these products by HSA office and over time during
The Great Flood of 1993.





6-13
















                           I



                           0-






                          -2-

                        9-3-
                        LU
                        0
                          -4-



                          -5



                          4-



                          -7-
                                             3'            6
                                                 Forecast Days


                  Figure 6-11. Bias and associated errorfor eachforecast duration at Sioux City,
                  Iowa.







                          0-















                        -20-



                        -0



                        -30 - -------
                              1       2       3              1       21     28
                                                Forecast Days



                  Figure 6-12. Bias and associated error for each forecast duration at
                  Boonville, Missouri.



                                                   6-14










             6.5.2 ANALYSIS OF SELECTED HYDROLOGIC FORECASTS FOR THE
                    AUSSOURI RIVER


             The MBRFC makes hydrologic forecasts for 2@ forecast points along the Missouri River from
             Sioux City, Iowa, down to St. Charles, Missouri. Of these 21 points, 9 have forecasts issued
             for them only when they are in flood (crest forecasts). Each day, the RFC makes routine 3-day
             forecasts for the other 12 forecast points. Additionafly, the RFC issues daily extended 4-, 5-,
             6-, and 7-day forecasts for 2 of the 12 forecast points. Each Wednesday, the RFC issues
             extended forecasts for days 4, 5, 6, 7, and 8 for 4 of the 12 forecast points, and 4-week
             extended forecasts for days 7, 14, 22, and 28 for 7 of the 12 forecast points. The long-term
             forecasts are generated by special request from specific end-users including the COE and the
             navigation industry. A principal use of the long-term forecasts by the navigation industry is to
             provide an estimate of low-flow conditions that could occur as much as 28 days in the future and
             that could consequently impact river barge traffic. It is possible to evaluate the skill of the
             forecast by comparing the forecasts with the observed river stages at various forecast points
             along the main stem of the lower Missouri River.

             Long-term forecasts (7, 14, 21, and 28 days) are issued by the MBRFC for the following seven
             forecast points: Omaha and Rulo, Nebraska; and St. Joseph, Kansas City, Boonville, Jefferson
             City, and Hermann, Missouri. The Sioux City, Iowa, forecast point and the Boonville and
             Hermann, Missouri, forecast sites were selected for ftirther analyses. The RFC issues forecasts
             for Sioux City 8 days into the future and for the Boonville and Hermann sites 7, 14, 21, and
             28 days into the future.     A series of hydrographs was generated using the daily stage
             observations and the future forecasts for each of the aforementioned forecast lead-times. Results
             for these sites, similar to those shown for St. Louis in Section 6.4.2, are presented in
             Appendix F.

             As with St. Louis, the skill associated with these forecasts drops off as forecast lead-times
             extend into the future. A principal reason for the decreased skill with lead-time is associated
             with the fact that precipitation that falls after the predictions are made is not accounted for in
             the forecast. Consequently, hydrologic forecasts tend to underforecast if significant, subsequent
             precipitation falls in the drainage area above the forecast point. This systematic underestimate
             is most clearly evident for longer forecast times.

             Figures 6-11, 6-12, and 6-13 depict the bias and error associated with the river forecasts for the
             Sioux City, Boonville, and Hermann forecast points, respectively, as a function of lead-time,
             or forecast days. Each figure gives both the bias and the associated error for each of the
             forecast durations. The bias for the June-August forecast period was calculated as the mean of
             the forecast minus observed river stage for each day in which there was a forecast. The error
             was calculated as the standard deviation of the forecast minus observed river stages. For
             example, in Figure 6-13, the bias and error for the 1-day forecast at Hermann are -0.21 and
             1.30 feet, respectively. The bias and error for forecasts made out to 28 days increases
             dramatically, for a variety of reasons, to -16.68 and 8.58 feet, respectively. Figures 6-11, 6-12,
             and 6-13 clearly show that forecast bias and error increase with forecast lead-time.


                                                            6-15

















                             5



                             0-
                            4- -T           T-

                            .lo-



                            15-








                                                     Forecast Days



                     FTgure 6-13. Bias and associated errorfor eachforecast duration at Hermann,
                     Missouri.





                            2








                            0-





                         LU












                            -4-
                                Sxc                13ON               HiM
                                          Forecast Points and Forecast Days



                     FIgure 6-14. Missouri Riverforecast errors.


                                                        6-16










             In addition to analyzing forecast accuracy as a function of lead-time, it is also possible to look
             at accuracy as a function of the upstream-downstream location of the forecast point in the river
             system. The MBRFC makes 3-day forecasts each day for a number of points along the Missouri
             River. There were three forecast points selected for error analysis. They are, in downstream
             order, Sioux City (SXC), Boonville (BON), and Hermann (HEM). Figure 6-14 gives the
             Missouri River forecast biases and errors for the 3-day forecasts for the aforementioned forecast
             points. The biases and errors are plotted in the figure for each of the forecast days (I through 3)
             and each of the forecast points in downstream order. For example, SXC refers to the Sioux City
             bias and error and and the figure shows the 1-day forecast, 2-day forecast, and 3-day forecasts
             in left-to-right order. Again, expected patterns emerge, e.g., biases and errors increase with
             forecast lead-times. The Hermann 3-day forecast shows the greatest forecast bias of -0.86 and
             error of 2.49 feet.



             6.6 HYDROLOGIC SERVICES FOR THE RED RIVER OF THE NORTH


             6.6.1 OVERVIEW OF FORECAST PRODUCTS

             During the flood, 2 of 44 locations in the Red River of the North basin exceeded the flood of
             record. Hundreds of river forecasts were issued. Appendix D gives the locations and associated
             stage information for the two stations which exceeded record crests in the Red River of the
             North. They are also shown in Figure 6-3.

             A table detailing the various forecast products issued by the WSFO Bismarck is included in
             Appendix E, and the products are included in Figures 6-4 and 6-5. There was excellent
             cooperation- between Environment Canada in Winnipeg and WSFO Bismarck in the exchange
             of crucial hydrologic information. WSO Fargo also answered hundreds of inquiries and
             provided service support at the local level.


             6.7 RIVER FORECASTS AND USE OF PREDICTED PRECIPITATION


             It is obvious from examining Figures 6-8 through 6-14 that the magnitude of the errors in the
             river forecast dramatically increase with increasing forecast lead-time. The predominant factor
             (during periods with substantial rainfall) responsible for this trend is the inability to effectively
             forecast and incorporate estimates of future precipitation into the current river forecast
             procedures. There are two main impediments: (1) the forecast system does not readily lend
             itself to the incorporation of precipitation forecast information, and (2) the current state of the
             art in precipitation forecasting produces forecasts that do not provide the level of precision
             needed by current hydrologic modeling techniques.




                                                              6-17








                As indiczted in Chapter 4, current hydrologic models used to prepare river forecasts are "lumped
                parameter" models that assume uniform precipitation over each subbasin.              Quantitative
                Precipitagon Forecasts (QPF) provide estimates of 24-hour precipitation amounts for 1 and
                2 days into the future; categorical or probabilistic forecasts/outlooks are available for longer
                lead-times. To incorporate this information into river forecasts, the area covered by each
                subbasin (both the NCRFC and the MBRFC make calculations for approximately 750 subbasins
                each) must be identified on the maps showing the QPF estimates. It is not possible to do this
                digitally within the ftamework of the existing NCRFC and MBRFC forecasting systems or with
                the current limitations in the nondigital format of the QPF products currently distributed by the
                National Meteorological Center (NMC). Efforts are currently underway at NMC, within the
                NWS Eastern Region, and at the Arkansas-Red Basin RFC (ABRFC) to develop efficient
                techniques to incorporate QPF digitally as input to RFC forecast operations.

                Even when digital QPF information becomes available to the RFCs, however, there are still
                significant, technical issues that must be overcome before QPF can be used objectively and
                quantitatively in routine forecast preparation (see Appendix B). While QPF shows a high level
                of skill on the synoptic scale', it cannot yet precisely define precipitation amounts at the
                subbasin scales needed in the current forecast system.        The case study that follows in
                Section 6.9.1 gives an indication of how inaccurate precipitation information can cause
                significant errors in the river forecasts.     Nevertheless, it is clear that, with improved
                methodology to couple QPF information effectively with advanced hydrologic modeling
                approaches, improvements can be achieved in hydrologic forecasts even with the current QPF
                skill leveRs.

                Clearly, progress will require applied research and development focused on both improving the
                accuracy at the smallest scales in the QPF forecasts, as well as innovative techniques to extract
                the maximum amount of information contained in the QPFs. At the subbasin scale, there is a
                low "signal-to-noise ratio" in current QPF forecasts. Research to reduce the "noise" (or random
                forecast error) in the QPF estimates at this scale is needed. However, aggregation of the QPF
                information to larger scales, which improves accuracies, provides promise for subsequent
                "disaggregation" when coupled with appropriate, advanced hydrologic modeling techniques. It
                is likely that probabilistic techniques, such as Extended Streamflow Prediction' methodology,
                can play an integral role in developing schemes to better use QPF. The ultimate solution will
                require the close collaboration of both those providing QPFs and the RFCs who can become one
                of the most important end-users. The Hydrometeorological Analysis and Support (HAS)
                function at the RFCs in the modernized weather service will be critical to providing an effective
                bridge between the RFCs and producers of QPFs at the WFOs and at NMC.




                   2 A synoptic scale feature is one comparable in size to a mature, winter cyclone, or 600-1,000 miles across.

                   ' Day, Gerald N., and Edward J. Vanl3largan. 1983. The use of hydrometeorological data in the NWS
                Extended Streamflow Prediction program. Fifth Conf. Hydromet., Tulsa, Oklahoma, American Meteorological
                Society.

                                                             6-18










                   F11qD1NG 6.1:. Long-term river fore-. RECONVOENDATION 6.1: Informa-
                   casts significantly underestimated stages.     tion. contained in precipitation forecasts
                   because they did not include esdmates of       'and outlooks must be factored into river
                   future precipitation.                          forecasts.
                   EMING 6.2: Current precipitation               RECOMMMATION 6.2: Manually
                   forecasts are not available in a format that   prepared precipitation forecasts and out-
                   allows easy incorporation into operational     looks must be formatted to allow for the
                   river forecast procedures.                     efficient, automated incorporation of digi-
                                                                  tal precipitation forecasts into river fore-
                                                                  cast procedures.
                   FTNDING 6.3: Precipitation forecasts           RECONSUNDATION 6,3: The NWS
                   are least accurate at the smaller scales       must focus efforts to: (1) enhance pre-
                   required by current hydrologic forecast        cipitation forecasting on the space and
                   procedures.     Nevertheless, QPF infor-       time scales needed in hydrologic models
                   mation at current skill levels contains        and (2) develop methodology that incor-
                   valuable information that could benefit        porates QPF information into advanced
                   hydrologic modeling.                           hydrologic modeling approaches.
                   FINDING 6.4; Extended Strearnflow              RECONUMTNDATION 6.4; The NWS
                   Prediction techniques provide a promising      should support research, development,
                   framework to incorporate precipitation         and operational testing to incorporate cur-
                   forecasts into the hydrologic modeling         rent QPF and other precipitation outlooks
                   and forecast system.                           into river forecasting procedures.
                   FINDING 6.5: Effective integration of          RECONUMTNDATION 6.5: An ex-
                   QPF information into hydrologic models         change program should be instituted
                   is extremely difficult and will require        whereby RFC staff visit NMC and NMC
                   close collaboration between NMC and the        staff visit various RFCs to address the
                   RFCs,                                          technical and scientific problems pre-
                                                                  venting effective use of QPF in opera-
                                                                  tional river forecast models.






              6.8 GENERAL ANALYSIS OF FORECAST AND WARNING SERVICES


              More than ten thousand forecast statements and warning products were issued by NWS field
              offices during The Great Flood of 1993. By and large, these products were well-worded and
              provided many beneficial details to the media, public, government agencies, and other
              specialized users, such as the private hydrometeorological community.              As stated in the
              introduction, a general finding is that the NWS, given the size of the event and the constraints


                                                              6-19








                of aging technologies, provided outstanding forecast and warning services. During the entire
                event, NWS employees went far beyond the call of duty to provide lifesaving and property-
                saving hydrologic products to the public and other agencies. As is the case with any event of
                this magnitude, operational problems surfaced.

                The NWS is the Federal agency charged with the responsibility for issuing weather and river
                forecasts and warnings to the public. Additionally, the NWS provides forecasts to other
                agencies, principally its major cooperators, such as the COE. The COE regulates more than
                700 major projects congressionally authorized for multiple-purpose flood control, navigation,
                hydropower, and recreation.     In addition to the major reservoir projects, the COE has
                constructed hundreds of levees across the Nation. Timely NWS forecasts and warnings of river
                stages are an essential part of the COE operation. On a regular basis, the NWS provides
                meteorological and hydrological information and forecasts to the COE, while the COE provides
                hydrological information, forecasts, and facility operations schedules to the NWS.
                The Great Flood of 1993 mandated an exchange of information between the two agencies of
                incredible magnitude and frequency.

                Although the COE uses NWS hydrologic forecasts to accomplish its basic mission in water
                control management of the Federal projects under its control, in-house hydrologic forecasts are
                prepared by the COE during flood events for internal use only. The COE forecasts are made
                for reservoir inflows and for various locations on rivers and streams where the NWS may or
                may not issue an official forecast.

                The COE and the NWS experienced excellent cooperation during the initial phases of The Great
                Flood of 1993. There were numerous reports on the timely information exchange between the
                two agencies. As the event continued, however, some philosophical differences began to
                emerge. The considerable drain on human resources and the intense media pressure associated
                with The Great Flood of 1993 highlighted the basic differences in the missions and the role of
                hydrologic forecasts within the COE and the NWS.

                The NWS issues forecasts and warnings to prevent the loss of life and property damage. Based
                on NWS forecasts, the public can take appropriate action. The COE, however, uses its reservoir
                inflow forecast for modeling and operation of its major reservoirs. The COE is also responsible
                for maintaining the safety of the public from failed or overtopped levees.          This latter
                requirement mandates a certain "safety factor" and creates a tendency for the COE to prefer
                forecasts on the "high" side to permit adequate time to raise tops of levees to prevent
                overtopping. The high estimates were in evidence in the COE's in-house forecasting during the
                last phases of The Great Flood of 1993 when many levees either failed or were overtopped.
                When comparing forecasts with the COE during the early to middle portions of The Great Flood
                of 1993, there was general agreement. The high-side forecasts became apparent, however, at
                the time of the extreme flow on the Mississippi River at St. Louis.





                                                            6-20








              A concern expressed not only by users but also by NWS meteorological forecasters is that there
              are too many types of products. Meteorologists and hydrologists occasionally had difficulty in
              deciding which products to issue. Some users were not familiar with certain products or how
              to interpret them. There were suggestions that warnings, forecasts, and other information may
              need to be repackaged. Also, there was inconsistency among certain offices, in some instances,
              on the type of product issued to cover a particular hydrometeorological situation.

              Many NWS field managers and forecasters expressed the need for objective means to evaluate
              the overall flood prediction capability of the NWS. They felt that it is essential to have a
              procedure to critique significant flood events for self-evaluation and professional development
              and to indicate the effectiveness of future enhancements to the hydrologic forecast program.
              Although NWS presently has a nationwide verification program for severe weather and other
              weather programs, there is no systematic evaluation of how well the NWS does in its national
              flood forecasting service. An effort involving the West Gulf RFC (WGRFC), other selected
              field offices, and the Office of Hydrology has led to the design of a national verification system
              for river forecasts; it has not yet been implemented.

              Several items surfaced concerning the National Oceanic and Atmospheric Administration
              (NOAA) Weather Radio (NWR). In some offices, issue dates and times were not always
              broadcast with forecasts and observed stage data. Listeners were sometimes confused about the
              latest information, especially during periods of rapidly changing stages. Gaps in NWS coverage
              are an ongoing problem. The WSFO in Sioux Falls expressed concern about not having NWR
              coverage for a large recreational area along the Missouri River.

              The lack of adequate staffing, and the effect that it may have had on providing high-quality
              forecast and warning services, was noted both at RFCs and HSA offices. Overtime use was
              extensive. Many offices had employees out for extended training, and other employees were
              on summer leave. HSA offices and RFCs reported receiving thousands of telephone calls--
              sometimes hundreds a day--from the public and the media. All offices indicated that they did
              not have enough staff to handle the extra workload. There was a period of about 2 weeks when
              the network radar at St. Louis experienced numerous outages. During this period, the staff at
              WSO Columbia was required to provide backup support from the Columbia local warning radar.
              WSO Columbia normally operates with just one person each shift. One RFC and several HSA
              offices used NWS personnel temporarily detailed from other NWS offices. This helped to
              alleviate some, but not all, of the workload problems.

              One major complaint, voiced by some emergency managers and other Federal offices, was that
              the NWS did not have a full-time, or at least routine, local presence at emergency operations
              centers that were established in several areas. One effect of this was that the NWS was not
              always given credit for its forecast and warning services. The WSFO in Des Moines and the
              NCRFC did provide representatives for extended periods on several occasions at local operations
              centers.   This was extremely beneficial to improved coordination and dissemination of
              information and to the visibility of NOAA/NWS services.



                                                              6-21









                      Another issue related to staffing is the lack of a Service Hydrologist (SH) at an HSA office.
                      Many meteorological forecasters did not feel proficient handling prolonged and major hydrologic
                      operations when an SH was not in the office or on staff. During major portions of the flood
                      event, continuing 24-hour operations at the RFCs would have been very helpful. The WSFO
                      in Topeka and Minneapolis expressed a concern that it is very difficult to maintain a high-quality
                      hydrologic program without immediate, local access to specialized expertise. The corollary is
                      that offices with SH positions stated they were indispensable in their capacity as local experts
                      who coordinated training, data flow, user interaction, media contacts, and forecast service.
                      During the flood event, the SHs were uniformly innovative and resourceful in their efforts to
                      amass valuable hydrometeorological data to support the NWS hydrologic forecast and warning
                      programs. They frequently developed and maintained local contacts necessary to ensure NWS
                      access to data sets collected by a wide variety of Federal, state, and local hydrometeorological
                      data collection networks.


                      Inaccuracy or delay in the forecast is felt sharply at the HSA offices. On some occasions, RFC
                      forecasts were outdated by the time they were received at the WSFOs. These occasions put
                      heavy demands on the skill of WSFO forecasters in handling hydrologic operations and on the
                      RFC/WSFO coordination process. Planned improvements in the forecast update cycle through
                      NWS modernization will alleviate many of these problems, but issues must also be dealt with
                      as effectively as possible now and throughout the transition to modernized operations.

FINDING 6.6: WSFOs and WSos
exhibited a wide range of philosophies in
the issuance of warnings versus state-
ments. The decision of what type of 
product to issue can become a judgement
call. To some degree, it is based on the 
geographical area and associated flood 
clomatorlogy.

RECOMMENDATION 6.6: All of-
fices should review Weather Service 
Operations Manual chapters that describe
types and content of products and adhere
to these guidelines as closely as possible.
The Regional Hydrologist should coordi-
nate with the SHs to ensure consistent use
of products (see Recommendation 6.17).

FINDING 6.7: No systematic, national
program exists to verify river forecasts.

RECOMMENDATION 6.7: WGRFC,
other participating field focal points, and 
the Office of Hyfrology have designed an
appropriate national verification system.
These offices should continue development 
and implementation of the procedures and 
software required for the system.

                                                6-22
 








                  FINDING 6.8; A growing recreational RECONEMYNDATION 6.8: The NWS
                  area along the Missouri River south of          should provide an NWR repeater in or
                  Sioux Falls often draws as many as              near the recreational area.
                  100,000 campers. There is no way to
                  provide weather information to these
                  campers.
                  FINDING 6.9: WSFOs and RFCs were                RECONUMENDATION Utz                     Each
                  inadequately staffed to manage a disaster       region should establish a personnel back-
                  of this magnitude. In the few locations         up procedure for large, protracted events.
                  where extra personnel were imported
                  from NWS offices that were not currently
                  experiencing severe hydrologic problems,
                  impacts were always positive.
                  EMING 6,10: WSO Columbia staff                  RECONEMWMATION 6,10:                   Every
                  was required to provide radar backup            effort should be made to reach acceptable
                  when the WSFO St. Louis' WSR-57                 operational availability levels for com-
                  Network Radar was down. This created            missioning WSR-88D radars as soon as
                  an additional burden on the already over-       possible.
                  worked staff.      This problem will be
                  slowly resolved when WSR-88D radars
                     gin to be commissioned.
                  FINDING 6.11: Many meteorological               RECONUVWNDATION 6,111 In the
                  forecasters did not feel proficient han-        modernized weather service, the NWS
                  dling prolonged and major hydrologic            should revisit its planned staffing allo-
                  operations when an SH was not in the            cations for SHs necessary to support
                  office or on staff. WSFO Topeka has no          those WFOs that have high levels of sig-
                  SH. Consequently, it was much more              nificant hydrologic activity.
                  difficult to maintain a high-quality hydro-
                  logic program without immediate access
                  to specialized hydrologic expertise.
                  Those offices with SH positions reported
                  them indispensable in the capacity of
                  local expert who coordinates hydrologic
                  training of office staff, data flow, user
                  interaction, media contacts, and forecast
                  services.                                     J-








                                                               6-23










                      IMING'6.12: The SHs served as the             RECOMMENDATION 6,12:
                      prirLury contacts at the WSFOs to             See Recommendation 6. 11.
                      accumulate a wide variety of data from a
                      large number of hydrometeordlogical data
                      networks supported by numerous Federal,
                      state, and local. agencies. The SHs were-
                      creative and innovative in their efforts. to
                      ensure that critical hydrometeorological
                      data were available for use in the NWS
                      hydrologic forecast and warning program.
                      FMING 6.13: Both MBRFC and                    RECONEMNDATION 6,13: RFCs
                      NCRFC provided extended coverage for          should be staffed for 24-hour coverage
                      most of the protracted flood event on a       during major flood events.
                      7-days-a-week schedule well into the
                      evening (usually until 10 or 11 p.m.).
                      Nevertheless, certain users cited an ina-
                      bility to acquire needed information
                      during hours when the RFCs were not in
                      operation, and 'many end-useTs require
                      24-hour RFC support during major flood
                      events. The NCRFC provided around-
                      the-clock coverage for 4 days during the
                      event. The MBRFC provided 24-hour
                      coverage for 2 days.
                      EMIN fi, 14: By the time some RFC             RECOMMENDATIUN ï¿½.14:.
                      forecasts were received by the WSFOs,         Whenever RFC forecasts are obviously in
                      observed river stages exceeded forecast       error, WSFO forecasters should imme-
                      stages. As the modernization process im-      diately coordinate with the supporting
                      proves the timeliness of the forecast         RFC before issuing any public product
                      cycle, improves the forecast accuracy,        based on these forecasts.
                      and reduces product transmission delays,
                      the     uency of this type of occurrence
                      will be -reduced.:.

                      FINDING 6.15.-        The NCRFC staff         RECOMME"ATION 6.15              'L   Within
                      stated that if the Planned staffing for HAS   the current budget constraints, NWS
                      forecasters in the modernized weather         Headquarters and regional offices should
                      service had been on board, the NCRFC          do everything possible to complete the
                      would have been able to analyze, in           modernized staffing levels for the RFCs.
                      greater depth, the radar rainfall estimates
                      and QPF products.




                                                                 6-24










                    FINDING 6,16:-, There were end-users                RECOMMENDATION 6.16:                       It is
                    that did Pot - have access to and/or the           'critical that the packaging and distillation of
                    expertise required to interpret the volumi-         the relevant information for water control
                    nous amounts of information contained in            and emergency management decision
                    the large number of NWS products. This              makers be improved. Some of this prob-
                    potentially can become an even greater              lem may subside as the NWS moves into
                    problem in the modernized NWS when                  modernized methods of providing infor-
                    much more site-specific information                 mation in graphical format. Until then,
                    becomes available.                                  HSA offices and RFCs should contact their
                                                                        principal governmental users to discuss and
                                                                        implement innovative packaging of infor-
                                                                        mation tailored to their local areas and

                                                                        neem.

                    EDMrz 6,17: During the flood event, a               RECONMENDATION 6.17: The SHs
                    large number of flood products were issued          should ensure that all office staffs are
                    including Flood Warnings, Flash Flood               trained on the appropriate use of product
                    Warnings, and Urban and Small Stream                types.
                    Flood Advisories. The appropriate choice
                    of product headers, and when to use them,
                    at times confused NWS meteorological
                    forecasters..

                    EMING 6,18: Extra NWS personnel                     RECONMENDATION 6,18: During
                    rotated into. the RFCs and WSPOs and                long, widespread record events of this
                    wo rked 'many hours of overtime.              The   type, essential personnel should return to
                    scheduling and rescheduling of leave or             their duty stations from long-term training
                    traiiiing for WSFO and RFC staff became             assignments.       Anyone withdrawn from
                    a factor in maintaining adequate sLaffing           long-term training under these conditions
                    levels.                                             should be rescheduled for a later date.

                    FINDING 6,19: There are ftw different               RECOMAMNDATION 6.19: The COE
                    RFCs that provide forecasts to the                  and NWS should establish a technical
                    St. Louis COE covering the upper                    worldng group consisting of personnel from
                    Mississippi River basin (NCRFC), the                all Wropriate NWS and COE offices to en-
                    Nhssoun River basin (NIBRFC), and the               sum that techniques and procedures are My
                    lower Nfississippi River basin (LMRFC).             understood and that clear points of contact
                    The St. Louis COE District Office ex-               established to clai* any potential misunder-
                    pressied concern that the forecasts from the        sMndmgs during flood events. Moreover, the
                    three NWS offices were not always inter-            NWS and COE offices gxxild implement a
                    nally consistent.                                   personnel exchange program whereby per-
                                                                        sonnel from the two agencies would work on-
                                                                        site in the other cooperating agency's office
                                                                        either part-am or full4ime,



                                                                     6-25










                                      6.9 CASE STUDEES


                                      The flooding on the Missouri and Mississippi Rivers was comprised of hundreds of smaller scale
                                      floods. These hundreds of events, which occurred in the spring and summer of 1993, are now
                                      collectively referred to as The Great Flood of 1993. It would be valuable, if time and resources
                                      permitted, to analyze in great detail most, if not all, of these events. Comprehensive analyses
                                      of all events was not possible within the scope of this report, but two cases were studied in some
                                      detail. These two cases were selected due to the hydrometeorological complexity of the events.
                                      They were also selected due to the high media visibility of the two locations during The Great
                                      Flood of 1993. The first case, the July 1993 flooding in Des Moines, Iowa, describes flooding
                                      on a relatively small basin. The second case, a very large-scale event, describes the flooding
                                      at St. Louis, Missouri, in July and August 1993. These two cases help describe the problems
                                      that can occur and the complexities that can be encountered during major floods.







                                                                      Miles                                                                                                                                                               . ...............
                                                                                                                                                                             -- - - - ---------------
                                                                                                                                                                                                             --------------- - -
                                                                                                                                                                                             ........ . ............
                                                          0              25             50

                                                                                                                                                                                ....... .... ......
                                                                                                                                                                                                                               Gutenburg


                                                                                                                                                                                -- ---- --------- ....................... .. ....................

                                                                                                                                .. . . . ........... ... -- --------
                                                                                         ...... ..... .. .
                                                                                                                                                                          terl  ;oo 0                  Inde  pendence                         Dubuque

                                                                                                                                                                                                              ............. ..       ............
                                                                                                                                                                                ..... .... ................
                                         .... . ......
                                                                                                                                                  ........ . ....... .                                                   Anamoso
                                                   ... . .......                    .. ........
                                                          ....... ... ... .....
                                                                                                                                 3oone
                                                                                        Carroll                                                                    Marshalltown
                                                       Onawo                                                   Jefferson
                                                                                                                                                                                                             Ced   a r Rapids        1,
                                                                                                                                               Ame:     :                    /0@1'    ;                i
                                                                                                                                                     s

                                                                            Denison
                                                                                                             0.
                                                                                                           i                  @ry                                                                         . . . ...........
                                                                                                 Bayard                                   Saylorvil!e Res.                      Marengo
                                                                                                                                                                                                                  Coralville R-.
                                                                                                                         Grimes 110
                                              ..... ...... ...                                                                                                                                         Iowa City       ---------------  ......i
                                                                                                                                               Des,moines
                                                                                                           Redfielcl!_                                                                  ............. ... . . .... ................
                                                                                                                        . . . .. .........


                                                                                                                                               Red Rock Res.
                                                                                                                                                                                Oskaloosa
                                                  Omaha
                                                  ............ .... ...                                                                                       ......                 --------- -........ . .--------
                                                                    -------              . ............    ........                                                                                                                   ............................

                                      ....... ....
                                                I                                                                       Osceola 0                       Chariton
                                                                                                                                                                                            .. ..... . ..........
                                                                                                                                                    ..... . ........                                        i
                                                                    ------------                                               . . ....................
                                                                                                                                                                                                               ............


                                                                                                                                                                                                                               ......... ....




                                                                                                                                                                             ...... .........
                                                                                                                                                                                                                                               ...........



                                      Figure 6-15. Map of Iowa %ith key locations and rivers.
                                                                           -----------

















                                                                                                                                               6-26









            6.9.1 CASE 1: DES MOINES, IOWA, FLOODING OF JULY 9-11,1993

            The following is a description of the July 1993 flooding in Des Moines, Iowa, and the events
            leading up to the flooding. For reference, key locations in Iowa are shown in Figure 6-15.

                     "When the Fourth of July weekend rolled around, Iowa had already endured
                     8 consecutive months of above-normal rainfall and less-than-normal sunshine and
                     15 consecutive months of major flooding. Measurable rain had fallen somewhere
                     in Iowa on 73 of the 85 days since April 10. Hundreds of thousands of acres of
                     corn had been left unplanted. Left unplanted was 8 percent of the state's intended
                     soybean crop--the slowest planting pace since such records have been kept. The
                     mighty Mississippi River was flowing through downtown Davenport on its way
                     to a record flood crest. When it seemed that nothing could get worse ... things got
                     much worse.


                     "The largest rain event of an already extremely wet year began to take form over
                     southwestern Iowa in the early morning hours of July 4. When the raindrops
                     stopped falling over eastern Iowa on the afternoon of July 5, a total of 4-8 inches
                     of rain fell across a 250-mile path from Taylor County in southwest Iowa,
                     northeastward through Osceola, Chariton, Oskaloosa, Marengo, Cedar Rapids,
                     Anamosa, and Dubuque. Major flooding ensued across much of southeastern
                     Iowa, with the greatest damage reported along Clear Creek in Johnson County.
                     The rains also pushed Coralville and Red Rock Reservoirs to record-high levels.

                     "Unbelievably, the worst was yet to come. Strong thunderstorms moved into
                     west-central Iowa before sunrise on July 8 and rapidly traversed eastward across
                     the state and into Illinois by noon. A second set of stronger thunderstorms
                     developed over west-central Iowa later in the afternoon of the 8th and slowly
                     moved along the same path as the morning storms. By the time these storms
                     weakened, around sunrise on July 9, a wide area of 3-9 inches of rain fell in an
                     uninterrupted 275-mile long band from the Nebraska border at Onawa, Iowa,
                     eastward through Denison, Carroll, Boone, Ames, Marshalltown, Waterloo,
                     Independence, and Guttenburg.

                     "Catastrophic flooding occurred along and south (downstream) of the rain area.
                     Squaw Creek, in Ames, raced to record heights which flooded Iowa State
                     University's Hilton Coliseum with 14 feet of water. Runoff into the Des Moines
                     River sent Saylorville Reservoir to a new, record-high level for the third time in
                     3 weeks. The heaviest rains were concentrated in the Raccoon River basin which
                     also sent the river to record heights. The bloated Raccoon forced thousands of
                     West Des Moines residents from their homes and put parts of the historic
                     Valley Junction business district under more than 5 feet of water. Farther
                     downstream, the river flooded the Des Moines Water Works, an installation
                     protected by dikes built 6 feet higher than the highest flood previously known.


                                                            6-27










                                         Water service was cut off to more than one-quarter million Des Moines area
                                         residents. The Raccoon River floodwaters combined with a record crest on the
                                         Des Moines River to flood numerous electrical power substations, knocidng out
                                         power to much of the Des Moines area, including all of downtown Des Moines."

                            Many of the tributaries feeding the Des Moines River, including the Raccoon River above Des Momes,
                            Iowa, were slightly above flood stage during the week of July 4, 1993, although they were Uling.
                            Moderate rain (0.2-1.2 inches) fell during the 24-hour period ending 7 am., July 8. Ibis slowed the
                            fAmg stages of larger rivers and caused within-bank rises for some of the smaller tributaries. Iben, very
                            heavy rain (up to 7.83 inches, with several unofficial reports of more than 12 inches) occurred over the
                            Race" basin and lower Des Moines River. Less widespread, moderate-to-heavy rain (1.09-3.39 inches)
                            was reported for the period ending at 7 am., July 10. As most of the precipitation reports are 24-hour
                            total cooperative observer reports, exact timing of the rainfall is uncertain. It appears, however, that
                            most of the serious, flood-producing rainfall occumed between 7 am., July 8, and 7 am., July 9. The
                            rainfall ending on the morning of the July 10 added to already high forecast crests.

Figure 6-16. Basin boundaries, streams, rivers, reservoirs, and NWS forecast points above
Des Moines, Iowa.


6-28



                                                                                                                                                         -- -- --------------- . ....... .... ...... . .. .. . .. ............










 








               In the discussion that follows, reference to Figure 6-16, showing basin boundaries and locations
               of rivers and forecast points will prove useful.

               The NWS issued river forecasts for three points in Des Moines, Iowa: on the Des Moines River
               at 2nd Avenue and SE 14th Street and on the Raccoon River at Fleur Drive. Table 6-2
               summarizes the forecasts issued. Included is the approximate rainfall for the Des Moines area
               during the July 7-11 period.

               Problems were encountered distributing the rainfall for this event. Rainfall distribution problems
               are typical and are frequently encountered when 24-hour total rainfall amounts, from a relatively
               small number of rain gages, are used to estimate rainfall distribution in both space and time for
               a series of complex, rapidly moving storms.

               In the reach of the North Raccoon above Jefferson, Iowa, the computed' runoff and the resultant
               forecast discharges for this area (Figure 6-17) were too high. This was, most likely, due to the
               inability to accurately resolve details of the rainfall distribution. Because model procedures
               route water volumes from upstream locations to points further down the river, this error in both
               magnitude and timing in the upper reaches of the Raccoon River had the additional effect of
               causing the crest to be forecast late for Fleur Drive and at Van Meter, Iowa.

               Problems determining the timing of the rainfall are obvious at Beaver Creek at Grimes, Iowa,
               (Figure 6-18) 15 miles north of Des Moines. (Although Beaver Creek at Grimes is a data point
               and not a forecast point, it is used in this case study.) At Grimes, peak discharge exceeding the
               previous record was successfully predicted; however, the forecast peak was 42 hours late. Based
               on the Beaver Creek response to the rainfall, it is possible to determine that additional rain (rain
               not accounted for by the sparse rainfall network) fell in the southern reaches of the basin. This
               appears to have caused a more rapid rise on Beaver Creek than would have occurred if the
               rainfall had been evenly distributed over the basin, as is usually assumed with current lumped
               parameter modeling procedures. This analysis is possible after the fact, with the aid of observed
               river stages. Analysis of the rainfall reports, available to the forecaster at the time of the
               forecast, does not indicate problems with the rainfall distribution analysis. The problem stems
               from forecasting with too few rainfall reports to define precisely the rainfall distribution that
               occurred. This problem also appeared at forecast points in the Raccoon basin during this event.




                    4 A major focus of this case study is the runoff and streamflow computations of the NCRFC modeling systems
               and the impact of these computed values on RFC forecasts. Figures 6-17 through 6-23 show "computed"
               hydrographs (and in some cases "routed" hydrographs) that are composites of model computations based, in all
               cases, on observed rainfall data. For example, every computed value shown with an "x" on Figure 6-17 is
               computed based on observed rainfall prior to the "x," processed through the NCRFC hydrologic analysis and
               modeling procedures. These computed values are also derived in "open-loop" fashion, i.e., model values are not
               adjusted to track observed stream conditions. This approach to the case study was adopted to simplify the exposition
               while preserving a focus on key issues. It does not capture, however, many of the forecasting complexities created
               by uncertainties in future precipitation or the forecast update cycle.

                                                                       6-29









                       35M.                          xxx
                    61 30OW -  Previous RecoM       x    xx
                    U.                             x      x
                       26M -                               x
                                                  x          x
                       20000-                                x
                       is=-                     x              XX Xx

                       10000-


                        ww-                    x

                                  -^AXX>00



                           4   5   6   7   a   9  10   11 12  13 14  15
                                              July 1993



                FIgure 6-17. North Raccoon River at Jefferson, Iowa, observed (solid line) and
                contputed (k) discharges, July 4-15, 1993.






                                                       xxx
                                                         x
                                                     x    x
                      IOWO-                         x      x
                             _FPwm7 us Reoor@d.
                                                  x          xx
                                                               xx
                                                                 x
                                               x
                                                      I Fk)od Stage F-K
                                          xxx
                                    x
                         01

                           4  5   6   7   8  9   10 11   12 13 14 15
                                             July 1993
                                                             'Xxxxx
                                               XX
                                               rx



                                                  Nxx>,
                                                               X
                                                                X
                                              )X              @x
                            >t'@@=Xxxx


                Fligure 6-18. Beaver Creek at Grimes, Iowa, observed (solid line) and computed
                (k) discharges, July 4-15, 1993.


                                             6-30









                      Table 6-2. Summary of crest forecasts for Des Moines, including precipitation observations.


                                                                                             DES MOINES RIVER

                                                                                                                     .......... ....                                                     ...................-.................
                                                                                                                             . ..... .....                                               ...... *'*'** ....... ..
                                                                                           ...................                                                                           .7110 . ........ ........
                                                                                                                                                                                         ...............................
                                      .. . ...........                                                                                                                                   ..............................................................
                                      .................                                         ..............                              ....                                         .... ........ ...
                                                                                                                                            ... ...                                      ......
                                                                                                                                            ...... ... .................                 Sk
                                                                                   ..................
                                                                                                                                                                                         SOW,
                                                                                   . ..........               . . . ......................  ... ........................                 .......
                                                                                           .......                           ...................... ...........                          ................. ............ 1-11.1 .......... ........
                                                    stage             yaw                  Stage       Forecast              Date                                                        Fo- -T Date
                                                                                                                             I                                                           rezt

                              2nd Ave.              30.2              1954                 24.2               30.0           7/9                                                         27.1 29.5-30 7/11

                              SE 14th               39.8              1965                 27.94              32.0           7/11                                                        30.6 33.0-34 7/11


                                                                                   .. . .......                                                                                          ....... .......
                                                                                           ..................    ........    ....................... ...............                     ...... ...............:
                                                                                           ........... .......
                                                               ...............
                                                                                                                                            .........................                    .. ... ..


                                                                                                                                                                                         .............
                            ........................

                                                                                                                             . ....                                                      .............. .............. ............
                                      ........ .......                                                                       ........ . ....                                             ......... ........
                                                                                                                                                                                         .................... .......................
                                                                                                                             . .....                                                     ........
                                                                                                   ............. .............                                                           ......
                                                                                                                                                                                         ............. ........................................

                                                    Stage                      Forecast                       Date                          Stage                                        Forecast

                              2nd Ave.              29.0                       29.5-30                        WIR                           31.5                                         Crested 31.6

                              SE 14th               32.2                       33.5-34                        7/H                           34.0                                         Near Crest Now






                                                                                                RACCOON RIVER
                                                                                                                             ................                                            . ..... ***-** ....... ..
                            ........ ............                                                                                                                                        .......... ......
                                                                                                                 .. . .......... ..
                                                                                                                                                                                         ............. ................
                                                               ...........                      ..... . ......... Z'
                                                                                                                                            ......................                       .... ....
                                                                                                                             ........       ....
                                                                      ....................
                                                                               ....... . . . . .                                                                                         .......
                            .........................                          ......      ....... ...... :.: ..... ...... ... ...                                                       . . ..... .
                                                                                                                                                                                         a.................... .....
                                                                                                                                                                                         .....................
                                                                                                                                                                                         d
                                                                                   ..........                                ....... ...    .......
                            ......................... .......                                                                ........................
                            . .... .... ...... ...... ...... ...... ......
                                      ..................       Old'Ri""                                                                                                                  ............ .....
                                                                                                                                                                                         :*:*.: ...........
                                                                                                                             ........       .......                                      ... ........
                                                                                                              . ................ ---        .......... .....................             ........
                                                               ..........
                            ........................... ........ I.
                                                    Stage             Year                 Stage       Forecast              Date                                                        Stage IForecast IDate

                              Fleur Dr.             19.9              1947                 15.9               21.0           7/13                                                        18.5 22.0 7/12




                                                                                                                                                                                         .......................
                                      ............                    ......                                                                                                             ...................................
                            ..............................                                      .............                                                                            . . ........ ...............
                                                    ........          ...                                     .........
                                                                                                              :.*.:,:::,:,*,:::::::I:::::::                                              ..................
                                                    ........   ........                    ........  . ....
                                                               ........................................... ... .................                                                         ......
                                                               ............
                                                                                                                             .................................. ......
                                              ................................. ......                                       ......         .....................                        .... .......
                                      ..........                                                                                                                                         ...... ..................
                                      .. ...............                       .. ...............                                                                                        .711  . .....
                            ........................................
                                                               .....................                              .... . .   .......                                                     ........
                                                                                                .. .... ....                                                                             .. ... ...-
                                      .............. . ..                                                     . ....... ...............................                                  da
                                                                                                                             ....           ..... ...................                    ........ ................
                                      .................................................................... ......                           .......

                                                    Stage                      Forecast                       Date                          Stage                                        Forecast

                              Fleur Dr.             22.6                       24-25                          7/11                          26.0                                         Near Crest






                                                                                                      RAINFALL
                                                                                                                                                                                         ............. ......... ...........
                                                    ..............................                                           ...........................
                              .............................................................................                                                                              ....... ......
                                                                                                                    ...........                                                          ................... ................................
                                                               ...... ............ ...                                                      ....... ...
                                                                                                                             ...................
                                                                                                                             .................
                                                                                                              ...                                                                        ..... . .1
                                              .. .. ..         ....... 11 .......
                                                               .. .........
                                      ................
                                      ..............           .....  ..............
                              ......................
                            ..............
                              .....................                                                   .71f @k::                                                                          .........
                                                                                                              7 -1#.' * * * * " ", * "      :;: :::*::                                   1.1 ... .......
                            ........          .... .....       ......                                                                       ..................................................................................
                                      .......:.... :'-.: ...................................
                            .................................. ..........                  ......
                                                                                                                                                                                         ...........
                                                                                                                                                                                         ..........
                                                                                                                                                                                         ..........
                                                               r                                                                                                                         ...........
                                                               AW                                                            .................. ...........
                                                                                                                                            ............
                                                                                   I                                                                                                     (AM:
                                      ........      ... ..     ...                 ...........                                              ....
                                      I............                                                                                                                                      ..... ...............
                            ............. ........... ...                          ..........                                .................
                                      ......................   .. ..............           .......            .....          ...................                                         ......-.........

                                                    3 - 7.8 in.                                         0.25 in.                                                                         0.5 - 3.0 in.
                                                                                                                                                                                         (4.5 at Slater)





                                                                                                              6-31

















                                   25=-


                              IT   20000-

                                                                                x



                                                Previous Rooord                    x
                                   10000-                               x         ""V I Flood Stage
                                     5000-                            x                    NX
                                                                      x

                                        0-       Xx

                                          4     5     a     7     8     9 1011 12131415
                                                                        July 1993



                          Figure 6-19. Middle Raccoon River at Bayard, Iowa, observed (solid line) and
                          computed (k) discharges, July 4-15, 1993.





                                   40000-


                                   35000 -                                      x

                               0   30000-
                                                                                    x
                                                                              x
                                   25M -                                            x
                                   20M -                                              x
                                                                          x     000    x
                                   110000-        Flood Stap            @x B           0- U00
                                                                                               000           x
                                    5M -                                   0                       000000OX
                                                               XXX        0                                   0
                                         0-             1100       OCIOD

                                          4     5     8     7     a     9     10    11    12    13    14     15
                                                                        July 1993
                                                                                    xx
                                                                                X>


                                                                      x


                                                                          X@
                                                                              0@0000xxxx
                                                                                          'x
                                                                                      0
                                                                                       0
                                                                        V
                                             eeft  @OCIOXXXOOOXOOI


                          Figure 6-20. South Raccoon River at Redfield, Iowa, observed (solid line),
                          computed (k), and routed (open box) discharge, July 4-15, 1993.


                                                                      6-32











             About 50 percent of the runoff at Van Meter came from the Middle Raccoon River at Bayard,
             Iowa, and the South Raccoon River at Redfield, Iowa. This reach of the river was successfully
             modeled and forecast by the NCRFC (Figures 6-19 and 6-20) rather well. The peak discharges
             at both points far exceeded flood flow levels. As shown in Figure 6-19, the peak discharge at
             Bayard was double the previous record. The remaining runoff at Van Meter came from the
             North Raccoon River above Perry, Iowa, and from contributions to the reach between Perry,
             Iowa, and the confluence of the North Raccoon River with the Middle Raccoon River at
             Van Meter, Iowa. Forecasting runoff from this reach of the Raccoon River proved particularly
             challenging for this event due to a variety of circumstances. The volume of water predicted
             from this reach of the river by RFC hydrologic modeling was reasonably accurate. The
             distribution of the rain was placed too far north and consequently resulted in a forecast timing
             problem. The main problems, however, appear to have been: (1) the absence of an established
             stage discharge relation and (2) insufficient river gage readings from the gage at Perry, Iowa,
             available to the RFC. As a result, the RFC forecaster had insufficient information and
             consequently routed too little water downstream. This undercomputation of streamflow volume
             went undetected until the crest reached Van Meter. Had the volume problem been detected
             earlier, more forecast lead-time could possibly have been provided at Van Meter and
             Fleur Drive.


             The gage on the North Raccoon River at Perry, Iowa, also proved to be a challenge for the RFC
             forecaster for two reasons. First, the gage is not rated; the stage-discharge relation is based only
             on empirical evidence. It is not based on discharge measurements taken over time and under
             various circumstances. Also, the crest at Perry exceeded the maximum stage of record.
             Discharges inferred from the reported stages were, therefore, subject to large errors. Second,
             in spite of the fact that flows at Perry had been running at near-flood stage for some time, stages
             were received by the RFC only once every 24 hours on the rising limb of the flood crest. Five
             additional stage readings, however, were made at Perry on July 9 that were never available to
             the RFC.

             Since the discharge inferred from the observed stage at Perry was "believed" by the forecaster
             (in contrast to the discharge computed by RFC models), that volume of water estimated from
             the observed stage was routed downstream to Van Meter. Figure 6-21 shows a difference of
             as much as 14,000 cfs between the computed and observed discharge (according to the
             presumably inaccurate rating) on the North Raccoon River at Perry. Figure 6-22 shows the
             observed, computed, and routed flows on the Raccoon River at Van Meter. The routed flows
             at Van Meter are based on the observed flows at Redfield (see Figure 6-20) plus the observed
             flows at Perry. If 14,000 cfs is added to the computed flows at Perry and routed to Van Meter,
             the recomputed hydrograph at Van Meter is depicted in Figure 6-23. It also clearly shows that
             distributing the rainfall too far upstream in the basin resulted in a late, flat forecast crest at
             Van Meter.





                                                            6-33

















                                46M -


                                40000-                                      >O<X
                                3&= -                                    x x     xxx
                                30000-       Previous Rooord            x            xx
                                26000-                                x
                                                                                         x
                                20000-                               x      013000 0000   XXXXX
                                Iww-                                x      0
                                                                         0               0000000000
                                10000-                                  0            Flood gia@ge
                                  5m-                                0
                                                           00000000
                                    0

                                       4    5     6    7     a     9    10   11    12    13   14   15
                                                                  July 1993


                        Fgure 6-21. North Raccoon River at Perry, Iowa, observed (solid line),
                        computed (k), and routed (open box) discharges, July 4-15, 1993.





                                60000-

                                66= -
                                50000-                                     XX
                                4WW -                                      00>0<
                                               Previous Rooord               000
                                40000-
                                35000-                                   0                    xxx
                                30000-                                                       11 X
                                25000-                            XX 0
                                2DOOO -
                                15000-                              00                Flood Stage
                                loooo-               "::40@66?65?65 OIJ
                                                               0
                                  5000-



                                       4    5     6    7     a     9    10   11    12    13   14   15
                                                                 July 1993
                                                                                         X
                                                                                      x
                                                                               77@ XX
                                          7                 70000001300-0000@oic)000000


                                                                         NXOXOMO

                                                                     x o
                                          ., 7x>-,@,,,@@xxooxo


                        Figure 6-22. Raccoon River at Van Meter, Iowa, observed (solid line), computed
                        (k), and routed (open box) discharges, July 4-15, 1993.


                                                                 6-34



                           


                    FIgure 6-23. Recomputed forecast at Van Meter, Iowa, observed (solid line),
                    computed (0k), and recomputed routed (open box), July 4-15, 1993.


            Two additional factors probably contributed to the forecast discharge at Van Meter being
            lower and later than observed: (1) the flow from Perry to Van Meter probably traveled
            faster than computed by RFC models, and (2) the rainfall in the local area between Perry
            and Van Meter, most likely, was greater than indicated by analyses available to the RFC.

            The observed volume of water at Van Meter was much larger than had previously been
            observed. The flood wave traveled faster than expected and arrived earlier than forecast
            at Van Meter. The crest at Van Meter exceeded the maximum flow of record, and the flood
            crest traveled between Van Meter and Fleur Drive in Des Moines much faster than had been
            previously observed. This resulted in a crest that was higher and arrived earlier than
            forecast at both Van Meter and Fleur Drive in Des Moines.


            Some Des Moines residents felt that releases from Panorama Reservoir on the Middle
            Raccoon River may have contributed to the problems in forecasting Van Meter. Evidence
            does not support this assumption. Panorama Reservoir is upstream of the Redfield, Iowa,
                                                                   edfield fore
            gage.   No problems were encountered with the R         f7         cast (see Figure 6-20).
                                                                                          x
                                                                                        0O0X
                                                                               \\O0X04606













                                                            6-35
 








                  It has been suggested that backwater from the Des Moines River at Des Moines contributed to
                  the flooding along the Raccoon River in Des Moines. Backwater from the Des Moines River
                  has been known for many years to be a problem at lower flows along this reach. Previous
                  backwater studies and recent fleld work by NCRFC hydrologists, however, support the view by
                  the COE that backwater had very little, if any, effect on the elevation of the crest on the
                  Raccoon River at Des Moines during the flooding on July 11, 1993.

                  The telephone line for the Limited Automatic Remote Collector (LARC) River gage at
                  Van Meter went down between 4:30 and 5 a.m. on July 10. It was back on-line about 10 p.m.,
                  July 11. On July 10 at about 4:30 a.m., the LARC was reading 22.28 feet and was rising.
                  When the phone line was repaired on July 11 at about 10 p.m., the reading was 23.20 feet and
                  was falling. The data collection platform (DCP) at the same site also became unreliable due
                  to an orifice problem that occurred after the crest. The orifize line was ripped loose early
                  Sunday morning, July 11 (between 1:30 and 1:45 a.m.). This occurred after the crest
                  (25.83 feet at 2 p.m. CDT, July 10). The DCP gage was repaired by 11 a.m., Sunday morning,
                  July 11. The absence of the LARC data, which was being automatically fed to the hydrologic
                  modeling system, caused delays both at the RFC and the Des Moines WSFO. Since the river
                  was rising faster than anyone had ever observed, the forecasters were suspicious of the DCP
                  readings. It was assumed that a problem had occurred with the gage itself. It was not until
                  several hours later that a manual observation at Van Meter confirmed the validity of the DCP
                  reading. Nonetheless, hours had been lost in updating the Van Meter and Fleur Drive forecasts
                  at a very crucial time.

                  The following general observations can be made about this event:

                         1.      An inability to determine the amount and time distribution of rain led to
                                 errors in forecasts for both the volume and the timing of flood crests.
                                 The analysis of the precipitation field was hampered by insufficient
                                 rainfall observations.


                         2.      Lack of an established stage-discharge relation (i.e., rating curve) at a key
                                 point (North Raccoon River near Perry, Iowa) made interpretation of the
                                 stage data (the conversion to streamflow) subject to error. Therefore, the
                                 computed flows for routing downstream were also subject to error.

                         3.      At Perry, Iowa, a key point upstream from Van Meter and Des Moines,
                                 24 hours elapsed between readings of 15.85 feet at 7 a.m., July 9, and a
                                 reading of 22.90 feet at 7 a.m., July 10, that were available to the RFC.
                                 Five additional stage readings, however, were made at Perry on July 9
                                 that were never available to the RFC. This occurred in spite of the fact
                                 that the 15.85 feet reading exceeded flood stage by almost 3 feet. The
                                 reading 24 hours later exceeded the previous flood of record by 0.2 foot.




                                                                 6-36









                    4.     Information from other key river gages was disrupted when they were
                           most needed (near the crest) due to telephone line outages.

                    S.     Many of the river stages exceeded their historic records.           Out of
                           necessity, the rating curves for these streams were extended by the
                           hydrologists at the RFC. Some of these rating curve extensions may not
                           have reflected the true flow, resulting in inaccurate forecasts downstream.
                           This is almost certainly true for the unrated gage at Perry.

                    6.     Lack of on-site computer capability at the NCRFC was a factor. This
                           limitation would have been even worse if RFC staff had not been
                           innovative in exploiting the office's local PC system to augment the
                           central-site computational capability.

                    7.     Current hardware and software technology at RFCs and WSFOs inhibited
                           forecasters from retrieving and managing operational data in a timely
                           manner. Forecasters at the RFCs and WSFOs were repeatedly forced to
                           manually analyze and interpret observational data. This resulted in
                           confusion about the data and delays in releasing forecasts.

                    8.     Historically, the vast majority of the data needed to drive RFC forecast
                           models is collected or transmitted every 6 hours on synoptic times. At
                           night, when human observers were sleeping, little, if any, data were
                           available. Over time, operational procedures have evolved based on these
                           data availability constraints. Today, with automation, more observational
                           data are becoming available around the clock, but operational procedures
                           have not kept up with the pace of this automation. Automated data
                           available during this event could have supported more frequent forecast
                           updates, but limitations in data analysis and modeling systems, the
                           comparatively inefficient batch-processing computer environment, and the
                           sheer magnitude of the event generally required forecasters to wait for
                           more complete data that were available at synoptic times.

                    9.     Lack of integrated, objective techniques to use QPF and satellite
                           precipitation estimates was a problem during this event.          With the
                           technology currently available, the RFC staff made excellent use of both
                           QPF and satellite precipitation estimates. Neither of these products can
                           be used directly in hydrologic models without significant analysis and
                           reprocessing (see Appendix B). Since interactive, graphics-based analysis
                           methods are not yet available at the RFC, both products are currently
                           being used only subjectively, which seriously limits their utility.





                                                           6-37









                         W.     Not enough information is contained in crest forecasts. Meteorological
                                offices and the public did not understand the science behind the adjustment
                                of the crest and the changes in the timing of the crest based on the
                                occurrence of additional rain. For specialized users, such as the COE,
                                this problem would be mitigated by sending total hydrographs as forecasts.

                         11.    Because the current implementation of RFC models makes calculations at
                                only 6-hour intervals, forecasters are prevented from effectively
                                integrating data that are observed at "intermediate" times during flood
                                situations.


                        12.     River flow travel times were overestimated at the record flows
                                experienced in this storm.



                     EMING 6,20.,             An inability to       RECO
                                                                                 ... ..... .... DON U&
                     determine accurately the amount and time       Completion of the WSR-88D network. and.
                     distribution of precipitation led to uncer-    the AWIPS program muit `bwthiue          ..to
                     tainty in forecasting both volume and          have high priority "(see,
                     timing  of flood crests. As specifically       mendations 5.14 and 5.15)..":           ... .....
                     noted   in the Des Moines, Iowa, case
                     study,  inaccurate precipitation estimates
                     are generally considered to be the greatest
                     single source of river forecast error. The                                     .. ... ...
                     NWS plans to produce precipitation esti-
                     mates which combine rain gage obser-
                     vations, WSR-88D precipitation esti-
                     mates, and satellite observations in
                     sophisticated,    multistage, multisensor
                     precipitation estimates using both inter-
                     active and automated quality-control fea-
                     tures.. These plans require the completion
                     of the WSR-88D radar net-work and the
                     on-site, interactive processing provided
                     by-AWIPS.
                     FINDING 6,21: Record flows occurred            RECONPAENDATION 6.21: Empirical
                     earlier than were forecast at many points      routing procedures should be recalibrated
                     along the Des Moines River and its tribu-      to account for maximum discharges that
                     taries due, in part, to Touting procedures     occurred during The Great Flood
                     that overestimated travel times. Current       of 1993.
                     routing procedures are based on observed
                     hydrograph data from previous floods.        1


                                                                 6-38












            6.9.2 CASE 2: MISSISSIPPI RIVER FLOOD AT ST. LOUIS

            This case study examines the problems encountered by the staffs of the NCRFC and the
            MBRFC, as well as the WSFO at St. Louis, Missouri, as they collaborated to forecast the
            Mississippi River at St. Louis. As flood-producing rainfall pummeled the Midwest during the
            summer of 1993, the staffs of these three NWS offices battled to update the flood forecasts along
            the Missouri and Mississippi Rivers during an ever-changing scenario. This effort culminated
            in the forecasts at St. Louis, Missouri, on the Mississippi River just below the confluence with
            the Missouri River. The combination of these two river basins comprise more than one-fourth
            of the area of the continental United States. All of the precipitation failing on this part of the
            United States must be accounted for in the river forecasts at St. Louis, since all of the surface
            drainage flowing out of this quarter of the Nation flows past St. Louis.

            The NWS has been criticized for the quality of forecasts on the Mississippi River at St. Louis,
            Missouri. Much of this criticism is based on a belief that the NWS did not use current stage-
            discharge relations and ignored or misused the discharge measurements provided by the
            U.S. Geological Survey (USGS) and the COE during this event. The main focus of this case
            study, therefore, is on the use of rating curves and discharge measurements by the NWS RFCs
            responsible for forecasting this flood.

            The NCRFC, in Minneapolis, Minnesota, is responsible for forecasting the Mississippi River
            basin above St. Louis except for the Missouri River basin, which is the responsibility of the
            MBRFC at Kansas City, Missouri. The St. Louis WSFO is responsible for producing flood
            watches and warnings based on RFC guidance and disseminating these products to the public for
            the areas indicated in Section 6.3. WSFO St. Louis was the focus of much of the flood
            forecasting in the Midwest during the summer of 1993 as numerous locations on both the
            Missouri and Mississippi Rivers recorded record crests time and again.

            The following description of the 1993 flooding on the Mississippi and Missouri Rivers was
            written by Jack Bums, SH, WSFO St. Louis:

                    'June and July 1993 were months of record flooding on the Missouri and
                    Mississippi Rivers. In the area served by the St. Louis WSFO, a total of
                    4a forecast points in the state of Missouri were above flood stage at some time
                    during the month of June. In July, 59 locations in Missouri were above flood
                    stage.

                    'For the state of Missouri, a total of 34 locations set river stage records: 12 on
                    the Mississippi River, 12 on the Missouri River, 5 on the Grand River in north-
                    central Missouri, 2 on the Platte River in northwestern Missouri, and the
                    remainder on the Lamine, the Marmaton, and the Moreau Rivers in west and
                    central Missouri. The end of August marked 153 consecutive days that the



                                                           6-39








                        Mississippi River at Hannibal, Louisiane, and Clarksville remained above their
                        respective flood stages.

                        "This flood broke river stage records established on the Mississippi River in April
                        1973 and on the Missouri River in July 1951. Serious flooding below the
                        confluence of the Ohio River was spared due to the low-flow levels on the
                        Ohio River aided with the use of flood control storage at the Barkley and
                        Kentucky Reservoirs [on the Cumberland and Tennessee Rivers which are major
                        tributaries to the lower Ohio River].

                        "In April, the Mississippi River had crested 6-10 feet above flood stage and, once
                        again, near the same stage levels during May. At the beginning of June, the river
                        had dropped below flood stage and was still Ming. During the second week of
                        June, the river level rose 5 feet to near flood stage and again began a very slow
                        recession. The Mississippi River, 2 weeks later, was 4 feet below flood stage at
                        St. Louis but still near flood stage at other locations from Quincy to
                        Cape Girardeau, Illinois.

                        "The month of July brought more heavy rains north of Missouri in the upper
                        Mississippi and Missouri River states of Iowa, Kansas, Nebraska, North and
                        South Dakota, and Minnesota. Rainfall amounts of 5-7 inches in 24 hours were
                        common. Hamburg, Iowa, reported nearly 10 inches of rain in 48 hours.

                        "Rains continued during the month of July and resulted in record-setting crests
                        moving down the Mississippi and Missouri Rivers. Both record crests reached
                        the confluence of the Mississippi and Missouri Rivers within days of one another.

                        "The Mississippi River stage paused for a few days at the April 1973 record
                        stages, seemingly waiting for the Missouri River water to arrive and then began
                        driving upward again--breaking levees, chasing people with their portable
                        property to higher ground, and generally causing havoc and mayhem with
                        anything in its path--to new record river stage levels.

                        "The crest, now combined as one, moved downstream through St. Louis and
                        Chester, Illinois, on a course to the southern tip of Illinois at Cairo. With the
                        Ohio River at low water levels, the Mississippi River flood crest joined with the
                        Ohio River flows and continued downstream toward Memphis but now at less
                        than bankfull levels. As the flood crest moved past Cairo, the COE curtailed
                        outflows from the Barkley and Kentucky Reservoirs to allow the crest to pass.




                    5 Note that in this case Louisiana is a citv in Missouri along the Mississippi River and not the state in which
                Hannibal is located.


                                                               6-40









                    'Beginning as early as June 7, reports of levee breaches and then levee breaks
                    became common on the Mississippi and Missouri Rivers. The effect on the
                    forecast was to delay the crests, but the water kept coming. Automatic gages
                    malfunctioned and backup observers, in many cases the COE, were called on for
                    river stage measurements. The USGS made daily, and sometimes more frequent,
                    flow measurements of the rising water up and down the rivers.

                    "Major sandbagging took place on the lower Missouri River, the River Des Peres
                    in St. Louis, the Mississippi River south of St. Louis, and many other rivers over
                    the state of Missouri. While some efforts were successful, many were not as the
                    river continued its rampage.

                    "More than 1,000 flood warnings and statements, 5 times normal, were written
                    to contend with the rising waters to inform the public that we were dealing with
                    the wrath of a river not seen since water stage records have been kept at
                    St. Louis. The 52-foot St. Louis flood wall, built to handle the volume of the
                    1844 flood, was able to keep this flood out of the city with just more than 2 feet
                    to spare.

                    "On August 1, a levee broke near Columbia, Illinois, to eventually flood
                    47,000 acres of land and inundate the towns of Valmeyer and Fults, Illinois. The
                    freed flood waters continued to flow to the south, parallel to the river,
                    approaching levees providing protection to the historic areas of Prairie du Rocher
                    and Fort de Chartres, Illinois. On August 3, the COE, using a drag shovel and
                    eventually dynamite, made several breaks through the Mississippi River levee to
                    provide a passage for the flood waters to flow back into the river. The innovative
                    plan worked, and the historic areas were saved from the flood waters.

                    'On the Missouri River, the COE has estimated that nearly 0 of the
                    700 privately built agricultural levees had been overtopped or destroyed. In late
                    June 1993, high water levels caused many locks on the upper Mississippi River
                    to close, shutting down navigation and impeding commerce. -In early July, as the
                    rainfall continued, more than 600 miles of the upper Mississippi River, 500 miles
                    of the Missouri River, and 60 miles of the Illinois River had to be closed to
                    vessel traffic. River levels remained high through all of July and much of
                    August. The ievels finally dropped enough by August 27 that all the locks in the
                    system were opened for the first time since June."


            Analysis-

            To produce the forecast for the Mississippi River at St. Louis, flows for the Missouri River
            above Hermann, Missouri, must be used. The MBRFC in Kansas City forecasts the Missouri
            River at Hermann. The flows computed by the MBRFC are transferred electronically to the


                                                          6-41









                NCRFC modeling system where they are combined with the flows from the upper Mississippi
                River to produce the forecasts for St. Louis. MBRFC forecasts for the Missouri River at
                Hermann, Missouri, are described in Section 6.5.2 and shown in Appendix F. NCRFC forecasts
                for the Mississippi River at St. Louis are described in Section 6.4.2 and shown in Figures 6-6
                and 6-7 and in Appendix F.

                The NCRFC and MBRFC use computer models to simulate the streamflow over the entire
                Missouri and Mississippi basins above St. Louis. The information available to these models is
                updated as rainfall reports are received. Computed streamflow is modified based on measured
                streamflow provided by various observers. The most frequently available information is the
                stage (water level). Observations of river flows (discharge measurements) are much more
                difficult to collect but are essential to develop rating curves that reflect true stage-discharge
                relations. RFC hydrologic models compute strearnflow that is then converted to stages to
                produce forecasts of stages. Rating curves are also used to convert observations of stages into
                flow rates. A major challenge when forecasting rivers like the Missouri and Nfississippi comes
                from problems of converting observations of stage to flow. A brief discussion of rating curves
                and how they are used by river forecasters follows.

                A rating curve is developed by making measurements over a period of time to define a relation
                between streamflow rate, or discharge, and the gage height, or stage, at the gaging site. Rating
                curves are checked periodically to ensure that the relation between the discharge and gage height
                has remained constant. Scouring of the stream bed or deposition of sediment (fill) in the stream
                can cause the rating curve to change so that the same discharge produces a different recorded
                gage height, or stage.

                "Official" rating curves are adjusted based on streamflow measurements made by the USGS,
                COE, and others. Adjustments to the official rating are made after detailed analysis by the
                office responsible for determining the official streamflow record at a given site. These official
                rating adjustments are not available in real-time because time is required to perform the detailed
                analysis of the rating.

                Current discharge measurements are made available to the RFCs to allow the RFC forecaster
                to compensate for rating shifts. Discharge measurements, due to the manner in which they must
                be made, are subject to considerable error. Therefore, official discharge measurements are
                made available only after detailed analysis is completed by the office responsible for the
                discharge measurement. Out of necessity, river forecasters analyze and adjust rating curves used
                in river forecasting in real-time. These ad ustments by the river forecaster are based on:
                (1) provisional discharge measurements provided by the offices making the discharge
                measurements and (2) experience and analysis of the feedback provided by the response of the
                RFC hydrologic models.

                This dynamic rating analysis is especially important in forecasting streams, such as the Missouri
                and Mississippi Rivers, where scour and fill provide some of the major challenges to the
                forecaster. Also, in rivers with gentle slopes, discharge for a given stage when the river is


                                                              6-42









              rising may exceed discharge for the same stage when the river is falling. This dynamic effect
              can be a factor in the Missouri River and the Mississippi River near St. Louis; adjustment
              factors must be considered in calculating discharge for rising and falling stages. At any time,
              professional judgment of the true rating at a point can and does vary. These differences of
              opinion about the official rating arise primarily from the ratings being used for different
              purposes. At NCRFC, no single hydrologist is solely responsible for determining a valid rating.
              A team effort is employed to review a rating based on the latest available information and
              experience from the hydrologist staff. Senior staff members are involved in this process.

              It is important to understand the rating analysis performed by both RFCs necessary to produce
              a successful forecast for St. Louis. Figure 6-24 shows the stage discharge relation for the
              Mississippi River at St. Louis. The rating curve is shown as a solid line. Recent discharge
              measurements made by the USGS and COE are also shown as triangles. Most of these
              meas          wem made in July 1993. A similar rating for the Missouri River at Hermann,
              Missouri, is shown in Figure 6-25. Ile rating curve for the Mississippi River at St. Louis
              (Figure 6-24) shows a variability in flow of around 15 percent at about 46 feet. USGS
              I             Wm on successive days (July 20 and 21) show a difference of discharge of
              12 percent with no change of stage. Similar variability is shown in Figure 6-25 for the rating
              for the Missouri River at Hamann. This variance required additional analysis to provide the
              best forecast possible.


                            so


                            48--
                                                       XO*-

                            46--

                                                                                    20 Jul-93
                         0-% 44.-
                                                              "Ool


                         4) 42--
                         IM
                         a
                         CO) 40 -                                      measurement
                            38--           oZI         I               rating
                            38'  z                                        --
                            34.                                          1
                              600    650  700   750   800   850   900   950   1000  1050 1100
                                                    Discharge (1000 cfs)


              Figure 6-24. Rating curve on the Mississippi River at St. Louis.
                                     El












                                                         6-43















                                3&


                                36


                                34


                                32.


                                30


                                2S.-
                              CD
                                26                                     measurement

                                24                                     rating




                                20

                                  ISO       280        380       480        580       680        780

                                                          Discharge (1000 cfs)


                Fligure 6-25. Rating curve on the Missouri River at Hermann, Missouri.



                Not all of the analysis concerning the rating curve shifts was done in-house at the NCRFC.
                Additional experts were consulted. For example, on July 26, 1993, after the second record crest
                had passed St. Louis, and before the third record crest arrived on August 1, the NCRFC
                requested assistance from the NWS Office of Hydrology's Hydrologic Research Laboratory
                (HRL), in Silver Spring, Maryland. The NCRFC asked for a second opinion concerning its
                analysis of the stage-discharge relation at St. Louis for the third crest. At that time, the NCRFC
                was computing 1,036,000 cfs flow with a stage of 48.0 feet at the crest on August 1. After
                analysis, HRL concurred with the NCRFC analysis. HRL concluded that dynamic effects would
                be very small and would not be a factor: any shift in the rating would be due to changes in
                cross-sections resulting from scour and fill. After additional rain, rating shifts, and levee
                failures, the NCRFC revised the crest forecast up to 49.7 for August 1, 1993. The observed
                crest was 49.6 feet on August 1.

                The following general observations can be made about this event:

                       1.      The suggestion that NWS RFCs did not make proper use of ratings and
                               discharge measurements is not supported by the evidence. Both MBRFC
                               and NCRFC effectively used discharge measurements to adjust their
                               ratings and forecasts in real-time.




                                                              6-44









                     2.      Discharge measurements were made very frequently during this event by
                             the USGS and COE. All of the NWS offices needing the measurements,
                             however, did not receive all of the information on the same day. Many
                             measurements were received in a haphazard way. Frequently, RFCs
                             learned of the availability of a new discharge measurement during a
                             teleconference. Also, NWS offices were not aware of the schedules for
                             the measurements, so they were not able to ascertain that they did not
                             have the latest rating. Better coordination and distribution of this vital
                             information is critical to improved flood forecasting.

                     3.      During major events, information must be exchanged in real-time among the
                             providers and users of hydrologic information, such as the NWS, COE,
                             USGS, and others. All users of this information should have the ability to
                             receive the information as quickly as possible. They should also have the
                             technology necessary to visualize the information, including discharge
                             measurements, rating curve shifts, computed flows, forecasts, precipitation
                             field analysis, soil moisture accounting values, river routings, etc.

                     4.      Levee failures caused many forecasting problems. RFCs do not have
                             good models to allow analysis of levee failures in real-time. Revision of
                             forecasts based on levee failures was very manpower intensive and caused
                             extra delays. Use of the best available technology and improved flood
                             routing models, as well as Geographic Information Systems at the RFCs,
                             would help greatly in these situations.

                     5.      Coordination between the MBRFC and NCRFC for the Missouri River
                             forecast at HeTmann, Missouri, was critical. Attempts to coordinate over
                             the telephone were partially successful, but technology that would allow
                             the Hermann forecaster at MBRFC and the St. Louis forecaster at NCRFC
                             to simultaneously visualize all of the information used in their forecasts
                             would have been of great value.

                     6.      The forecasters and users of the forecasts expressed the need for
                             additional information in river forecasts required to do proper risk
                             analysis. Forecasters compute total hydrographs for their forecast points,
                             and they have ideas concerning the variability that may occur in the
                             forecasts due to uncertainties such as levee failures and rating shifts. The
                             forecasts, however, are for single-point crest forecasts at a specific time
                             (e.g., 49.7 feet on August 1, 1993). Consideration should be given to
                             releasing total forecast hydrographs with bracketed numbers indicating the
                             level of uncertainty that could be expected for the crest.




                                                             6-45









                                                   CHAPTER 7


                               COORDINATION AND DISSEMINATION


             One of the fundamental objectives of the National Oceanic and Atmospheric Administration's
             (NOAA) National Weather Service (NWS) is to reduce the loss of life and property resulting
             from meteorological and hydrological events. This is done by combining efforts and sharing
             resources with other agencies and by ensuring that information is disseminated through the
             most effective means available.



             7.1 INTRA-AGENCY COORDINATION


             Coordination among individual Weather Service Forecast Offices (WSFO)/Weather Service
             Offices (WSO), River Forecast Centers (RFC), national centers, and regional and national
             headquarters is a vital part of the warning process. During The Great Flood of 1993, there
             was frequent coordination among all components of the NWS.             Special teleconferences
             involving the RFCs, the WSFOs, the National Meteorological Center (NMC), and the Office
             of Hydrology were held during the event to improve forecast coordination. During peak
             flooding, daily teleconferences were held in the Central Region with key NWS field offices
             in the Central Region and in the Southern Region. In this way, it was possible to keep all
             critical offices abreast of local hydrometeorological issues on a daily or more frequent basis.


             The teleconferences used standard audio-telephone links, but future, significant, long-duration
             events might profit from video teleconferencing since visual aids could help discussions that
             often center on Rocation, severity, and movement of weather systems.                      Video
             teleconferencing capabilities currently require at least a week for installation even on an
             emergency basis, though a few months is more typical.

             Service Hydrologists at the WSFOs stayed in contact with RFC hydrologists to keep the
             forecasts updated. The RFCs were staffed 24 hours a day for parts of the flood event and
             for extended hours of operation throughout the event. Service Hydrologists mentioned that
             additional RFC support and coordination would have been helpful, on occasion, during the
             time when the RFCs were closed. Additionally, Service Hydrologists noted that the use of
             different RFC product transmission formats caused them to spend extra time editing RFC
             products before issuing them. Similarly, WSFOs and WSOs expressed varying degrees of
             satisfaction with RFC services. The presence or absence of a staff Service Hydrologist,
             collocation of the WSFO/WSO and RFC, and WSFO/WSO staffing levels were important
             considerations during the peak flood event.




                                                           7-1









                RFC, WSFO, and WSO personnel routinely coordinated with various Federal, state, and
                local Emergency Operations Centers (EOC).              Coordination was typically provided by
                frequent telephone contact and also by NWS personnel on-site at specific EOCs during
                critical peAods.

                In one instance, confusion occurred for several local governments and Emergency
                Management Agencies (EMA) when internal NWS discussion products were distributed and
                appeared to represent official NWS forecasts and warnings.


                     FINDING 7.1:                The special        RECONEMW.NDATION 7.1;                    The
                     teleconferences       involving       RFCs,    logistics of handling and guidelines for
                     WSFOs, NMC,          and the Office of         the content of the teleconferences should
                     Hydrology during     the 1993 flood event      be more streamlined by regional, NMC,
                     were beneficial in several aspects, es-        Office of Meteorology, and Office of
                     pecially to RFCs that were trying to           Hydrology personnel. The information
                     consider     future    hydrometeorological     on quantitative precipitation forecast
                     conditions over their broad areas. Cer-        products conveyed from NMC should
                     tain improvements, however, in the             have concentrated on additional physical
                     management and content of the telecon-         insights into the forecasts, and their
                     ferences would have made them even             potential    accuracies,     beyond      that
                     more beneficial.                               contained in the issued products.

                     FWDING 7,2: NWS teleconferences                RECOMMENDATION 7.2: The NWS
                     did not use video.                             should investigate the feasibility and
                                                                    evaluate the potential effectiveness of
                                                                    video teleconferencing during protracted
                                                                    events such as The Great Flood of 1993.

                     FINDING 7.3:            In some cases,         RECOMAIENDATION 7.3: All RFCs
                     differences in RFC formats used to             should use the same format in trans-
                     transmit river forecasts required editing      mitting    river   forecasts    and     other
                     by WSFOs and WSOs prior to issuance            products.
                     to the public.

                     FINDNG 7A Several internal NWS                 RECOMMENDATION 7.4;                    NWS
                     products, such as the State Forecast           Headquarters should complete a review
                     Discussion     and    Excessive Rainfall       of the policy on dissemination of inter-
                     Discussion, were widely distributed to         nal forecast discussion products through
                     the media.     In some instances, these        the NOAA Family of Services.
                     technical products were taken out of
                     con   t, sensationalized, and presented
                     as official NWS forecasts by the media.




                                                                 7-2










            7.2 EXTERNAL COORDINATION

            As the NWS issues forecasts and warnings, those products are distributed in near real-time to
            a wide variety of Federal, state, and local agencies. Major cooperating agencies include the
            Federal Emergency Management Agency (FEMA), the U.S. Army Corps of Engineers
            (COE), and local and state EMAs.

            In most cases during the flood, coordination between the NWS and other agencies was good.
            During the flooding, the NWS provided daily briefings on expected weather and flood
            conditions throughout the affected areas to FEMA's EOC in Washington, DC.                 This
            information was valuable in planning for the allocation and placement of additional
            resources. The Regional Hydrologist for the Central Region briefed the COE Vicksburg
            Division on a daily basis during the critical flood period. Nonetheless, the hydrologic
            situation at St. Louis is complex. There are three NWS RFCs that provide hydrologic
            forecasts for the region of the country covered by the St. Louis COE District Office.
            Consequently, the potential for internal inconsistency or confusion among the NWS forecasts
            exists. In an effort to minimize misinterpretation and facilitate interagency communication,
            EOCs were established in Kansas City, Minneapolis, Des Moines, and St. Louis, among
            other areas. Cooperating agency personnel suggested that during the flood event, interagency
            communication could have been enhanced by on-site NWS personnel available to provide
            rapid, clear interpretation of the NWS forecasts, warnings, and products.        Xt was also
            suggested that ongoing cross-training of personnel would be very beneficial.

            In a few cases, there was a lack of coordination between local EMAs and the NWS. There
            were several instances cited by local volunteer workers and residents where levees failed and
            local EMA officials failed to contact the NWS so that timely flash flood warnings could be
            issued.


            Many Federal, state, and local agencies combined their efforts to establish EOCs in Kansas
            City, Minneapolis, Des Moines, and St. Louis. The centers were established to coordinate
            operations and disseminate information. The NWS provided a large amount of information
            to each center but had the staff resources to provide a full-time (8 hours per day), on-site,
            representative at only the Des Moines EOC continuously for a 2-week period in addition to
            other critical times during the flood event.

            COE district offices routinely provided reservoir outflow data to the RFCs and to selected
            WSFOs, but COE officials expressed concern over problems and inefficiencies caused by
            interagency computer connections and slow transfer rates experienced with antiquated NWS
            computers and communication equipment. NWS personnel spent considerable time faxing
            NWS products to COE offices so the COE would receive the information faster. The COE
            and other cooperating agencies also noted frequent difficulty in accessing RFCs and
            WSFOs/WSOs through frequently busy commercial telephone lines.



                                                         7-3










                      Despite the recognized problem areas, much satisfaction with NWS performance and support
                      was expressed by cooperating Federal, state, and local agencies. For example, the St. Louis
                      Federal Aviation Administration (FAA) office expressed great satisfaction with the
                      performance and information provided by WSFO St. Louis. That information allowed the
                      FAA to remove much of their equipment from affected areas, such as Spirit of St. Louis
                      Airport, to help prevent property loss-

                      At a natimial level, beginning in mid-July, the Meteorological Operations Division (MOD) of
                      the NMC began extensive interactions with FEMA Headquarters and the Davenport, Iowa,
                      office. MOD provided composite, 24-hour accumulated rainfall maps derived from RFC
                      data files, latest forecasts, and special narrative discussions concerning the rainfall outlooks
                      through 5 days, which was faxed to the Davenport office. MOD personnel participated in
                      the daffy briefing at the Washington FEMA office and provided a 5-7 minute presentation on                      the latest observed rainfall information and the latest forecast for the next 5 days. These
                      briefings were also seen live by the White House Chief of Staff. Each day, information was
                      assembled and faxed to the White House, FEMA Headquarters, and the Department of
                      Agriculture at 8 a.m.; to FEMA in Davenport, Iowa, at I I a.m.; to FEMA Headquarters and
                      USDA at 3 p.m., with a different package to FEMA in Davenport also at 3 p.m.

FINDING 7.5: In some communities
there appeared to be a lack of communi-
cation and coordination among different
agencies within the same commuinity and
officials of adjoining comminities.  Crit-
ical river and flood forecast information
needed to prevent damage to major facil-
ities was sometimes unavailable to all 
agencies.

RECOMMENDATION 7.5: National,
regional, and local NWS offices should
team with Federal, state, and local
agencies to coordianate more frequent
communication to ensure that needed
information is distrubuted among all 
agencies.

FINDING 7.6: County officials often 
failed to call the NWS when lecees
failed.  In many cases, the media knew
about failures before the NWS. For 
example, St. Louis emergency response
teams, such as the Red Cross and
Disaster Services, reported that some
local officials were slow to report levee
breaks to the local NWS office, which
resulted in delays in the issuance of
flash flood warnings by the NWS.

RECOMMENDATION 7.6: More
intesive efforts should be undertaken at
national, regional, and local levels to 
ensure maximum coordination and
cooperation among agencies involved in
disaster mitigation. While moderni-
zation and associated restrucuring
expansion of local staffs to include a 
Warning Coodination Meterologist at
each Weather Forecast Office should
promote better coordination, immediate
efforts are needed.

                                                 
                                                                                     7-4
 








                 FINDING 7.7 EOC operations were              RECOMMENDATION 7.7: All
                 established at several locations including   WSFOs, RFCs, and WSOs should
                 Kansas City, Minneapolis, Des Moines,        provide the highest level of       support
                 and:: St. Louis.    These centers were       possible to EOC operations within their
                 staffed by key personnel from a variety      service areas      during      emergency
                 of Federal, state, and local agencies        situations. Highly reliable communi-
                 involved in coordinating flood operations    cations between the EOC and the
                 and disseminating information. WSFO          WSFO/WSO/RFC is essential. When
                 Des Moines. and the North Central            feasible, periodic, on-site EOC support
                 RFC\WSFO Minneapolis maintained a            should be provided. Such actions would
                 periodic presence at EOCs through much       improve coordination and cooperation in
                 of the flood event. Given the limited        addition to increasing NWS visibility..
                 staffing available, it is out of the
                 question for any NWS office to provide
                 around-the-clock, on-site staffing support
                 for EOCs. Although other WSFOs and                                                 
                 RFCs provided information, they did not
                 provide on-site representation at EOCs.
                                                                                     
                 In other cases where official EOCs were
                 not established, close alliances were                                   
                 .formed with the COE, the U. S.
                                                                                    
                 GeoIogqical Survey, and local officials,                                 
                 such as in North Dakota.

                 FINDING 7.8:   The COE district       	  RECOMMENDATION 7.8.  ver the
                 offices generally provided reservoir out-    short term, the NWS and COE'sh'0'Uld
                
                 flOW'.data on a periodic basis to the      take all feasible actions to      improve
                 RFCs and to some WSFOs; however,             communications systems and data
                 the COE offices expressed concern over       exchange procedures. Over the longer
                 piblms and inefficiencies in the con-      term, the NWS and COE should ensure
                 nections and transfer rates experienced    that their respective RFC and water con-
                 with ah84ua:NW.S computers and    trol district gateway systems are opti-
                 0mmunication uit. The NWS,        mally interfaced.
                                   q pmen
                                 11ad to fax. products to the
                 
                 






















                                                           7-5
 









                     IMING 7.9: The Rock Island COE               RECONUMMNI)ATION 7.9:                   See
                     District strongly encouraged cross-          Recommendation 6.19.
                     training between COE and RFC per-
                     sonnel.    Cross-training of NWS and
                     COE personnel would substantially
                     improve intra-agency and interagency
                     operations, not only during flood events
                     when personnel may be shifted from one
                     office to another but also during routine
                     operations.
                     FINDING 7.10: More -timely and               RMONEMWENDATION 7,10:                  The
                     effective ways are needed for computer-      NWS should actively pursue the multi-
                     to-computer exchange and dissemination       ple avenues required to provide timely
                     of data and products, including graphic      products and information in appropriate
                     displays, between NWS field offices and      formats to the various communities of
                     their cooperators and end-users.             end-users (see Recommendation 7.8).
                                                                  As part of this effort, NOAA/NWS
                                                                  should improve various aspects of its
                                                                  product dissemination policies.
                     FINDING 7.11: Certain cooperating            RECONUVW.NDATION 7,11:                 The
                     agencies, especially the COE, noted fre-     NWS should install additional, private
                     quent difficulty in accessing RFCs and       telephone lines as required, if not on a
                     WSFOs through commercial telephone           permanent basis, then at least on a tem-
                     lines.                                       porary basis during severe    weather and
                                                                  flood events of this magnitude. The ad-
                                                                  ditional lines will help critical coop-
                                                                  erators coordinate with NWS offices.

                     FINDIN(i 7.12:          Arrangements to      MONEMWMATION 7.12: NMC
                     handle NMC/MOD interactions with             should establish a better level of under-
                     FEMA were accomplished largely on an         standing with other Federal agencies
                     ad hoc basis in response to the emer-        concerning what information can be pro-
                     gency situation.                             vided on an emergency basis, how it
                                                                  should be provided, and who are the'
                                                                  appropriate contact points.









                                                               7-6




FINDING 7.13: The National Flood
Insurance Program, administered by the 
FEMA through the Community Rating
System, ecsourages coordination amoung
various local and regional agencies in 
the development of flood warning plans.
Communities that qualify for
participarion in the Community Rating
System receive discounts on flood
insurance policy premiums throughout
the community.

RECOMMENDATION 7.13: The 
NWS should encourage FEMA and the 
National Flood Insurance Program to 
strengthen recognition of community
flood warning acitvities and to expand
eligible activities to include
comprehensive flood action plans.
These flood action plans are designed to 
mitigate the impactof impending
flooding, such as the identification of
flood magnitude thresholds that trigger
action (e.g., sandbagging) to protect
critical facilities and infrastructure.

           7.3 MEDIA CONTACTS


                7.3.1 NATIONAL WEATHER SERVICE SERVICES To MEDIA


                Contacts were made by the disaste survey team with 2 media outlets in Minneapolis,
                Minnesota, Des Moines, Iowa; and Kansas (City, Columbia, and St. Louis, Missouri; t1D
                evaluate NWS performance during The Great Flood of 1993. Included were metropolitan
                daily newspapers, television newsrooms and weather departments, radio station newsrooms
                and weather departments, and an Associated Press bureau office.  The contacts were
                representative of media throughout the flooded area.

       Media representatives were unanimous in their support of NWS efforts and were especially
                Complimentary of the spirit of cooperation exhibited at local NWS field offices throughout
                the flood event. There was no media criticism of NWS actions, attitudes, or cooperation
                with media representatives. Some contacts mentioned minor changes they would like to see
                in products, but those proved to be the exception and did not negatively impact the NWSs
                ability to communicate with the public through the media.

                Typical media comments are summarized:

                         Paul Douglas, Chief Meteorologist, KARE TV-11, Minneapolis: 'Overall, I
                         was very impressed mth the timeliness and information prow&4- not just on the
                         weather forecast side but on the Fiver side as well.
 








                       Jodi Chapman, Weather Reporter, WHO Radio, Des Moines: "We've been
                       very happy with the information given by the National Weather Serwice. Watches
                       and warnings were timely and accurate.... We have a very good relationship with
                       the National Weather Service. [Area ManagerlMeteorologist in Charge] John
                       Fel& is very easy to @work with. '

                       John Carlson, Reporter, Des Moines Register: 7he most important aspectfor
                       [reponers] is the ability to get an update or an interview... [WSFO Des Moines]
                       did a very goodjob in providing us with information during the flood. Weusually
                       called two or three times in the aflernoon, and they were always responsive and
                       helpfid. -

                       Brian Bracco, News Director, KMBC TV-9, Kansas City: 'I thought your guys
                       were on the ball every step of the way. I've found they bend over backward even
                       when up to their ears with forecasts.         I think [Warning Coordination
                       Meteorologist] Bill Bunting and the whole crew is highly professional It makes
                       ourjob a lot easier worlang with those guys giwng us the support they did. "

                       71m O'Neal, Reporter, St. Louis Post-Dispatch: 7he information seemed to
                       hold up pretty good, even when there were lots of updates because of the
                       continued rain. 7he numbers always seemed to be within a few inches of what
                       levels were reached. '


                       Tom 1,anorneyer, Program Director, KMOX Radio, St. Louis: NWe relied
                       heavily on [Seri4ce Hydrologist] Jack Bums for information. We had very good
                       cooperation on getting information on river stages, as well as weather and other
                       conditions Yhere was generally great cooperation by the NWY "

                       Scott Connell, Chief Meteorologist, KSDK TV-5 St. Louis: "7he WSFO was
                       very cooperative, in particular Jack Bums. Overall, the office put out excellent
                       statements included with evacuation warnings and safety rules. "


               All of the WSFOs, WSOs, and RFCs in the affected areas, as well as NWS Headquarters and
               NMC, reported higher levels of media inquiry than previously experienced. All offices received
               numerous calls from media ftom around the country, and several received calls from media in
               England, Japan, Austria, Canada, and Venezuela. At the local level, whenever possible, media
               calls on the flood were handled by the Service Hydrologists. The huge volume of calls,
               however, necessitated that all forecast staff members and technicians assist in handling media
               requests. In addition, several times per day, the MOD handled requests for interviews by
               National Public Radio. These were used extensively by many radio stations. These telephone
               interviews typically included both the latest observed information and the forecasts.



                                                             7-8









                 At various times, WSFOs, WSOs, RFCs, the Regional Hydrologist, and the Public Affairs
                 offices were mundated with numerous media queries. The sheer volume of incoming telephone
                 calls severely overtaxed the public relations capabilities of all offices involved. On one occasion
                 at the North Central RFC and on another at WSFO Des Moines, media calls were so pervasive
                 during critical severe weather and flooding incidents that the local managers sought external
                 assistance in handling the heavy media activity. The Central Region Public Affairs office
                 advised the managers to issue special media advisories stating that only emergency telephone
                 calls could be answered until threatering situations passed. This action allowed forecasters to               devote full attention to potentially severe situations and to provide accurate and timely updates.
                 Precipitation comparisons compiled from climate summary products were distributed on a daily
                 basis and proved to be greatly appreciated by the media. Weather and river forecast updates
                 were frequently requested by area media. Print media in distant locations made numerous
                 requests for basic flood and weather background information. Because of the long duration of
                 The Great Flood of 1993, additional resources to help handle public affairs functions would have
                 been helpful. Agency-wide staff shortages prevented temporary stiffing actions from being
                 taken. Additional training on interaction with the media and other external parties would have
                 been beneficial to shorthanded staffs that had been working long hours under high stress. The
                 vast area of flooding prevented implementation of a single-point (regional) contact to handle
                 media calls regarding the flood.

                 While the media were highly complimentary of NWS cooperation and the high level of
                 information provided, some did suggest ways in which timely coordination could be improved.
                 One suggestion to help broadcasters meet public demand for early, daily information was for
                 better coordination of river stage information and flood forecast product issuance with broadcast
                 schedules. This wouid allow radio and television meteorologists to receive such products with
                 sufficient time to tailor them for specific audiences.

FINDING 7.14: The magnitude of The
Great Flood of 1993 made the central
United States the focus of national and 
worldwide attention, which led to intense
media interest.  The volume of telephone
media queries for critical and noncritical
flood information overtaxed NWS staff at
national, regional, and local levels. All
Offices in the affected areas were inun-
dated with requests to provide interviews,
material , and information to the media
and NWS Headquaters for input to con-
gressional briefings and for other program
exercises.

RECOMMENDATION 7.14: Because
of the long duration of The Great Flood
of 1993, additional resources to help
handle public affairs functions should have
been available. A plan for activation of
additional publuc affairs personnel support
for such events should be developed.
Additional trining on procedures for 
interaction with the media and other
external parties should be provided for 
some offices.

                                                                7-9
 



FINDING 7.15: Some media members
suggested that better coordination of the 
NWS product release times to coincide
with the broadcast schedules would have
allowed for more timely and effective
broadcast of NWS products to the public.

RECOMMENDATION 7.15: The NWS
should continew all possible acceleration
of modernization and associated
restructuring components including
lengthened standard hours of operation,
staff augmentation, and implementation of
new technologies at RFCs, which should 
allow initial morning river forecasts to be 
issued in the 7 a.m. time frame.

                       

                      7.3.2 OTHER AGENCY MEDIA CONTACT'S


                      Much of the flood information to the media was provided by personnel from other
                      government agencies and private services. The COE; state, county, and city EMAs; FEMA;
                      river authorities; and other agencies were in frequent contact with the media. The large
                      number of "officials" providing information in interviews at times caused some public
                      confusion because of the different data sets and terminology used. The private agencies
                      generally deferred questions on flood forecasts and left that up to NWS personnel.

                      The overall media attitude appears to have been one of cooperation with both NWS and
                      private sources. One reporter noted that because his newspaper did not subscribe to the
                      NOAA Weather Wire Service (NWWS), it forced reporters to contact the NWS more
                      frequently than would have been necessary with NWWS to provide information.


                      7.4 DIRECT USER SERVICES


                      The survey team found substantial differences in the levels of public interaction and direct
                      individual service provided by the various NWS offices in the flood-affected areas. These
                      differences were caused largely by differences in staffing, geography, and other local
                      differences, as well as the availability of river authorities and emergency preparedness
                      agencies to deal with the public. Obviously, user satisfaction was greatest in those instances
                      where the NWS had the resources to provide greater personal contact.

                      Information provided by the NWWS was valuable; in some instances, however, local
                      government agencies said they would like to have the service but cannot afford its high cost.
                      Currently, many local EMAs receive weather warnings through their state crime networks.
                      Weather warnings, however, are not given high priority on these systems. Sometimes they
                      are received long after the warning has been issued. These networks tend not to carry
                      statements or other information that would be very useful in the operations of EMAs. In the
                      interest of public safety, many NWS offices spent valuable time faxing crucial information



                                                                                    7-10
 









                 that is available on NWWS but not through state crime information networks to various
                 county EMAs.

                 NOAA Weather Radio (NWR) provided a useful source of direct contact between the NWS
                 and users. Virtually all radio and television stations contacted used NWR as a backup
                 information source to NWS. The effectiveness of NWR to the public was limited. Even
                 though NWR broadcasts were available in almost all areas impacted by the flooding, much of
                 the public remains unaware of its existence. An occasional problem was discovered in areas
                 where NWR was used by the public. Users noted that some flood forecasts broadcast on
                 NWR were out of date and that some river forecasts did not specify the time of observed
                 stages.

                 Many NWE offices faxed graphicz to state ZMAs. This included 24-hour rainfall and
                 quantitative precipitation forecasts for the 24- and 48-hour periods. Many EMAs stated that
                 this information proved very valuable. They would like to see a system developed by which
                 they could receive graphical guidance on a regulaz basis. They also expressed an interest in
                 receiving continuous radar imagery. Some county EMA directors said they had investigated
                 the possibility of subscribing to the NEXRAD Enformation Dissemination System (NIDS),
                 through which radar imagery will be provided in the modernized NWS, but found it                                              too
                 expensive for small county budgets.

FINDING 7.16: In many instances,
local communities and municipalitits are
not making effective use of the NWWS.
In some cases, agencies were not even
aware of the existence of the NWWS.
Many communities did not use NWWS
because of: (a) the high cost of the 
service, (b) the need for tailored forecast
information, and (c) the high volume of 
products disseminated.

RECOMMENDATION 7.16: The 
NOAA/NWS costs, study
the ramifications of not lowering
NWWS costs, and redouble efforts to 
make other agencies aware of NWWS
availability and features. Additional
sources of product distribution, such as
Internet, should be explored.  Also,
NOAA should encourage FEMA to pro-
vide support and assistance to communi-
ties so they can subscribe to the 
NWWS.

FINDING 7.17: Most of the public is
unaware of the availability of NWR,
even though it broadcasts across most of 
the United States.

RECOMMENDATION 7.17: The 
NOAA/NWS must make a substantially
greater effort to educate the public on
the availability of NWR and of the life-
savings service it provides.

                                                                          7-11
 









                      FINDING 7,18: Broadcasts of flood              RECOMMENDATION ML-                       The
                      forecasts on NWR were sometimes not            current NWR policy of broadcasting the
                      up to date. Some river products did not        time and date for specific observations
                      specify the time of the observed stage.        should be adhered to. See Finding and
                      It is especially critical during epic          Recommendation 5.36 pertaining to
                      weather and flood events, such as The          more frequent forecasts and updates.
                      Great Flood of 1993, that personnel at
                      NWS offices take extra steps to ensure
                      that information broadcast on NWR is
                      updated frequently so that NWR
                      listeners    receive    only    the    latest
                      information.

                      FINDING 7.19: Weather radar imagery            RECONUVEENDATION 7,19:                  Ile
                      and graphic products were not available        NWS should determine whether current
                      to most Federal, state, and local              and planned provisions for dissemination
                      agencies.                                      of weather radar products are adequate
                                                                     to meet the needs of NOAA cooperators
                                                                     throughout the Nation.
                      FITSMING 7.20: Some county EMAs                RECONEVIENDATION 7.20:                  The
                      stated that the cost of becoming a NIDS        Federal Government should ensure that
                      subscriber exceeds financial resources of      the NIDS providers continue to offer
                      many county EMA offices, especially in         lower cost capability for dim counties.
                      counties with small populations.               The local WSFOs should also continue
                                                                     emergency coordination with county
                                                                     EMAs.




























                                                                  7-12









                                                     CHAPTER 8


                                PREPAREDNESS AND USER RESPONSE





             8.1 INTRODUCTION


             The National Weather Service (NWS) and state and local governments and communities work
             together to prepare for and deal with the consequences of meteorological and hydrological
             disasters. The agency maintains a warning and preparedness program to coordinate and expand
             this effort. There are two important elements in preparing the public to minimize or eliminate
             the weather's impact. First, information about the event must be communicated or disseminated
             to those at risk. Second, dissemination of information that encourages the public to respond
             appropriately is critical. For the communication process to succeed, it is critical for officials
             to notify the public so those at risk can take the proper steps to protect themselves and their
             property.



             8.2 INTERNAL PREPAREDNESS


             The effectiveness of NWS information is only as good as the proficiency of the NWS staff to
             monitor weather conditions, detect severe storms, evaluate conditions, and issue appropriate
             forecasts or warnings. Realistic drills for aIR operations personnel should be a part of every
             office's internal preparedness program. Drills should include all phases of office emergency
             operations for all events that threaten the area of responsibility.

             Internal drills are conducted on floods and flash floods by all NWS Central Region Forecast
             offices. The offices are routinely required to ensure that critical maps, data sets, and basin
             overlays are available that accurately depict the hydrologic information in their respective areas
             of interest. In spite of these efforts, some offices were still hampered by not having suitable
             base maps to appropriately carry out their functions. An important tool for hydrologic
             forecasters is a current, updated set of topographic maps depicting the current geographic
             information in the forecast offices' areas of responsibility.

             NWS offices are staffed for most weather situations, but the severity and length of this flood
             made it difficult for personnel to handle the additional workload. During the flood event,
             19 NWS hydrologists were reassigned to provide assistance at Weather Service Forecast Offices
             (WSFO) and River Forecast Centers (RFC) in affected areas. There is, however, no officia.1
             national or regional policy for reassignment during long-term, weather-related emergencies. In
             some cases, NWS personnel were at training during the event; there is no official policy for



                                                            8-2










                      recalling employees back to their duty stations during extreme weather emergencies like
                      The Great Flood of 1993.

FINDING 8.1: Some basin and 
topographic maps at WSOs were outdated
or missing.

RECOMMENDATION 8.1: Offices in 
need of topographic maps should procure
them directly from the U.S. Geological
Survey. NWS Headquaters and regional
offices should establish procedures to 
generate and update WSFO basin maps.

                 8.3 EXTERNAL PREPAREDNESS


                      It is vita that NWS personnel share knowledge of dissemination systems, procedures,
                      capabilities, and response requirements with the media; Federal, state, and local agencies; and
                      the general public involved in the total warning process.

                      As part of this effort, NWS field offices are responsible for managing warning preparedness
                      programs in their areas with one person in each WSFO acting as the key contact with emergency
                      management officials, the media, the public, and other agencies. Of the nine WSFOs affected
                      by the flood, three have Warning and Coordination Meteorologists (WCM), and six have
                      Warning and Preparedness Meteorologists (WPM).

                      WPMs/WCMs develop extensive networks of trained spotters to report severe weather in their
                      areas. Audio-visual and printed materials are used to train these spotters. In the nine-state
                      region hardest hit by the flood (Illinois, Iowa, Kansas, Minnesota, Missouri, Nebraska,
                      North Dakota, South Dakota, and Wisconsin) dense networks of nearly 18,000 weather spotters
                      exist. These spotter networks maintained effective coordination efforts throughout the flood
                      event. Few of these spotters, however, were recruited or trained to report floods. In fact, few
                      have rain gages. While the spotter networks were able to continue operations, except in
                      instances where spotters were personally impacted by the flood, additional training and
                      participation in precipitation and flood reporting could have made their contributions even more
                      effective and significant.

                      Benefits of community or statewide drills with Federal, state, and local agencies to improve
                      knowledge of weather hazards and to evaluate current communications systems and procedures
                      are immeasurable. Throughout the Midwest, state drills on severe weather preparedness are
                      conducted at least once a year.

                      An effective warning preparedness program depends on frequent contact and coordination with
                      Emergency Management Agencies (EMA). NWS offices may need to strengthen coordination
                      with local and state EMAs. During the flood itself, the quality of coordination among the NWS


                                                                                      8-2
 









                 and EMAs varied. In some locations, EMA personnel did not effectively communicate vital
                 river information to the NWS, leading to delays in the issuance of flood and flash flood
                 warnings. In other locations, working relationships among these entities was excellent and led
                 to faster dissemination of warnings.

                 County emergency officials expressed general satisfaction with NWS services and coordination.
                 Some local EMAs noted occasional confusion caused by different statements made by the NWS
                 and the U.S. Army Corps of Engineers (COE). Because COE representatives were often on-site
                 at Emergency Operation Centers (EOC), levees, and flood-threatened areas, local authorities
                 often used information on stage levels and expected crests that was provided by the COE rather
                 than using NWS statements and forecasts levels. On-site NWS representation, especially at
                 EOCs, would have improved coordination efforts, helped alleviate confusing or contradictory
                 information, and made the public more aware of the active NWS involvement.

                 NWS access to flood operation manuals for emergency management and water facility
                 departments in major municipalities could have improved the response to forecast and warnings.
                 These manuals provide information for decision makers based on river stages.

                 The size and sophistication of Rocal EMAs, along with the availability of state-of-the-art
                 communications equipment, also had an impact on effective cooperation and coordination
                 between the NWS and the EMAs. Obviously, computer-equipped offices were better prepared
                 to process and act on information provided by the NWS. Most up-to-date EMAs were located
                 in large cities, although there were exceptions. For example, St. Charles County, Missouri,
                 (located adjacent to St. Louis) has a relatively small population but maintains a modern EOC that
                 employs a computer-based Emergency Information System that provides EMA officials with
                 critical hydrometeorological information. Redundant, advanced communications systems connect
                 the EOC with other emergency agencies and the NWS. Coordination efforts between
                 St. Charles County EMA and the NWS were excellent through the course of the flood. EMA
                 officials noted that St. Charles County had made a commitment to implement the best emergency
                 operations system and equipment available. Private sector funding was solicited and secured to
                 help the county supplement its emergency operations budget. Similar efforts could be beneficial
                 to emergency managers in other areas.

FINDING 8.2: County emergency
management officials expressed general
satisfaction with NWS services. They
sometimes noted a difference between
statements issued by the COE and the 
NWS. Often, since the COE had a
physical presence at the flood site, local
authorities used information provided by 
the COE.

RECOMMENDATION 8.2: The NWS
should imporve coordination with county
and state EMAs and EOCs through peri-
odic review of action plans, particiation
in mock distater exercises, and other
planning approches. Improved real-time
coordianation between the NWS and EOCs
is addressed in Recommendation 7.7.

                                                                             8-3
 



FINDING 8.3: Most public works and 
emergency management departments in 
major municipalities have flood operation
manuals.  These manuals contain infor-
mation of critical decision points for
which various actions are initiated once
critical river stages are reached (or fore-
cast). These manuals were not always
available in some NWS field offices.

RECOMMENDATION 8.3: The NWS
should obtain the flood operation manu-
als, as well as maintain and improve rela-
tionships with respective public works
agencies and EMAs. Relevant infor-
mation from these manuals should be in-
corporated in the Service Hydrologist
Information Management System.

FINDIGN 8.4: St. Charles County, 
Missour, which has a moderate popu-
lation, maintains modern EOC oper-
ating a state-of-the-art Emergency Infor-
mation System. Private sector funding
Helped to build an advanced EOC that 
uses NWS warnings and forecast to 
better serve the public.

RECOMMENDATION 8.4: Federal,
state, and local agencies are encourged
to coordinate and to expand this typr of 
modernized emergency system nation-
wide. This would improve dissemination
and increase efficiency of providing NWS
information to the public.

                                   
                 8.4 PUBLIC AWARENESS OF AND RESPONSE TO NATIONAL WEATHER
                        SERVICE RIVER FORECAST SERVICES


                 In most cases, flood forecasts were provided with sufficient lead-time to allow residents to
                 prepare for the event, although greater lead-time clearly would have contributed to improved
                 mitigation actions in many instances. Statements, watches, and warnings provided "call-to-
                 action" information instructing the public on the proper safety procedures.

                 Extensive media coverage of the event heightened public awareness of the severity and danger
                 of The Great Flood of 1993. While general public awareness was high, there was some
                 confusion among the media and the public as to the specific meaning of NWS flood statements,
                 watches, warnings, and forecasts. Such confusion could prove detrimental to future effectiveness
                 of NWS warning efforts.

                 Dimemination of flood forecasts was generally rated good to excellent by those receiving the
                 information. Virtually all individuals and media outlets interviewed by the survey team concerning
                 flooding of the Nississippi and issoun Rivers and their tributaries were pleased with the products
                 provided by the NWS. Much of the public was unaware that forecasts and statements originated
                 from the NWS, crediting them rather to the COE, the electronic media, etc.
                                                                                 







                                                                                          8-4
 









                  The numerous NWS precipitation reports, flash flood and flood advisories, and river forecasts
                  undoubtedly saved lives and prevented tens of millions of dollars in damages as business owners,
                  farmers, homeowners, and others responded in a timely fashion to reduce losses by
                  floodproofing property, fortifying levees, and moving equipment, livestock, and machinery.
                  Unfortunately, the survey team was not able to provide a credible estimate of damages averted
                  because of NWS forecasts. A research project to investigate the cost savings resulting from the
                  NWS forecasts and warnings associated with The Great Flood of 1993 could benefit the NWS
                  and be of interest to the disaster preparedness community.

                  It was disclosed that a few agricultural users of NWS flood forecasts and river stage information
                  tended to discount the accuracy of those products. Although forecast river stage levels were
                  reasonably accurate, one agricultural user in St. Charles County stated that he and others
                  mistakenly thought that stage forecasts were exaggerated. This perception sometimes resulted
                  in less-than-adequate protective measures being taken by some agricultural users. A strong,
                  post-flood effort by NWS offices to work with local media to inform the public of the
                  complexities involved in predicting and following the crests of such large floods could result in
                  positive public reaction and increased awareness of NWS efforts and responsibilities.

FINDING 8.5: The media and the 
public do not fully understand hydrologic
terminology, procedures, and forecast
products.

RECOMMENDATION 8.5: The NWS
and NOAA Public Affairs, at all levels,
should develop a public education pro-
gram to increase awareness of and under-
standing about the hydrology program by 
using brochures, news releases, fact
sheets, and other backgroung materials,
along with increased interaction with the 
media.

                                                                           8-5
 








                                                    CHAPTER 9


                     SUNMARY OF FINDINGS AND RECONMONDATIONS




             9.1 GENERAL DESCRIPnON OF TIIE EVENT AND ITS IMPACT
                  (CHAPTER 1)

             No findings and recommendations.


             9.2 MAJOR LESSONS LEARNED AND OPPORTUNITIES FOR THE
                              (CHAPTER 2)

             FINDING 2.1; The meteorological, climatological, hydrological, and hydraulic conditions
             that converged to produce The Great Flood of 1993 were unique in many aspects. Initial
             assessments of the economic impact of The Great Flood of 1993 indicate that losses will
             range between $15-20 billion. This is the single, greatest flood loss in the Nation's history
             and rivals Hurricane Andrew in overall losses. The extent of social disruption is beyond
             measure.


             RECOND4ENDATION 2.1:               The National Oceanic and Atmospheric Administration
             (NOAA) should work closely with its many collaborators to encourage ftirther investigations
             into the various aspects of The Great Flood of 1993. Much is left to be learned. Additional
             scientific studies should be conducted to provide important insights on how to further
             minimize losses from future disastrous floods. -



             FTNDING 2.2; There were major benefits, as well as some problems, related to the many
             uses of National Weather Service (NWS) flood forecasts. The disaster survey team was
             unable to assess comprehensively the impact of the hydrologic forecasts and products due to
             the limited duration of the survey. Because of the large socioeconomic impacts of this
             historic flood event and the potential mitigating effects of higher-quality hydrologic forecasts,
             a more detailed post-flood impact analysis would be invaluable.

             RECONEMENDATION 2,2: NOAA should support a comprehensive, external study to
             evaluate and quantify the benefits derived from hydrologic forecasts. This study should take
             maximum advantage of the lessons learned during The Great Flood of 1993.





                                                           9-1









                 FINDM 2,3: A large suite of software and hydrologic procedures, especially National
                 Weather Service River Forecast System (NWSRFS), is critical to current River Forecast Center
                 (RFC) operations and even more critical to future operations. There is significant concern about
                 maintaining the required depth of expertise and support at both the field and headquarters levels
                 required for this complex system.

                 REMARIEND-A= 2.3: The NWS Office of Hydrology should systematically evaluate the
                 operatiorW readiness of NWSRFS and other software used in hydrologic forecasting.


                 FINDM ZA: RFCs do not routinely store river and flood forecast information and products in
                 digital    . Similarly, the National Meteorological Center (NMC) does not routinely archive
                 quantitative precipitation f6recast (QPF) products in digital form.     These data and forecast
                 products are critical for post-event analyses, research and development, model calibration,
                 extended streamflow prediction and simulation requirements, climatological studies, and forecast
                 verification.


                 RECONEMU*4DATION 2.4: Routine procedures must be implemented at the NMC and the
                 RFCs, as part of modernized system capabilities, to archive all data and products in digital
                 format that are pertinent to ongoing developmental, operational, and verification programs.


                 FINDING- 2.5: Although only mine Weather Surveillance Radars 1988 Doppler (WSR-88D) had
                 been installed for areas covering parts of the flooded states, several instances illustrated the
                 revolutionary impact the WSR-88D will have on flood and flash flood forecasts and warnings.
                 One especially noteworthy example occurred on July 18, 1993, when the Chicago WSR-88D
                 accurately mapped a 4.0- to 6.6-inch rainfall core that led to a warning being issued prior to
                 significant flooding. Greater lead-time could have been provided, however, if the flash flood
                 potential (FFP) algorithm had been implemented in the WSR-88D Radar Product Generator.

                 RECONEMMMATION 2.5: Every effort must be made to keep the NWS modernization on
                 schedule and to accelerate its implementation and operational support. It is imperative that the
                 change-marWernent process for the WSR-88D program be streamlined so that it does not take a
                 year, or longer in some cases, to get critical software changes or enhancements implemented--the
                 FFP algorithm being a case in point. Furthermore, Advanced Weather Interactive Processing
                 System (AWIPS)-type capabilities must be installed at the RFCs to use effectively WSR-88D
                 rainfall estimates for numerical input to hydrologic models.


                 FINDING 2.6: Weather Service Forecast Offices (WSFO) in the affected area have headwater
                 tables for selected basins that are used to provide flash flood guidance. Nonetheless, many
                 offices felt a need for more advanced, local river forecast procedures to produce headwater
                 forecasts systematically or to update RFC forecasts. This was especially critical in situations in
                 small river basins where hydrometeorological conditions changed rapidly.


                                                               9-2









            RECONEMWNDATION 2.6.0 NWS national and regional headquarters, NWS field offices,
            and the Forecast Systems Laboratory of the Office of Oceanic and Atmospheric Research
            should accelerate development of the Weather Forecast Office (WFO) Hydrometeorological
            Forecast and Warning Subsystem for incorporation into the AWIPS application software
            suite.



            FINDING 2.7: The modernized NWS has a critical need for professional personnel trained
            in both hydrology and meteorology and has developed qualification criteria for these new
            hydrometeorologists.

            RECOMMENDATION 2.7; NWS and NOAA managers and personnel offices must ensure
            that personnel, recruitment, qualifications, and promotion processes appropriately reflect
            requirements for hydrometeorologists.


            FINDING 2.8; The effectiveness of the NWS's river forecasting services critically depends
            on other Federal, state, and local agencies for (1) information used in the forecasting
            process, (2) the dissemination of forecasts and warnings, and (3) ensuring that the public take
            actions necessary to prevent loss of life and to mitigate damage.

            RECOMACENDATION 2.8: The NWS needs to maintain and strengthen cooperative
            arrangements with current partners and to seek additional opportunities to work with
            interested parties to ensure the protection of life and property.


            FINDING 2,2; Currently, RFCs typically issue stage forecasts for only 1, 2, and 3 days
            into the future at most forecast points and crest forecasts out to about I week for a few
            selected forecast points. Federal, state, and local groups indicated a need for increased lead-
            times for hydrologic forecasts. Many expressed the need for a range of forecast stages with
            associated probabilities of occurrence.

            RECONEMWE"ATION 2.9:               The Federal Government should press forward with
            implementation of the Water Resources Forecasting System (WARFS) which will provide the
            required capabilities.


            FPiDING 2.10;       QPFs are not being used directly, objectively, and systematically in
            hydrologic modeling in Central Region RFCs. In addition, not all WSFOs have appropriate
            software and computer equipment to issue QPF forecasts for the RFCs.              Many users
            understand that QPF products have inherent uncertainties. Nonetheless, many expressed a
            need for probabilistic river forecasts that incorporate QPFs.




                                                          9-3









                RECQhnffMATION 2.10; If Recommendations 2.6 and 2.9 are implemented, they will
                also satisfy the requirements to include QPF information in hydrologic forecasts. The NWS
                should continue to support scientific efforts aimed at producing probabilistic QPFs at WSFOs
                and Weather Service Offices (WSO) through support of training and research initiatives.


                FINDING 2,11: The extensive flooding of 1993 has created large regions with above-
                normal soil moisture conditions across the Upper Midwest. Consequently, fall rains and
                spring snowmelt in 1994 may substantially elevate the potential for flooding. There is a need
                for immediate and extended assessments of flood potential persisting through at least the
                spring of 1994. Special hydroclimatological assessments done monthly would be valuable.

                RECONUOENDATION 2,11: The NWS Office of Hydrology and the Central Region
                should provide early and ongoing assessments of potential spring flooding in 1994 in the
                areas affected by The Great Flood of 1993. This effort should draw on early experiences
                from the NWS modernization and pilot WARFS activities wherever possible. Additionally,
                information and data from the Midwest Climate Center and NMC's Climate Analysis Center
                should be used to support an ongoing assessment of soil moisture conditions and potential
                future flooding across the Upper Midwest. Moreover, the NWS should support an enhanced
                airborne soil moisture data collection program during the late fall of 1993 and a
                comprehensive airborne snow water equivalent data collection program during the winter of
                1993-94 over the region affected by The Great Flood of 1993.


                9.3 HYDROMETEOROLOGICAL SETTING (CHAPTER 3)

                FINDING 3. 1:     The duration and magnitude of The Great Flood of 1993, as well as its
                antecedent conditions, strongly support the premise that this event was a significant climate
                variation rather than simply a sequence of meteorological incidents.

                RECONEMENDATION 3.1: Additional analyses of this situation, by both research and
                operational communities inside and outside of the NWS, should be encouraged. The Great
                Flood of 1993 should be considered as a climate time-scale variation or anomaly, which may
                be attributable to a combination of atmospheric, oceanic, and land factors, such as
                circulation, temperature, soil moisture, and their complex interactions.


                FE14DING 3.2:     The soil moisture models for the Midwest, operated by the Midwestern
                Climate Center, can provide a constantly updated assessment of regional soil moisture
                conditions and a probability of future soil moisture potential critical to an evaluation of
                longer-term flood potential. In addition, the High Plains and Northeast Climate Centers also
                provide soil moisture information.



                                                            9-4









            RECOMMENDATION 3.2: The NWS and, in particular, the RFCs should obtain soil
            moisture information from the Regional Climate Centers to enhance near real-time
            monitoring of hydrologic conditions and to guide preparation of flood potential outlooks.
            The remaining Regional Climate Centers should be encouraged to consider providing soil
            moisture information.



            9.4 HYDROLOGIC AND HYDRAULIC FORECAST METHODOLOGY
                 (CHAPTER 4)

            FINDING 4,1: Accurate river gage and other information reported on NWS Form E-19 is
            critical to hydrologic forecast techniques and procedures. The severe flooding of both the
            Mississippi and Missouri Rivers and their tributaries will necessitate updating much existing
            E-19 information.


            RECONIMEN-DATION 4.1;           The Regional Hydrologist, Area Managers, Hydrologists in
            Charge, and Service Hydrologists (SH) should coordinate with the U.S. Army Corps of
            Engineers (COE), the U.S. Geological Survey (USGS), and other agencies to research,
            verify, and update river stage levels and other information required by Form E-19 at all
            affected reporting points.


            FDWING 4.2: The number of sites where backwater or loops in ratings affected forecasts
            was unprecedented.

            RECO-NEVENDATION.. 4.2,-, Loop rating curves are an indication that a dynamic wave
            routing technique is required. Each RFC and the Office of Hydrology should investigate the
            input data, model calibration, and simulation results associated with implementation of a
            dynamic wave model in any affected area.


            EDWING 4.3; In many of the flooded areas on the Missouri and Mississippi Rivers, the
            stages exceeded those of prior records while the corresponding volumes of flow often did
            not. Assessment of the causes of this factor are important to the objective of applying the
            best river hydraulics in future river modeling and forecasting.


            RECD_@@@ATION 4.3: In The Great Flood of 1993, levee effects and unknown
            ratings are probably the dominant causes of discrepancies between the river stages and
            volumes of flow. The Hydrologic Research Uboratory should use the dynamic wave model
            to determine the causes for these discrepancies.    Additionally, new ratings must be estab-
            lished for many forecast points.




                                                         9-5









               FINDING 4A Levee effects on overbank storage and downstream forecasts were difficult
               to analyze. The size and type of failures were highly variable.

               RECQhRffMAT10N 4.4* The use of airborne photographic reconnaissance to pinpoint
                                           I
               levee failures should be an option readily available to RFCs. The Hydrologic Research
               Laboratory and the RFCs should investigate more effective ways to model levees and levee
               failures.



               FINDING 4.5: St. Louis District COE has profiles of Federal levees with top-of-levee
               elevations for non-Federal levees. Some levee profiles may change in the aftermath of the
               extensive flooding.

               RECONZEMAMN 4.5: The NWS should coordinate with the COE to obtain levee
               information for use in forecast procedures, especially when implementing the dynamic wave
               model in areas affected by the flood.


               FINDING 4.6: Coordination between the Missouri Basin River Forecast Center (MBRFC)
               and the North Central River Forecast Center (NCRFC) for the Missouri River forecast at
               Hermann, Missouri, was critical. Attempts to coordinate over the telephone were somewhat
               successful, but much of the information exchange was hampered by technological limitations.
               Limitations in the current RFC technology do not allow the Hermann forecaster at the
               MBRFC and the St. Louis forecaster at the NCRFC simultaneously to view all of the graphic
               and hydrologic information (including WSR-88D, hydrograph, satellite, and derived data
               sets) used by the other forecaster as input to his/her forecast procedures.

               RECONEMENDATION 4.6: The NWS should aggressively pursue installation of AWIPS
               and AWIPS-type facilities at RFCs (see Recommendation 4.10, 5.15, and 5.16) required to
               support the modernized NWSRFS, the Interactive Forecast System, and inter-RFC
               communications.



               FINDING 4,7: Portions of the Mississippi and Missouri River basins have many complex
               hydrologic and hydraulic elements that require application of advanced modeling approaches
               to handle such effects as backwater at river junctures, overbank flows, levee failures, and
               changing ratings.

               RECONEMUiDATION 4.7: The RFCs and the Office of Hydrology should accelerate the
               implementation of the dynamic wave routing model on those river reaches where its
               capabilities are required.





                                                           9-6









            FINDING 4.8: Detailed Geographic Information Systems (GIS) would have helped in the
            design and calibration of some hydrometeorological procedures, as well as allowing for more
            site-specific delineation of flood occurrences.

            RECONUWENDATION 4.8; NWS Headquarters should carefully examine plans for use of
            GIS applications within the AWIPS program to assure the most effective use of this
            technology to assist the national hydrology program.


            FINDING 4.9: Current limitations in operational implementation of hydrologic/hydraulic
            models, computer hardware, and software contributed to the inability of the RFCs to
            incorporate QPF amounts into river forecasts on an objective, routine basis.

            RECOMAWNDATION 4.9: The RFCs should move as quickly as possible to implement
            advanced hydrologic/hydraulic models and planned, modernized methods to objectively and
            routinely incorporate QPF. Since these planned methods require AWIPS-type technology,
            the RFCs should also investigate ways in which QPFs may be objectively incorporated into
            the river forecasts in the near term (see Finding 2.10 above) without damaging the integrity
            of the forecast (e.g., issuing a banded forecast based on potential rainfall).


            FWDING 4.10: The forecasters and end-users expressed frustration with the limited amount
            of information contained in the river forecasts. Sufficient information is not provided to do a
            proper risk analysis. Forecasters compute total hydrographs and have some feel for the
            potential effects of various hydrologic contingencies, such as levee failures and rating shifts.
            There is currently no way routinely to convey this additional information to the sophisticated
            end-users capable of benefiting from the added information.

            RECOND4ENDATION 4,10: As soon as possible, the NWS should: (1) install AWIPS
            and AWIPS-type equipment at the RFCs (see Recommendation 4.6, 5.15, and 5.16) and
            (2) implement WARFS to provide the required hydrologic forecast capabilities
            (see Recommendation 2.9).


            9.5 DATA ACQUISITION, TELECOMMUNICATIONS9 FACILITIES, AND
                 COMPUTER SYSTEMS (CHAPTER 5)

            FINDING 5.1; Most NWS offices indicated that a shortage of stream and precipitation
            gages hindered their ability to produce accurate and timely forecasts. The Des Moines case
            study in Chapter 6 dramatically illustrates the major impact that the loss of just one stream
            gage can have on hydrologic forecast procedures.




                                                          9-7









                RECQM6ffMATION 5.1: NWS field offices should continue to provide support to
                cooperating agencies in their efforts to obtain resources for the maintenance of existing gages
                and the installation of additional stream and precipitation gages in strategic locations.


                @M 5.2: There were a number of errors in Standard Hydrometeorological Exchange
                Format (SHEF)-coded data.

                RECOMMENDATION 5.2: The Office of Hydrology and regions should increase the
                emphasis on training in the use of SHEF for data exchange. Additionally, the NWS should
                increase the use of automated, quality-control procedures for data entry including those
                appropriate for Remote Observation System Automation (ROSA).


                FINDING 5,3: The number of stations in the NWS cooperative program has been declining.
                There is a need to recover lost stations.


                RECOMMENDATION 5.3: Local NWS offices should explore ways to enhance their
                cooperative programs. The importance of the Cooperative Observer Program should be
                stressed to all current and prospective members of the cooperative network.


                FINDING 5A Most offices would like to see the ROSA system expanded to include more
                cooperative stations.

                RECONMENDA770N 5A Advantages of ROSA should be emphasized, and NWS should
                fund increased deployment of ROSA systems.


                FINDING 5.5: RFCs and WSFOs found the data collection platform (DCP) river stage data
                to be generally useful; but cases were noted when significant formatting, decoding, and other
                errors occurred. One RFC felt that rainfall information from tipping bucket gages was so
                unreliable as to be unusable with current quality-control procedures. Consequently, the DCP
                precipitation data in the RFC's area were not used in the river and flood forecasts.

                RECOMKMATION 5.5: DCP data should be carefully scrutinized daily. When errors are
                detected, the agency owning that particular DCP should be contacted immediately. If the
                problem is not corrected within a reasonable time, proactive, follow-up contacts should be made
                when time permits. RFCs should improve their capabilities to display, verify, and quality
                control DCP rain gage data automatically to make maximum use of this valuable data source.






                                                              9-8









            EMMG 5,6: Once transmitted, DCP data take too long to reach the RFC and WSFO
            databases.


            RECONEMNDATION 5.6: NWS must ensure that the increased computing capabilities
            planned as a part of NWS modernization include adequate telecommunications and a robust
            data management system to alleviate these problems.          The NWS should implement
            Automated Critical Reports in Hydrometeorological Automated Data System (HADS) as soon
            as possible to help alleviate this problem.


            ERMC, 5,7: In one instance, the RFCs had difficulty receiving data from HADS. The
            problem stemmed largely from the imprecise specification of the Time Periodic Report
            capabilities and occurred when retrieving COE DCP data from the Rock Island District.

            RECOMAWNDATION 5.7; The NWS should provide an in-depth training program to
            HADS focal points at RFCs and WSFOs. The NWS should implement Automated Critical
            Reports in HADS to facilitate data transfer.


            FINDING 5.8; Some NWS Limited Automatic Remote Collectors (LARC) were unable to
            report data when the river stage exceeded 32.7 feet. The data register in a LARC can accept
            and report information from a total of 32,767 increments. If the decimal point is set to read
            out to one thousandth of a foot, the unit has a range of only 0.000-32.767.

            RECONAUNDATION 5.8* Electronics Technicians should program LARCs so that they
            can accept and report data only to the nearest one hundredth of a foot (resulting in a total
            range of 00.00-327.67 feet). Electronics Technicians should also set up all appropriate
            LARCs so that the data range is broad enough to cover well beyond the greatest flood of
            record, as well as below the lowest low flow on record. The NWS Training Center should
            provide the necessary training to program and set up LARCs.


            FINDING 5.2: Information obtained from LARCs demonstrably increased the ability of
            forecasters to issue accurate and timely forecasts and warnings.
            RECOMAWWU@TION 5.9-*_ High priority should be placed on the installation and main-
            tenance of additional LARCs with attached, automated rain gages. The NWS should place a
            high priority on the Equipment Replacement Program needed to restore, to maintain, and, in
            some strategic locations, to add LARCs required to support the NWS hydrology program.






                                                         9-9









                FINDMM 5,10: Currently there are two Centralized Automatic Data Acquisition System
                (CADAS) computers. System A collects data from LARCs located in the Eastern and
                Central Regions, and System B collects data from LARCs located in the Southern and
                Western Regions. Each system is currently designed to collect data from 510 LARCs.
                System A presently collects data from 503 LARCs, and System B presently collects data
                from 350 LARCs. A better balance between the two systems may be possible to ensure that
                System A has room for more than the seven free spaces that now exist.

                RECONOUNDAMN 5,10: CADAS should be modified to collect data from more
                LARCs. Additionally, the CADAS interrogation programs should be updated to include
                newer telemetry systems such as Sutron 8200 data loggers with modems and Campbell
                CR-10 recorders. The NWS regions and the Office of Hydrology should establish an
                advisory board to recommend to the CADAS Program Manager appropriate modifications to
                the CADAS required to support the NWS hydrology program.


                FINDING 5,11: Stream gage observations from multiple gages at single locations some-
                times created confusion.


                RECONEMENDATION 5,11.0t NWS policy should clearly designate the primary and
                secondary gages at those sites where multiple gages exist.


                FINDING 5,12: In many cases, stream gages are mounted on the downstream side of piers
                and bridge pilings. At high flows, drawdown effects may lead to errors and inconsistencies
                in stage observations.

                RECONBUNDATION 5,12: In a cooperative effort with the other agencies involved, the
                NWS should study the drawdown effect to better quantify this problem.


                FINDING 5.13: There were numerous automated stream gage outages throughout the flood,
                as well as other cases with biased observations, that caused forecasting difficulties. Although
                backup procedures were often in place, they were not always adequate to meet the needs for
                a flood of this magnitude.

                RECONEMENDATION 5.13; NWS offices should ensure that the backup plans for stream
                gages in their areas are as complete and thorough as possible.          Guidelines should be
                established and tested to provide a smooth transition to the backup gage when a site's
                primary gage fails.






                                                             9-10









           FINDING 5,14: Some WSR-88Ds in the flooded area (Chicago, Illinois; Hastings,
           Nebraska; St. Louis, Missouri; and Topeka, Kansas) experienced extended downtime as a
           result of lightning strikes and other system failures. The operational availability of the
           WSR-88Ds must be increased to the 96percent level specified in the Next Generation
           Weather Radar (NEXRAD) Technical Requirements to provide the continual time series of
           rainfall estimates needed for input to flood and flash flood models. Improved methods for
           lightning protection are being tested using the WSR-88D at Norman, Oklahoma.

           RECOMM.NDATION 5,14:, Lightning protection and other system improvements for the
           WSR-88Ds required to achieve the contract-specified 96 percent operational availability must
           be given high priority.


           FINDING 5,15: The WSR-88D Principal User Processor does not support digital output or
           provide sufficient capabilities to make effective, quantitative use of the WSR-88D
           precipitation estimates. Without the planned AWIPS interactive processing facility and the
           additional precipitation processing stages planned for AWIPS-era operations, the useftilness
           of WSR-88D precipitation data for quantitative hydrologic forecast applications is quite
           limited.


           RECOMMMATION 5,15: The NWS should aggressively pursue installation of AWIPS
           and AWIEPS-type facilities for WSR-88D-equipped offices and for RFCs with significant
           coverage of their areas of responsibility by WSR-88D systems.


           FINDING 5.16: To use the WSR-88D precipitation products as input into the river forecast
           models, RFC staff had to manually estimate mean areal precipitation (MAP) values using
           hard-copy printouts. This method is imprecise and time-consuming.

           RECOMMENDATION 5.1-6-,-, Improved computer technology at the RFCs, which is a part
           of NWS modernization, will help remedy this problem. Every opportunity should be taken
           to accelerate the implementation of computer processing capabilities at the RFCs. Also, map
           backgrounds outlining MAP areas should be added to the WSR-88D database.


           FTqDING 5.17:       Graphical representation of satellite-derived isohyetal patterns are not
           available over the Automation of Field Operations and Services (AFOS) system.

           RECONEMWMATION 5,17: The NWS and National Environmental Satellite, Data, and
           Information Service (NESDIS) should make the Interactive Flash Flood Analyzer (IFFA)-
           derived precipitation estimates routinely available over AFOS during flash flood events.





                                                       9-11









                FINDM 5,18: The operational use of satellite precipitation estimates has not yet reached
                its full potential.

                RECON04ENDATION 5,18: The NWS and NESDIS should develop a procedure to
                integrate EFFA-derived rainfall estimates with radar and rain gage observations.            The
                procedure should be flexible enough to compensate for missing observations.


                FINDING 5.19: Satellite soil moisture estimates are not currently used in operational river
                forecasting.

                RECONEMW,NDATION 5,19: NOAA should implement techniques to use remotely sensed
                (i.e., airborne and satellite) and in siW soil moisture observations in river and flood
                forecasting.


                FINDING 5,20: In at least one case, the hardware configuration of the Automated Local
                Evaluation in Real-Time (ALERT) system made it technically impossible to transfer NWS
                river forecasts and warnings to the ALERT system.

                RECOMTvW,NDATION 5,20: NOAA Weather Wire is the primary method of NWS
                product distribution.   Nonetheless, NWS forecast offices should ensure that appropriate
                memoranda of agreement are in place with local parties for appropriate two-way exchange
                between ALERT systems and the NWS. Where technically feasible, ALERT systems should
                be modified to facilitate exchange of hydrometeorological data, forecasts, and warnings
                between ALERT systems and NWS offices.               Additionally, local hydrometeorological
                detection systems, such as ALERT, should be tested periodically to ensure that they are
                functioning properly.


                FINDING 5,21: There was variation in the effectiveness of reporting flood conditions by
                SKYWARN observers.


                RECONEMTWDATION 5.21:, NWS Headquarters should include in the SKYWARN spotter
                training syllabus material on flood reporting. Local offices should educate observers about
                effective flood reporting procedures. Spotters should be encouraged to submit reports when
                heavy rain and/or flooding occurs (which may require maldng affordable rain gages
                available).


                FT14DING 5,22:       Existing stage-discharge relations were exceeded at approximately
                100 sites. During the most severe flooding, flow measurements were too sparse.




                                                             9-12









            RECOMWMATION 5,22;                 Through collaborative efforts with principal NOAA
            cooperators, resources (including those to update streamflow measurements and/or perform
            analyses) need to be made available so that new stage-discharge relations can be developed
            for these sites.



            ERMG 5,23: There were periodic coordination and communications problems associated
            with data exchange between Federal agencies. For example, appropriate NWS offices did
            not always receive, in a timely manner, the special streamflow measurements made by the
            COE or USGS. Additionally, appropriate NWS offices were not always made aware of the
            streamflow measurement schedules; consequently, it was impossible to infer when NWS
            offices did not have specific stream discharge measurements. Computer hardware limitations
            sometimes made it difficult to distribute NWS products to end-users. Consequently, NWS
            offices were, on occasion, required to fax forecasts and products to end-users.

            RECONEWENDATION 5.23: The COE, USGS, and NWS should improve communications
            links among themselves and with other Federal, state, and local agencies. Specifically, the
            three agencies should ensure that the data collection schedules and the data distribution
            mechanisms for stream discharge measurements and other valuable hydrometeorological data
            sets are well understood and documented. In some cases, computer-to-computer links must
            be developed and/or upgraded (see Recommendation 6.19).


            EMING 5,24; Precipitation from stranger reports cannot conveniently be input into
            NWSRFS in its present form.      RFC personnel must input these reports at defined nearby
            missing stations, or manually estimate affected MAP areas. Because of this labor-intensive
            process, stranger reports provided by WSFOs/WSOs are not usually used.

            RECONEMENDATION 5.24: The Office of Hydrology should make the necessary effort to
            modify the MAP preprocessor so it can accommodate stranger reports.


            EINDINQ 5.25; Much of the early flooding (March, April, and May) in the Upper Midwest
            was aggravated by above-normal snow cover conditions that developed during the winter and
            spring of 1993. WSFO Sioux Falls indicated that additional snow water equivalent data
            would have been valuable before the onset of the 1993 spring snowmelt flooding. The NWS
            maintains a dense network of airborne flight lines in the Upper Midwest. The airborne snow
            survey program provides reliable, real-time airborne snow water equivalent measurements
            over the flight line network for use by NWS field offices when assessing the potential for
            spring snowmelt flooding.







                                                        9-13









               RECOADIENDATION 5,25: Hydrologists in the regional, RFC, and WSFO offices should
               request airborne snow surveys over specific areas within their respective regions of
               responsibility when snow water equivalent is expected to be a major factor associated with
               spring flooding in the Upper Midwest.


               FINDWG 5,26: The Great Flood of 1993 left large regions of the Upper Midwest with
               much above-average soil moisture conditions in the fall of 1993. The existing network of
               airborne flight lines can be used to make airborne soil moisture measurements in the late fall
               of 1993. Fall airborne soil moisture measurements are used by NWS hydrologists at the
               NCRFC when assessing the potential for future flooding during each winter and spring.

               RECOADdEZMATION 5,26: The Office of Hydrology should make a comprehensive air-
               borne soil moisture survey over the existing flight line network in the Upper Midwest to
               provide an assessment of soil moisture conditions in the late fall of 1993.


               FTNDING 5,27: Telephone lines to certain key stream gages were destroyed by the flood.

               RECONEMW,NDATION 5,27: The use of alternative data acquisition systems for stream
               gage data (e.g., radio, satellite, or meteorburst transmission technology) should be explored
               to build redundancy into the system at key locations.


               FINDING 5,28:       The current telecommunications environment for interagency            data
               exchange relies on limited, voice-grade, two-way links. This telecommunications approach
               did not provide an adequate level of service to the COE and other Federal, state, and private
               cooperators during The Great Flood of 1993. Moreover, it is completely inadequate to
               support even higher rates of data exchange. Higher levels of service can be achieved now
               with available telecommunications technology.

               RECONEWENDATION 5,28; The NWS should implement plans for modem telecommuni-
               cations and information exchange with major water management cooperators and conduct a
               demonstration of these capabilities as soon as possible.


               FINDING 5,29: WSFO Bismarck dials directly into- the Environment Canada system for
               data. - There are frequent problems, however, in routing data from the National Center in
               Toronto through the NMC to the WSFO. These data are often delayed or unavailable.

               RECONEMW2-;DATTON 5,29: NWS and Environment Canada field offices should continue
               their good working relations. The NMC and Environment Canada's National Center should
               investigate the possibility of improving the interface between their computer systems.



                                                           9-14









             FINDING 5,30: There is no backup should there be a disastrous failure of the NOAA
             Central Computer Facility (NCCF) for those RFCs that are still dependent on the facility.

             RECOAMEMATION 5.30: As quickly as possible, NOAA should develop disaster con-
             tingency plans to use distributed AWIPS-type RFC systems to provide backup for NCCF-
             dependent RFCs until AWIPS is deployed.


             FINDING 5,31; Despite the limited capabilities of AFOS and the fact that those capabilities
             were pushed to their limits throughout the flood event, AFOS generally performed in a
             reliable and stable manner. Concern was expressed that AFOS, which has exceeded its
             original life expectancy, will not be able to continue reliable performance.

             RECONEMUMATION 5,31: AFOS must be maintained as a highly reliable operational
             NWS system until replaced by AWIPS at the earliest possible date.


             FINDING 5,32: Communications between RFCs and the NCCF are critical to RFC
             operations and are a weak link in the current river forecast system.

             RECONEMWI'4DATION 5.32: The NWS must evaluate its backup procedures to ensure
             there is sufficient communications capacity to support operations during major flooding.


             FINDING 5.33: Current RFC communications capabilities are too slow for extreme loads
             generated at times of widespread major flooding. During The Great Flood of 1993, a
             workaround was developed to operate both the dedicated 9600-baud circuit simultaneously
             with the 4800-baud dial backup circuit for the North Central RFC. This was effective in
             increasing the communications capacity by 50 percent, but it is expensive and has no backup.

             RECOMMENDATION 5,31 All RFCs should be made aware of the potential use of the
             dial backup remote job entry circuit as an emergency, temporary boost to their NCCF
             telecommunication capabilities.


             @I[NG 5.34; Some offices lack large workspace areas for use of bulky items such as
             topographic maps.

             RECOMMENDATION 5.34i               The layout of new facilities being built as part of
             modernization and associated restructuring (MAR) should be configured to consider the
             requirement for flat workspace. Where practical, current offices should be rearranged to
             accommodate this requirement.




                                                         9-15









                FINDING- 5,35: The posting, data management, and quality control of hydrometeorological
                data, in general, is too slow, laborious, nonsystematic, and incomplete.

                RECOMM
                             MATION 5,35:           The AWIEPS system (which will employ sophisticated
                graphics, database, and computing capabilities that far exceed those currently in use) should
                eliminate system reliability problems and facilitate data management tasks. It is essential that
                AWIPS be implemented as soon as possible.


                FTNDIN(; 5,36: Users indicated a need for more fi-equent river forecast updates. The RFC
                model update cycle is dependent on batch computer operations over a communications link to
                the NCCF. This problem was less acute for the MBRFC because some forecast operations
                are run locally on a minicomputer. Batch-mode operations not only contribute to delays in
                forecast updates but also inhibit the forecaster from gaining the level of insight into
                hydrometeorological conditions that is possible with local, interactive processing.           This
                contributed to delays in forecast release times.

                RECONMUNDATTON 5.36: The NWS should move as quickly as possible to install on-
                site, interactive forecast systems in RFCs to speed up production of forecast products,
                including updated river forecasts and contingency forecasts based on various precipitation
                scenarios.   Although the AWIPS system will ultimately support this interactive RFC
                environment completely (see Recommendation 5.35), opportunities to take advantage of
                AWIEPS-type facilities and/or early AWIPS platforms must be maximized. Additionally,
                Hydrologic Service Area (HSA) offices should work with the RFCs to coordinate event-
                driven updates that provide users with timely flood warning information.


                FINDING 5,37: Various system hardware problems and the lack of technician support
                required hydrologists to perform electronic maintenance functions to keep systems operating.

                RECOMMENDATION 5,37: Contingency plans should be developed by the Office of
                Systems Operations and the NWS regions to ensure that all RFCs have adequate electronic
                systems support during critical flood events.


                9.6 WARNING AND FORECAST SERVICES (CHAPTER 6)

                FMING 6.1: Long-term river forecasts significantly underestimated stages because they
                did not include estimates of future precipitation.

                RECOMMENDATION 6.1i Information contained in precipitation forecasts and outlooks
                must be factored into river forecasts.





                                                              9-16








            FINDING 6.2: Current precipitation forecasts are not available in a format that allows easy
            incorporation into operational river forecast procedures.

            RECOMMENDATION 6,21 Manually prepared precipitation forecasts and outlooks must
            be formatted to allow for the efficient, automated incorporation of digital precipitation
            forecasts into river forecast procedures.


            FINDING .3: Precipitation forecasts are least accurate at the smaller scales required by
            current hydrologic forecast procedures. Nevertheless, QPF information at current skill levels
            contains valuable information that could benefit hydrologic modeling.

            RECOMMENDATION 6.3: The NWS must focus efforts to: (1) enhance precipitation
            forecasting on the space and time scales needed in hydrologic models and (2) develop
            methodology that incorporates QPF information into advanced hydrologic modeling
            approaches.


            FINDING 6.4: Extended streamflow prediction techniques provide a promising framework
            to incorporate precipitation forecasts into the hydrologic modeling and forecast system.

            RECONEV014DATION 6.4:             The NWS should support research, development, and
            operational testing to incorporate current QPF and other precipitation outlooks into river
            forecasting procedures.


            FINDING 6.5:       Effective integration of QPF information into hydrologic models is
            extremely difficult and will require close collaboration between NMC and the RFCs.

            RECONEMMMATION 6.1. An exchange program should be instituted whereby RFC staff
            visit NMC and NMC staff visit various RFCs to address the technical and scientific problems
            preventing effective use of QPF in operational river forecast models.


            FT@WlNfz 6.6; WSFOs and WSOs exhibited a wide range of philosophies in the issuance of
            warnings versus statements. The decision of what type of product to issue can become a
            judgment call. To some degree, it is based on the geographical area and associated flood
            climatology.

            RMONUVW11DATION 6.6:                All offices should review Weather Service Operations
            Manual chapters that describe types and content of products and adhere to these guidelines as
            closely as possible. The Regional Hydrologist should coordinate with the SHs to ensure
            consistent use of products (see Recommendation 6.17).



                                                        9-17








                FINDI@ffi 6,7: No systematic, national program exists to verify river forecasts.

                RECOhDMMATION 6.7: The West Gulf RFC, other participating field focal points, and
                the Office of Hydrology have designed an appropriate national verification system. These
                offices should continue development and implementation of the procedures and software
                required for the system.


                FINDING 6.8: A growing recreational area along the Missouri River south of Sioux Falls
                often draws as many as 100,000 campers. There is no way to provide weather information
                to these campers.

                RECONUMMNI)ATION 6.8: The NWS should provide a NOAA Weather Radio (NWR)
                repeater in or near the recreational area.


                FINDING 6.9: WSFOs and RFCs were inadequately staffed to manage a disaster of this
                magnitude. In the few locations where extra personnel were imported from NWS offices that
                were not currently experiencing severe hydrologic problems, impacts were always positive.

                RECONEMW,NDATION 6.9: Each region should establish a personnel backup procedure for
                large, protracted events.


                FINDING 6,10: WSO Columbia staff was required to provide radar backup when the
                WSFO St. Louis' WSR-57 Network Radar was down. This created an additional burden on
                the already overworked staff. This problem will be slowly resolved when WSR-88D radars
                begin to be commissioned.

                RECONEMW.NDATION 6.10: Every effort should be made to reach acceptable operational
                availability levels for commissioning WSR-88D radars as soon as possible.


                FMING 6.11: Many meteorological forecasters did not feel proficient handling prolonged
                and major hydrologic operations when an SH was not in the office or on staff. WSFO
                Topeka has no SH. Consequently, it was much more difficult to maintain a high-quality
                hydrologic program without immediate access to specialized hydrologic expertise. Those
                offices with SH positions reported them indispensable in the capacity of local expert who
                coordinates hydrologic training of office staff, data flow, user interaction, media contacts,
                and forecast services.


                RIECOMAU,NDATION 6.11: In the modernized weather service, the NWS should revisit
                its planned staffing allocations for SHs necessary to support those WFOs that have high
                levels of significant hydrologic activity.


                                                           9-18








            FINDING 6,12: The SHs served as the primary contacts at the WSFOs to accumulate a
            wide variety of data from a large number of hydrometeorological data networks supported by
            numerous Federal, state, and local agencies. The SHs were creative and innovative in their
            efforts to ensure that critical hydrometeorological data were available for use in the NWS
            hydrologic forecast and warning program.

            RECOMMENDATION 6,12: See Recommendation 6. 11.


            FIND-ING 6,13: Both MEBRFC and NCRFC provided extended coverage for most of the
            protracted flood event on a 7-days-a-week schedule well into the evening (usually until 10 or
            11 p.m.). Nevertheless, certain users cited an inability to acquire needed information during
            hours when the RFCs were not in operation, and many end-users require 24-hour RFC
            support during major flood events. The NCRFC provided around-the-clock coverage for
            4 days during the event. The MBRFC provided 24-hour coverage for 2 days.

            RECONEMW,NDATION 6,13: RFCs should be staffed for 24-hour coverage during major
            flood events.



            FINDIN(I 6,14; By the time some RFC forecasts were received by the WSFOs, observed
            river stages exceeded forecast stages. As the modernization process improves the timeliness
            of the forecast cycle, improves the forecast accuracy, and reduces product transmission
            delays, the frequency of this type of occurrence will be reduced.

            RECONEWENDATION 6.14:               Whenever RFC forecasts are obviously in error, WSFO
            forecasters should immediately coordinate with the supporting RFC before issuing any public
            product based on these forecasts.


            FINDING 6.15:          The NCRFC staff stated that if the planned staffing for
            Hydrometeorological Analysis and Support forecasters in the modernized weather service had
            been on board, the NCRFC would have been able to analyze, in greater depth, the radar
            rainfall estimates and QPF products.

            RECONEMWI14DATION 6,15: Within the current budget constraints, NWS Headquarters
            and regional offices should do everything possible to complete the modernized staffing levels
            for the RFCs.



            FINDIN(i 6.16;: There were end-users that did not have access to and/or the expertise
            required to interpret the voluminous amounts of information contained in the large number of
            NWS products. This potentially can become an even greater problem in the modernized
            NWS when much more site-specific information becomes available.


                                                         9-19









               RECOMMENDATION 6,16: It is critical that the packaging and distillation of the relevant
               information for water control and emergency management decision makers be improved.
               Some of this problem may subside as the NWS moves into modernized methods of providing
               information in graphical format. Until then, HSA offices and RFCs should contact their
               principal governmental users to discuss and implement innovative packaging of information
               tailored to their local areas and needs.



               EMP-M 6,17: During the flood event, a large number of flood products were issued
               including Flood Warnings, Flash Flood Warnings, and Urban and Small Stream Flood
               Advisories. The appropriate choice of product headers, and when to use them, at times
               confused NWS meteorological forecasters.

               RECONEMMMATION 6,17: The SHs should ensure that all office staffs are trained on the
               appropriate use of product types.


               FTNDING 6,18: Extra NWS personnel rotated into the RFCs and WSFOs and worked many
               hours of overtime. The scheduling and rescheduling of leave or training for WSFO and RFC
               staff became a factor in maintaining adequate staffing levels.

               RECONEMENDATION 6,18; During long, widespread record events of this type, essential
               personnel should return to their duty stations from long-term training assignments. Anyone
               withdrawn from long-term training under these conditions should be rescheduled for a later
               date.



               FTNDING 6,19: There are three different RFCs that provide forecasts to the St. Louis COE
               covering the upper Mississippi River basin (NCRFC), the Missouri River basin (MBRFC),
               and the lower Mississippi River basin (LMRFC). The St. Louis COE District Office
               expressed concern that the forecasts from the three NWS offices were not always internally
               consistent.


               RMONEMENDATION 6,19: The COE and NWS should establish a technical working
               group consisting of personnel from all appropriate NWS and COE offices to ensure that
               techniques and procedures are fully understood and that clear points of contact are
               established to clarify any potential misunderstandings during flood events. Moreover, the
               NWS and COE offices should implement a personnel exchange program whereby personnel
               from the two agencies would work on-site in the other cooperating agency's office either
               part-time or full-time.







                                                         9-20








             FINDING 6,20: An inability to determine accurately the amount and time distribution of
             precipitation led to uncertainty in forecasting both volume     'and timing of flood crests. As
             specifically noted in the Des Moines, Iowa, case study, inaccurate precipitation estimates are
             generally considered to be the greatest single source of river forecast effor. The NWS plans
             to produce precipitation estimates which combine rain gage observations, WSR-88D
             precipitation estimates, and satellite observations in sophisticated, multistage, multisensor
             precipitation estimates using both interactive and automated quality-control features. These
             plans require the completion of the WSR-88D radar network and the on-site, interactive
             processing provided by AWIPS.

             RECONDIENDATION 6,20: Completion of the WSR-88D network and the AWIPS
             program must continue to have high priority (see also Recommendations 5.14 and 5.15).


             fMJNG 6.21; Record flows occurred earlier than were forecast at many points along the
             Des Moines River and its tributaries due, in part, to routing procedures that overestimated
             travel times.    Current routing procedures are based on observed hydrograph data from
             previous floods.

             RECONEMENDATION 6,21: Empirical routing procedures should be recalibrated to
             account for maximum discharges that occurred during The Great Flood of 1993.


             9.7 COORDINATION AND DISSEMINATION (CHAPTER 7)

             FINDING 7,1: The special teleconferences involving RFCs, WSFOs, NMC, and the Office
             of Hydrology during the 1993 flood event were beneficial in several aspects, especially to
             RFCs that were trying to consider future hydrometeorological conditions over their broad
             areas.    Certain improvements, however, in the management and content of the tele-
             conferences would have made them even more beneficial.


             RECONEMENDATION 7.1: The logistics of handling and guidelines for the content of the
             teleconferences should be more streamlined by regional, NMC, Office of Meteorology, and
             Office of Hydrology personnel. The information on QPF products conveyed from NMC
             should have concentrated on additional physical insights into the forecasts, and their potential
             accuracies, beyond that contained in the issued products.


             ELN-DING 7.2: NWS teleconferences did not use video.

             RECONEMENDATION 7.2; The NWS should investigate the feasibility and evaluate the
             potential effectiveness of video teleconferencing during protracted events such as The Great
             Flood of 1993.



                                                             9-21









                FINDING 7.3: In some cases, differences in RFC formats used to transmit river forecasts
                required editing by WSFOs and WSOs prior to issuance to the public.

                RECOhnffMATION 7.3: All RFCs should use the same format in transmitting river
                forecasts and other products.


                FINDINQ 7A Several internal NWS products, such as the State Forecast Discussion and
                Excessive Rainfall Discussion, were widely distributed to the media. In some instances,
                these technical products were taken out of context, sensationalized, and presented as official
                NWS forecasts by the media.

                RECONEMENDATION 7A NWS Headquarters should complete a review of the policy on
                dissemination of internal forecast discussion products through the NOAA Family of Services.


                FINDING 7.5: In some communities there appeared to.be a lack of communication and
                coordination among different agencies within the same community and officials of adjoining
                communities. Critical river and flood forecast information needed to prevent damage to
                major facilities was sometimes unavailable to all agencies.

                RECONEMW24DATION 7,5: National, regional, and local NWS offices should team with
                Federal, state, and local agencies to coordinate more frequent communication to ensure that
                needed information is distributed among all agencies.


                FRqDING 7.6: County officials often failed to call the NWS when levees failed. In many
                cases, the media knew about failures before the NWS. For example, St. Louis emergency
                response teams, such as the Red Cross and Disaster Services, reported that some local
                officials were slow to report levee breaks to the local NWS office, which resulted in delays
                in the issuance of flash flood warnings by the NWS.

                RECONEMW,NDATION 7.6: More intensive efforts should be undertaken at national,
                regional, and local levels to ensure maximum coordination and cooperation among agencies
                involved in disaster mitigation. While MAR expansion of local staffs to include a Warning
                Coordination Meteorologist at each WFO should promote better coordination, immediate
                efforts are needed.



                FINDING 7.7: Emergency operations centers (EOC) were established at several locations
                including Kansas City, Minneapolis, Des Moines, and St. Louis. These centers were staffed
                by key personnel from a variety of Federal, state, and local agencies involved in coordinating
                flood operations and disseminating information. WSFO Des Moines and the North Central
                RFC\WSFO Minneapolis maintained a periodic presence at EOCs through much of the flood


                                                            9-22









           event. Given the limited staffing available, it is out of the question for any NWS office to
           provide around-the-clock, on-site staffing support for EOCs. Although other WSFOs and
           RFCs provided information, they did not provide on-site representation at EOCs. In other
           cases where official EOCs were not established, close alliances were formed with the COE,
           the USGS, and local officials, such as in North Dakota.

           RECOMMMAMN 7.2; All WSFOs, RFCs, and WSOs should provide the highest
           level of support possible to EOC operations within their service areas during emergency
           situations. Highly reliable communications between the EOC and the WSFO/WSO/RFC is
           essential. When feasible, periodic, on-site EOC support should be provided. Such actions
           would improve coordination and cooperation in addition to increasing NWS visibility.


           FMING 7.8: The COE district offices generally provided reservoir outflow data on a
           periodic basis to the RFCs and to some WSFOs; however, the COE offices expressed
           concern over problems and inefficiencies in the connections and transfer rates experienced
           with antiquated NWS computers and communication equipment. The NWS, in some cases,
           had to fax products to the COE.

           RECONUMMATION 7.8; Over the short term, the NWS and COE should take all
           feasible actions to improve communications systems and data exchange procedures. Over the
           longer term, the NWS and COE should ensure that their respective RFC and water control
           district gateway systems are optimally interfaced.


           fMING 7.2; The Rock Island COE District strongly encouraged cross-training between
           COE and RFC personnel. Cross-training of NWS and COE personnel would substantially
           improve intra-agency and interagency operations, not only during flood events when
           personnel may be shifted from one office to another but also during routine operations.

           RECONUMMATION 7.9: See Recommendation 6.19.



           FINDING 7,10; More timely and effective ways are needed for computer-to-computer
           exchange and dissemination of data and products, including graphic displays, between NWS
           field offices and their cooperators and end-users.

           WONEMMMATION MQ: The NWS should actively pursue the multiple avenues
           required to provide timely products and information in appropriate formats to the various
           communities of end-users (see Recommendation 7.8). As part of this effort, NOAA/NWS
           should improve various aspects of its product dissemination policies.





                                                       9-23









                 FINDING-7,11: Certain cooperating agencies, especially the COE, noted frequent difficulty
                 in accessing RFCs and WSFOs through commercial telephone lines.

                 RECONVAFENDATION 7,11: The NWS should install additional, private telephone lines as
                 required, if not on a permanent basis, then at least on a temporary basis during severe
                 weather and flood events of this magnitude.           The additional lines will help critical
                 cooperators coordinate with NWS offices.


                 FINDING 1. 12:       Arrangements to handle NMC Meteorological Operations Division
                 interactions with the Federal Emergency Management Agency (FEMA) were accomplished
                 largely on an ad hoc basis in response to the emergency situation.

                 RECOIMB0MATION 7.12 NMC should establish a better level of understanding with
                                               1
                 other Federal agencies concerning what information can be provided on an emergency basis,
                 how it should be provided, and who are the appropriate contact points.


                 FINDMG 7,13: The National Flood insurance Program, administered by the FEMA
                 through the Community Rating System, encourages coordination among various local and
                 regional agencies in the development of flood warning plans. Communities that qualify for
                 participation in the Community Rating System receive discounts on flood insurance policy
                 premiums throughout the community.

                 RECONEMENDATION 7,13: The NWS should encourage FEMA and the National Flood
                 Insurance Program to strengthen recognition of community flood warning activities and to
                 expand eligible activities to include comprehensive flood action plans. These flood action
                 plans are designed to mitigate the impact of impending flooding, such as the identification of
                 flood magnitude thresholds that trigger action (e.g., sandbagging) to protect critical facilities
                 and infrastructure.



                 FINDINCz 7,14: The magnitude of The Great Flood of 1993 made the central United States
                 the focus of national and worldwide attention, which led to intense media interest. The
                 volume of telephone media queries for critical and noncritical flood information overtaxed
                 NWS staff at national, regional, and local levels. All offices in the affected areas were
                 inundated with requests to provide interviews, material, and information to the media and
                 NWS Headquarters for input to congressional briefings and for other program exercises.

                 RECOMWEMATION 7,14: Because of the long duration of The Great Flood of 1993,
                 additionaR resources to help handle public affairs functions should have been available. A
                 plan for activation of additional public affairs personnel support for such events should be
                 developed.   Additional training on procedures for interaction with the media and other
                 external parties should be provided for some offices.


                                                              9-24










           FINDING 7,15: Some media members suggested that better coordination of the NWS
           product release times to coincide with the broadcast schedules would have allowed for more
           timely and effective broadcast of NWS products to the public.

           RECONEMMMATION 7.15; The NWS should continue all possible acceleration of MAR
           components including lengthened standard hours of operation, staff augmentation, and
           implementation of new technologies at RFCs, which should allow initial morning river
           forecasts to be issued in the 7 a.m. time frame.



           FINDNG 7,16: In -many instances, local communities and municipalities are not maldng
           effective use of the NOAA Weather Wire Service (NWWS). In some cases, agencies were
           not even aware of the existence of the NWWS. Many communities did not use NWWS
           because of. (a) the high cost of the service, (b) the need for tailored forecast information,
           and (c) the high volume of products disseminated.

           RECONEMENDATION 7.16: The NOAA/NWS should explore the possibility of lowering
           NWWS costs, study the ramifications of not lowering NWWS costs, and redouble efforts to
           make other agencies aware of NWWS availability and features. Additional sources of
           product distribution, such as Internet, should be explored. Also, NOAA should encourage
           FEMA to provide support and assistance to communities so they can subscribe to the
           NWWS.



           FINDING 7,1_7; Most of the public is unaware of the availability of NWR, even though it
           broadcasts across most of the United States.


           RECONEVENDATION 7.17: The NOAA/NWS must make a substantially greater effort to
           educate the public on the availability of NWR and of the life-saving service it provides.


           FINDIN(j 7,18: Broadcasts of flood forecasts on NWR were sometimes not up to date.
           Some river products did not specify the time of the observed stage. It is especially critical
           during epic weather and flood events, such as The Great Flood of 1993, that personnel at
           NWS offices take extra steps to ensure that information broadcast on NWR is updated
           frequently so that NWR listeners receive only the latest information.

           RECONEMENDATION 7,18:         '  The current NWR policy of broadcasting the time and date
           for specific observations should be adhered to. See Finding and Recommendation 5.36
           pertaining to more frequent forecasts and updates.





                                                       9-25









                         . 7,19: Weather radar imagery and graphic products were not available to most
                Federal, state, and local agencies.

                RECOM74EMATTON 7.19: The NWS should determine whether current and planned
                provisions for dissemination of weather radar products are adequate to meet the needs of
                NOAA cooperators throughout the Nation.


                           7.20: Some county Emergency Management Agencies (EMA) stated that the cost
                of becoming a NEXRAD Information Dissemination System (NIDS) subscriber exceeds
                financial resources of many county EMA offices, especially in counties with small
                populations.

                RECO-m-azNPATION 7,20: The Federal Government should ensure that the NIDS
                providers continue to offer lower cost capability for these counties. The local WSFOs should
                also continue emergency coordination with county EMAs.


                9.8 PREPAREDNESS AND USER RESPONSE (CHAPTER 8)

                FINDING 8,1: Some basin and topographic maps at WSOs were outdated or missing.

                RECONEMW.NDATTON 8,1: Offices in need of topographic maps should procure them
                directly from the USGS. NWS Headquarters and regional offices should establish procedures
                to generate and update WSFO basin maps.


                FINDING 8.2: County emergency management officials expressed general satisfaction with
                NWS services. They sometimes noted a difference between statements issued by the COE
                and the NWS. Often, since the COE had a physical presence at the flood site, local
                authorities used information provided by the COE.

                RECOM3ff,NDATTON 8.2,* The NWS should improve coordination with county and state
                EMAs and EOCs through periodic review of action plans, participation in mock disaster
                exercises, and other planning approaches. Improved real-time coordination between the
                NWS and EOCs is addressed in Recommendation 7.7.



                FINDING 8.3: Most public works and emergency management departments in major
                municipalities have flood operation manuals. These manuals contain information on critical
                decision points for which various actions are initiated once critical river stages are reached
                (or forecast). These manuals were not always available in some NWS field offices.




                                                            9-26









           RECOAMMATION 8.3: The NWS should obtain the flood operation manuals, as well
           as maintain and improve relationshi ps with respective public works agencies and EMAs.
           Relevant information from these manuals should be incorporated in the Service Hydrologist
           Information Management System.


           FINDING 8.4; St. Charles County, Missouri, which has a moderate population, maintains a
           modem EOC operating a state-of-the-art Emergency Information System. Private sector
           funding helped to build an advanced EOC that uses NWS warnings and forecasts to better
           serve the public.

           RECONEMWNIDATION 8A Federal, state, and local agencies are encouraged to coordinate
           and to expand this type of modernized emergency system nationwide. This would improve
           dissemination and increase efficiency of providing NWS information to the public.


           FINDING 8.5., The media and the public do not fully understand hydrologic terminology,
           procedures, and forecast products.

           RECONBUNDATION 8.5; The NWS and NOAA Public Affairs, at all levels, should
           develop a public education program to increase awareness of and understanding about the
           hydrology program by using brochures, news releases, fact sheets, and other background
           materials, along with increased interaction with the media.


























                                                     9-27









                                             APPENDIX A


                            DISASTER SURVEY TEAM CONTACTS




           A.1 NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION/
                 NATIONAL WEATHER SERVICE


                  Regional Hydrologist, Central Region
                        Lee Iarson, Regional Hydrologist
                  North Central RFC Minneapolis, Minnesota
                        Dean Braatz, Hydrologist in Charge
                        Pat Neuman, Hydrologist
                  Missouri Basin RFC Pleasant Hill, Missouri
                        Larry Black, Hydrologist in Charge
                        Jack Vochatzer, Senior Hydrologist
                        Julie Meyer, Senior Hydrologist
                        John Pescatore, Hydrologist
                  WSFO Bismarck, North Dakota
                        Donald Stoltz, Area Manager
                        Charlene Prindiville, Service Hydrologist
                  WSFO Chicago, Illinois
                        Bob Somrek, Deputy Meteorologist in Charge
                        Jim Allsopp, Warning Coordination Meteorologist
                        William Morris, Service Hydrologist
                  WSFO Des Moines, Iowa
                        John Feldt, Meteorologist in Charge
                        Lee Anderson, Deputy Meteorologist in Charge
                        Larry Ellis, Service Hydrologist
                  WSFO Milwaukee, Wisconsin
                        Ken Rizzo, Area Manager
                        Tony Siebers, Deputy Meteorologist in Charge
                        Brian Hahn, Service Hydrologist
                  WSFO Minneapolis, Minnesota
                        Craig Edwards, Area Manager
                        Glenn Lussky, Deputy Meteorologist in Charge
                        Gary McDevitt, Service Hydrologist
                        Byron Paulson, Lead Forecaster
                        Sam Stanfield, Meteorological Technician




                                                    A-@









                     WSFO Omaha, Nebraska
                            David Wert, Deputy Meteorologist in Charge
                            Roy Osugi, Service Hydrologist
                     WSFO St. Louis, Missouri
                            Steve Thomas, Area Manager
                            Ted Schroeder, Lead Forecaster
                            Jack Burns, Service Hydrologist
                            Jim Kramper, Warning Coordination Meteorologist
                     WSFO Sioux Falls, South Dakota
                            Greg Harmon, Area Manager
                            Cliff Millsapps, Service Hydrologist
                     WSFO Topeka, Kansas
                            Curt Holderbach, Area Manager
                            Don Rogers, Deputy Meteorologist in Charge
                            Steve Kruckenberg, Service Hydrologist - Goodland, Kansas
                            Mike Akulow, Warning Coordination Meteorologist
                            Ken Labas, Science and Operations Officer
                     WSO Columbia, Missouri
                            David Larm, Official in Charge
                            Roger Pratt, Electronics Technician
                     WSO Fargo, North Dakota
                            Lou Bennett, Official in Charge
                     WSO Kansas City, Missouri
                            Randall McKee, Meteorologist in Charge
                            Steve Predmore, Service Hydrologist
                            Bill Bunting, Warning Coordination Meteorologist
                            Steve Runnels, Meteorologist


              A.2 U.S. ARMY CORPS OF ENGINEERS


                     Kansas City District
                            Jerry Buehre, Chief, Water Control Section
                     Lower Mississippi River Division (phone contact)
                            Joe McCormick, Assistant Chief of Operations
                     Office of Chief Engineer, Washington, D.C. (phone contacts)
                            Earl Eiker, Chief of Hydrology
                            Charlm Sullivan, Chief of Water Control and Water Quality
                     Omaha District
                            Phyllis Pistillo, National Emergency Manager
                            Wayne Dorough, Chief, Hydraulic Engineering Branch
                            Kevin Grode, Hydraulic Engineer
                            Kathy Willcuts, Chief, Water Control Section



                                                         A-2











                  Omaha Division
                         Chet Worm, Chief, Reservoir Regulation Section
                         John Countee, National Emergency Program Manager
                  Rock Island District
                         William Koellner, Chief, Hydraulics Branch
                  St. Louis District
                         Bill Arthur, Asst. Chief, Hydrologic and Hydraulics Branch
                         Gary Dyhouse, Chief, Hydrologic Engineering Section
                         (phone contacts):
                         Tom Lovelace, Chief, Hydrologic and Hydraulics Branch
                         Don Coleman, Potamology Section
                  St. Paul District
                         Ed Eaton, Chief, Water Control Branch
                         Bob Engelstad, Chief, Hydraulic Engineering
                         Major Andy Reese, U.S. Army
                         Pat Foley, Chief, Hydrology Branch
                         David Christenson, Chief, Emergency Management
                  Saylorville Reservoir and Dam, Johnson City, Iowa
                         John Demarce, Manager (phone contact)



            A.3 EMERGENCY MANAGEMENT AGENCIES


                  Chicago FEMA (phone contact)
                         Stuart Rifkind, Chief, Emergency Management Division
                  Columbia/Boone County EMA
                         Michael Sanford, Director
                  Iowa Emergency Management Division
                         Ellen M. Gordon, Administrator
                  Kansas City Emergency Operations Center
                         Joseph Henry Munoz, Chief
                  Lincoln County (Missouri) Emergency Management Agency
                         Dennis Harrel, Emergency Management Coordinator
                  Minnesota State Emergency Management Agency
                         Jim Franklin, Director
                         Judy Rue, Natural Disaster Coordinator
                         Brad Wise, Duty Officer of Supervision
                  Missouri State Emergency Management Agency
                         Charles Walker, Director
                  St. Charles County Emergency Management Agency
                         Gary Schuchardt, Director
                         Rod Zaire, Communications Officer
                  St. Louis County Police Emergency Management Office
                         Michael Redman, Communications Coordinator


                                                     A-3









              Sioux Falls Emergency Management Agency
                  Tom Welch, Region 8 Coordinator
              Scott County (Iowa) Emergency Mgmt. Agency (phone contact)
                  Ross Bergen, Disaster Services, Operations Officer


         A.4 NEWS MEDIA


              Coiumbia
                  KOMU TV
                       Ron Taylor, News Director
              Des Moines
                  WHO Radio
                       Jodi Chapman, Weather Reporter
                  KCCITV
                       Dave Busik, News Director
                       Gary Ambel, Meteorologist
                  Des Moines Register
                       John Carlson, Reporter
              Kansas City
                  KMBC TV
                       Brian Bracco, News Director
                       Brian Busby, Chief Meteorologist
              Minneapolis
                  KARE TV
                       Paul Douglas, Chief Meteorologist
                  WCCO TV
                       Mike Fairbourne, Chief Meteorologist
                       Rebecca Kolls, Meteorologist
              St. Louis
                  KMOX Radio
                       Thomas Langmeyer, Program Director
                       John Angelides, News Director
                  St. Louis Post Dispatch
                       Laslo Domjan, City Editor
                       Bill Allen, Science Writer
                       Tim O'Neil, Reporter
                       Virgil Tipton, Reporter
                  Associated Press
                       Lori Rose, Assignment Editor
                  KMOV TV
                       Trish Brown, Chief Meteorologist




                                     A-4











                           KSDK TV
                                  Scott Connell, Meteorologist
                                  John Fuller, Meteorologist


                         no
            A.5 OTHERS


                   Iowa

                           Davenport Public Works (phone contact)
                                  Dee Breurnmer, Public Relations Officer
                           Des Moines City Manager's Office
                                  Cy Carney, City Administrator
                           Des Moines Public Works
                                  Patrick Kozitza, Assistant Director
                                  Darwin Larson, Senior Engineer
                           Des Moines Water Works
                                  L.D. McMullin, General Manager
                                  Marty Lausiti, General Services Director
                           Iowa American Water Company (phone contact)
                                  Dave Hansen, Risk Management Officer
                           West Des Moines City Manager's Office
                                  Art Pizzano, City Manager
                                  Randy Bracken, Fire Chief
                                  Edward Stangl, Environmental Engineer

                   Missouri


                           American Red Cross, St. Louis
                                  Andrea Beer, Disaster Specialist
                                  Michael Monehan, Disaster Specialist
                                  Michael Miller, Dispatcher
                                  Jim Udell, Disaster Coordinator
                           American Waterways Operators, Washington, D.C.
                                  Jennifer Boucher, Public Affairs Officer (phone contact)
                           Coast Guard/Army Corps Command Center, St. Louis
                                  Jon Burk, Chief Planner, USCG
                                  LT Jim Curry, USCGR
                           Congressman Jim Talent's Office
                                  Brian Borsa, Staffer
                           Federal Aviation Administration
                                  Jim Adelman, Airway Facilities Specialist
                           Jersey County Olffinois) Sheriff's Office
                                  Frank Yocom, Sheriff


                                                         A-5









                           Kansas City Public Affairs Office
                                 George Hanley, Public Affairs Officer
                           Lincoln County (Missouri) Sheriffs Office
                                 Everett Rodger, Sheriff
                           Missoun Department of Transportation
                                 Gene Stephens, Track Safety Specialist
                           Missouri Highway and Transportation
                                 Jack Hynes, Director of Transportation
                                 Mel Sundermeyer, Administrator of Waterways and Railroads
                           St. Charles County Farm Bureau
                                 Earl Heitmann, President
                           Waterways Journal, St. Louis
                                 Dan Owen, Assmate Editor

                     Virginia

                           American Commercial Barge Line, CSX Corp
                                 Vance Richardson, Manager, Editorial Services




























                                                      A-6









                                                    APPENDEK B


                                     PRECIEPITATION FORECASTING




             BA NTRODUCTION

             A key input to any river forecast model is precipitation. Current operational river forecast
             procedures generally start with observed precipitation and predict its movement through the
             "earth portion" of the hydrologic cycle. The current procedures provide valuable forecast
             information for downstream locations on major river systems, where the time between rainfall
             and river rise is days to weeks.

             Forecasts for periods beyond the time between rainfall and river rise at a particular location
             depend on the ability to quantitatively predict future rainfall. As indicated in Section 4.3. 1. 1,
             river forecasts are based on the integration of computations for relatively small subbasins.
             Therefore, in addition to predicting the time and amount of precipitation, the location of the
             rainfall also needs to be precisely specified so that it is geo-referenced to the correct subbasin.
             Even for larger river systems, unless the timing, magnitude, and location of the predicted
             rainfall can be accurately delineated, errors in the timing and magnitude of downstream crest
             forecasts can be substantial.

             One of the frequent questions encountered by the disaster survey team had to do with the general
             absence of use of quantitative precipitation forecasts (QPF) in the hydrologic forecasts issued
             throughout this event. This appendix discusses some of the more significant issues raised by this
             question. Section B.2 examines QPFs produced by the National Weather Service's (NWS)
             National Meteorological Center (NMC) in some detail, including an assessment of the skill level.
             The section also includes three case studies of events that generated significant flood-producing
             precipitation during The Great Flood of 1993. This is followed by a limited evaluation of the
             QPFs viewed in terms of input quantities needed by current river forecast models (Section B.3).
             Section BA addresses the possible use of precipitation forecasts and outlooks with Extended
             Streamflow Prediction (ESP) modeling techniques to produce probabilistic river forecasts. The
             appendix concludes with an assessment of current capabilities and suggestions to enhance river
             forecast schemes (Section B.5).

             B.1.1 TYPES OF PRECEPITATION FORECASTS


             On a daily basis, NMC produces a set of maps specifying the spatial distribution of the
             magnitude of precipitation expected (QPFs) throughout the United States. The forecasts are for
             6- and 24-hour periods. In addition to the Day 1 QPF, a Day 2 forecast for the same time
             period is issued 24 hours before the beginning of the valid period; and the Day 2 is revised each


                                                             B-1








                    afternoon after receipt of the 12:00 Universal Coordinated Time' (UTC) model guidance
                    packages. On the same set of maps, areas forecast to have excessive rainfall are also indicated.
                    In addition to maps showing the spatial distribution of the forecast precipitation, text products
                    are prepared discussing the meteorological reasoning that went into the.QPFs. VVhile excessive
                    rainfall discussions are regularly issued twice a day, updates are prepared when heavy rainfall
                    conditions change rapidly.

                    NMC also issues 3- to 5-day precipitation anomaly forecasts every day. These are categorical
                    forecasts with regions being assigned to an above-normal, normal, or below-normal chance of
                    occurrence. On a daily basis, 5-day total precipitation categorical forecasts are also prepared.
                    The categories are: (1) no precipitation, (2) light, (3) moderate, and (4) heavy precipitation.
                    Three times a week, 6- to 10-day precipitation forecasts are issued using the same four
                    categories as for the 5-day precipitation forecasts. These forecasts are mainly determined by
                    statistical climatology. Finally, twice a month, NMC issues 30-day precipitation outlooks and
                    on a monthly basis 90-day precipitation outlooks. The outlooks indicate the probabilities of
                    precipitation amounts deviating from the climatological norm. Although this appendix focuses
                    primarily on the use of short-term, 24-hour, Day I QPF, it includes perspectives on how
                    precipitation forecasts/outlooks for longer lead-times may be included in future hydrologic
                    forecast procedures.


                    B.2 QUANTITATIVE PRECIEPITATION FORECASTING

                    Due to the many variables that enter into the forecast picture each day, forecasts for the precise
                    location and amount of convective rainfall is among the most difficult of the many weather
                    forecast problems, especially when a forecaster is asked to specify the temporal and spatial
                    details many hours before the event begins. It has been documented that the majority of summer
                    mesoscale convective rainfall events occur at night. Thus, 24-hour QPFs are issued from NMC
                    about 12-18 hours in advance of the rain event ("Day 1 forecast"). The forecaster relies quite
                    heavily on model circulation forecasts and interpretation of current data, including satellite and
                    radar imagery, and attempts to blend all of the available information into a logical and accurate
                    forecast.

                    From NMC's viewpoint, there has not been a warm season' with a circulation pattern similar
                    to that which prevailed during June and July of 1993 since QPFs were first issued in 1960. The



                          UTC is also known as Greenwich Mean Time. In the Midwest, it is shifted ftom local daylight time by
                    5 hours. Thus 12:00 UTC is the same as 7 a.m. CDT.

                       2  The meteorological processes influencing precipitation differ significantly throughout the year. Winter
                    precipitation is due mainly to frontal cyclones, while summer rainfall is predominantly produced by convection.
                    Ile ability to model winter precipitation is better than the skill in predicting summer rainfall. Since both the
                    physical processes leading to precipitation and the forecast skill are different, analysis and verification of QPF is
                    partitioned between a cool season (October-March) and a warm season (April-September).

                                                                            B-2








            striking feature of the 850-mb mean wind vector during mid-June to late July 1993
            (Figure 3-8(a)) is the strength of the southerly low-level wind field across the western Gulf of
            Mexico and south-central United States. Also quite evident is the west to northwest wind over
            the Upper Midwest and northern Rockies. These features combined to create a massive
            low-level convergence zone across the central United States. Figure 3-8(a) shows that a large
            supply of very warm, moist, and unstable air was being rapidly transported into a waiting
            low-level convergence zone.

            Figure 3-7(a) shows the mean 250-mb level wind vectors and mean wind speed for the same
            period. This figure shows that an upper-level jet pattern persisted during this critical 6-week
            period and provided extremely strong upper-level dynamics favorable to sustaining convective
            activity. Even in 6-week mean charts, the coupled low-level and high-level jet structure is very
            evident, with the central United States under the influence of the right entrance region (i.e., right
            rear quadrant) of the 250-mb jet, while simultaneously being located in the left exit region
            (i.e., left forward quadrant) of the low-level jet. The importance of this structure was found in
            individual precipitation situations where the coupled jets acted to produce very large precipitation
            events. Although the concepts of the coupled jets were empirically used by NMC forecasters
            for many years, recent documentation@ has served to focus increased attention on situations
            featuring coupled low-level and high-level jets.

            Since the prevailing low-level wind field over the south-central United States is southerly during
            the summer, it is useful to note how the 1993 summer wind field compared to a normal
            situation. Figure 3-8(b) shows the anomalous low-level wind vectors and analyzed wind speed.
            The low-level mean southerly wind exceeded by 4 m/s the mean wind for the 1979-1988 base
            period. Figure 3-7(b) shows the 250-mb anomalous wind vector field for the same period. On
            this chart, the 250-mb winds exceeded the reference 10-year average by over 10 m/s.
            Summarizing the impact of this flow regime, an extremely impressive synoptic situation
            prevailed for a 6-week period. This synoptic pattern ensured that the major ingredients for
            mesoscale convective rainfall and attendant flooding would occur and be sustained over a
            multistate area in the central United States during June and July 1993.

            Most of the events observed during The Great Flood of 1993 fit the Maddox et al      .4 composite for
            a frontal-type flash flood event. A southwest-northeast frontal boundary located below and to the
            south of the upper-level jet, shown schematically in Figure 3-6(a), acted to focus warm advection
            across the Plains and Midwest through the period. Each of the events was characterized by much
            stronger-than-normal, low-level, southerly jets that transported moisture northward into the front
            (Figure 3-8). The 850-mb winds and dew points and precipitable water values during the event
            exceeded the mean value found by Maddox et al. for frontal-type flash flood events.



                3 Uccellini, L.W., and D.R. Johnson. 1979. The coupling of the upper and lower troposphericjet streaks and
            implications for the development of severe convective storms. Mon. Wea. Rev., 107, 682-703.

                4 Maddox, R.A., C.F. Chappell and L.R. Hoxit. 1979. Synoptic and meso-a scale aspects of flash flood
            events. Bull. Amer. Meteor. Soc., 60, 1 IS-123.

                                                             B-3















                                      0.25-                                                                                        2000


                                                                                                                                 -1800


                                       0.2-                                                                                      -1600


                                                                                                                                 -1400


                                      0.15-                                                                                      -1200
                                                                                                                                         V

                                                                                                                                 -1000
                                                                               1K.

                                       0.1-                                                                                      -800


                                                                                                                                 -600


                                     0.05-                                                                                       -400


                                                                                                                                 -200


                                       0                                                                                       --a
                                           198t         1983          1985         1987         1989          1991         1993
                                                 t9a           1984          1986         1988         1990         1992
                                                                                   Year


                                                    -W- June TS      -)K - JLdy TS          kme Area  = My Area



                      Figure B-1. Monthly total ]-inch area measurements for June aeft bar) and July (tight bar)
                      and the 7hreat Score attained by NWforecasters.



                      B.2.1 QUANTITATIVE PRECIEPITATION FORECAST VERIFICATION SCHEME

                      Since 1961, NMC QPFs have been verified with an isohyetal areal verification scheme. This
                      system provides measurements of the areas of the forecast and observed (analyzed) isohyets, and
                      the area common to both, which is the correct area. These measurements are combined to
                      compute the Threat Score (TS):


                                                                     TS = AC/(Af + A0 - Ad


                                                    AC = Area Correct,

                                                    Af = Area Forecast, and

                                                    A0 = Area Observed.



                                                                                   B-4








            The analysis is based on available precipitation data including those in the River Forecast
            Centers' (RFC) precipitation files. The data are mapped to a grid which has a spacing that is
            1/6 of the Limited Fine Mesh (LFM) model (about 30 km). Manual forecasts (and model
            forecasts for recent years) are interpolated to this same grid.

            Figure B-1 shows the area covered by the observed 1-inch isohyet for each June and July since
            1981, and the TS attained by the NMC forecasters. Nationally, both June and July 1993 were
            quite ordinary in terms of overall area covered by the 1-inch isohyetal. analyses. The observed
            area over the United States for June and July 1993 was well within one standard deviation of the
            mean for these years.

            The TS over the entire United States for manual forecasts was quite good. In July, forecasters
            set a number of records for 0.5- and 1-inch forecasts, while in June one record was set and
            several other records approached. Figure B-2 shows the daily TSs for a 1-inch threshold for the
            manual and the Regional Analysis and Forecasting System (RAFS) model forecasts for June and
            July, 1993. This graph is for the entire United States. However, reference to the individual
            cases which follow will show that scores, if available for the central United States, would be
            even better. Figure B-2 clearly shows the advantage of forecaster interpretation over raw model
            forecasts. In fact, for both June and July, the verification program shows that the monthly
            average TS of the forecasters' 36- to 48-hour, R-inch forecast ("Day 2 forecast") is typically
            superior to the various models' Day I forecasts for the 1-inch isohyet.

            The NMC QPF verification program covers the United States as an entity and does not yet
            include comparison of the ETA  5 model raw QPFs. Nationally, the Day 2 forecasts are virtually
            unbiased (i.e., the ratio of forecast areas to observed areas is near unity). On the other hand,
            statistics show that the Day I area bias varies from 1.2 to about 1.35 from month to month.

            B.2.2 CASE STUDIES


            Three case studies were selected to focus on heavy rainfall events that contributed greatly to
            flooding problems. The discussions include a brief overview of the synoptic situation including
            the models' mass field forecasts. This is followed by a discussion of QPFs and a comparison
            with observed precipitation. Each day includes: (1) the analyzed 24-hour rainfall ending at
            12:00 UTC on the date indicated, with the analysis based on data retrieved from the RFC data
 4          files, (2) manual 24-hour QPFs for Day 1, and (3) 12- to 36-hour QPFs from the RAFS and
            ETA and AVNI models.






               ' ETA not an acronym. It stands for the Greek letter, e, which is used in the mathematical formulation of the
            vertical coordinate system used in this model.

                 AVN is not an acronym but stands for the AViatioN model.

                                                          B-5

















                               0.45-


                                 0.4-


                               0.35-


                                 0.3-

                              0
                              VO 0.25-

                                 0.2-


                               0.15-


                                 0.1 -


                               0.05


                                  0
                                           1  3   5   7   9 11 13 15 17 19 21 23 25 27 29
                                            2   4   6   8 10 12 14 16 18 20 22 24 26 28 30
                                                                     June



                               0.45-
                                 0.4-                                                             (b)

                               0.35-


                                 0.3-

                              0
                             LO 0.25-

                                 0.2-


                               0.15-


                                 0.1-


                               0.05-


                                  0
                                          1   3   5  7   9 11 13 15 17 19 21 23 25 27 2@ il
                                            2   4  6   8 10 12 14 16 18 20 22 24 26 28 30
                                                                     July


                                                        RAFS             Forecaster





                Figure B-2. Daily ]-inch Threat Scores for (a) June and (b) July for NWforecasters and
                forRAFS. 7he RAFSforecast for July 9 was not made.
                                                             - wn-




                                                                 B-6









            On the precipitation figures that are shown, analyzed isohyets are for 0.5 inch and multiples of
            I inch. The Day I manual forecast also includes a 0.25-inch isohyet, while the models include
            a zero line and central maximum values. Generally, on each day, the various model forecasts
            were extremely similar in their mass field forecasts and quite adequately represented the large-
            scale environment within which the precipitation events developed and were sustained. Thus,
            these fields are not shown.


            B.2.2.1 REVIEW OF THE JUNE 17-19 RAINFALL EVENT


            B.2.2.1.1 SYNOPTIC DISCUSSION


            By 12:00 UTC, June 17, 1993, an unseasonable and very strong 500-mb trough had moved
            southeastward across the Pacific Northwest to Utah. This upper-level system moved into the
            central Rockies (Colorado) by the following morning, and by 12:00 UTC on June 19, it had
            moved slowly out over the western Plains of Nebraska. By June 19, it had weakened but was
            still a potent shortwave regarding its capability to trigger major rainfall activity. During the
            24 hours before 12:00 UTC, June 17, 1993, low-level southerly flow of moist, unstable air had
            been reinforced by high pressure building southeastward from the Great Lakes to off the
            mid-Atlantic coast. In association with the major upper-level system, a surface low developed
            over the central High Plains, and a high pressure center settled in over Montana and the
            Dakotas with pressures above 1020 mb. All of these features combined to create a fairly strong
            frontal zone that generally stretched from southwest Nebraska into Wisconsin. This frontal zone
            began weakening on June 19 as the upper wave began to lose some of its strength.

            B.2.2.1.2 FORECAST AND QPF DISCUSSION


            The models handled the upper system quite well.           At the same time, they displayed
            characteristic errors in overdeveloping the surface low over the western High Plains. To
            illustrate this point, at 12:00 UTC, June 17, the observed sea-level pressure gradient between
            Chicago and Sioux Falls was 6 mb. The RAFS 36-hour forecast, valid at 12:00 UTC on
            June 17 for this sea-level gradient, was 10 mb and the AVN 11 mb. Further examples of this
            sort of error may be found in: (1) the RAFS prediction of a 1003-mb center near North Platte
            on the 48-hour forecast valid 00:00 UTC, June 18; (2) the AVN forecast of a 998-mb low near
            Grand Junction; and (3) the ETA forecast of a 1002-mb low in southeastern Colorado. The
            verifying RAFS analysis for this time had a 1013-mb low in southwest Wisconsin. Sea-level
            pressures were 10 16 mb at North Platte and 10 11 mb at Grand Junction and southeast Colorado.
            Despite these errors in the low-level field, the models did provide some useful circulation
            guidance. Even though the models had excessive low-level inflow, their QPFs did not
            overpredict precipitation.






                                                          B-7












                                                                                           *25\
                                                                 .5 1 2





                                                50
                                                                              Cb)                      (C)
                              4zZ:,50

                                                                         .5                       X
                                                                        .25



                                                  .......               05
                                                    (a)                                    .25


                                                                              (d)                      (8)


                Figure B-3. Rainfall for 24 hours ending 12:00 UTC on June 17. (a) observed, (b) manual
                forecast, (c) A VN forecast, (d) RAFS forecast, and (e) ETA forecast.



                Figure B-3 shows the array of observed and forecast rainfall maps for the first 24-hour period
                ending 12:00 UTC, June 17, 1993, with an analyzed 5-inch isohyet in Minnesota. The AVN
                12- to 36-hour forecast, Figure B-3(c), showed this as a relative minimum region; the RAFS axis
                of maximum precipitation, Figure B-3(d), was too far north; and the ETA, Figure B-3(e),
                appears to be the better model in positioning the precipitation center, although the orientation
                of the area is incorrect. The manual QPF, Figure B-3(b), showed the extent of the 1-inch
                isohyet too far north but was very good on the rainfall axis in Minnesota.

                Figure B-4 shows similar observed and forecast rainfall maps for the next 24-hour period,
                ending 12:00 UTC, June 18, 1993.           The outbreak from the previous day continued
                northeastward into Wisconsin and new activity developed over the central Plains, with several
                2- to 3-inch isohyets across Kansas and Nebraska. The RAFS forecast, Figure B-4(d), was wet
                but details were poor. Its maximum was in Iowa, exactly where the forecaster decided would
                be a good choice; the AVN forecast, Figure B-4(c), focused on South Dakota where observed
                amounts were less than 0.50 inch, while the Iowa-Minnesota portion was a reasonable forecast.
                The axis of the ETA in Figure B-4(e) was too far north in Nebraska but otherwise captured the
                observed axis quite well. The manual forecast, Figure B-4(b), was adversely affected by some
                of the model auxiliary output. As an example, the RAFS 24-hour vertical motion was + 12 over
                western Iowa valid at 00:00 UTC, June 18, which, when considered in conjunction with other
                                                            1E M
                                                            V
                                                                       '84
                                                                  k2 8
                                                                       _XO
                                                                       X





























                key model forecast parameters of strong southerly flow, strong low-level convergence and the




                                                             B-8








                                 50                                                 X181      RX
                                                                 4@5
                                                                3                      .25
                                                               2


                                           50                             (b)                       (C)

                                                                          e-W
                                           o504@@ 5       .5,.2                      25
                                               <Z)l         -      X1 86              .5
                                0           Q50               I

                                                (a)          .5                             .5.25
                                                             2
                                                                          (d)                        (e)


            Figure B-4. Rainfallfor 24 hours ending 12:00 UTC on June 18: (a) observed, (b) manual
            forecast, (c) AVNforecast, (d) RAFSforecast, and (e) ETA forecast.


            presence of a jet streak', was very misleading to a forecaster. The QPF discussion that was
            issued at 6:40 a.m. EDT on June 17 highlighted the region for both the Day 1 and Day 2
            periods, "Very dangerous and long duration flash flood event will continue the next couple of
            days over the central Plains ... Upper Mississippi Valley area as excessive rainfall continues to
            drench this rain soaked area. Expect two-day rainfall totals in some areas to approach ten inches
            by Saturday morning. " The plotted data showed some 2-day totals in central Kansas of
            6-7 inches with nearly 6 inches in the Texas Panhandle.

            The third day of this sequence is depicted in Figure B-5 and includes a rather large 1 -inch area
            stretching from the Texas Panhandle northeastward into Wisconsin, with a significant number
            of 2- to 3-inch areas. The RAFS 1-inch forecast in Figure B-5(d) was primarily over northwest
            Kansas-Nebraska into northwest Iowa. Only the Iowa portion was realistic. The AVN,
            Figure B-5(c), placed its precipitation mainly in northwest Kansas, which again was poor with
            an unrealistic round shape. This guidance was easily discounted by an experienced forecaster.
            The ETA precipitation forecast, Figure B-5(e), was focused primarily in Nebraska-Iowa,
            although it did forecast 0.50 inch across Kansas. The forecaster, Figure B-5(b), predicted a
            realistic-sized 1-inch area but focused the maximum in southwest Iowa where a small area
            exceeded 2 inches. The excessive rainfall discussion that was issued at 10:30 a.m. EDT,
            June 18, 1993, stated, "Another day of heavy rainfall is expected across the Plains from Kansas
            and Nebraska across most of Iowa.... A favorable position along the right rear quadrant of an
                                                                     -1
                                                                (4--5/--
                                                                3
                                                         j2  22
                                                                              1
                                                               5




































                  Jet Streak is a "local wind maxima embedded within the jet stream." (Palmen and Newton. 1969.
            Atmospheric Circulation Systems. Academic Press. [See Chaps. 4,5,8,9,13]).

                                                          B-9



















                                                                1  2                              .25
                                                                          -A              X26
                                                                            (b)                      (C)

                                                     0




                                                                                      X096     X126
                                                                            .25                '1
                                                    (a)                                           5
                                                                                                  .25

                                                                            (d)                      (e)


                Figure B-5. Rainfallfor 24 hours ending 12:00 UTC on June 19. (a) observed, (b) manual
                forecast, (c) AVNforecast, (d) RAFSforecast, and (e) ETAforecast.


                upper-level jet streak would provide upper-level divergence and lifting across the region ...
                    IUMUM rainfall is expected to be in the 3- to 5-inch range." Several reported values from
                central Kansas were 5-6 inches.


                B.2.2.2 REVIEW OF THE JULY 4-9 RAINFALL EVENT


                B.2.2.2.1 SYNOPTIC DISCUSSION


                The most notable rains fell during the three 24-hour periods ending at 12:00 UTC on July 5, 7,
                and 9. The series culminated when 4-7 inches of rain fell over the Raccoon River basin and
                flooded the Des Moines water treatment plant (see Section 6.9). The discussion of this episode
                will focus on these three heaviest days.

                A massive upper-level ridge was located over the eastern United States, and a mean trough was
                located over the High Plains and Rocky Mountains at 12:00 UTC, July 4 (similar to conditions
                shown schematically in Figure 3-6(a)). A strong cyclone developed to the lee of the Rockies
                and tracked into Manitoba as a potent jet streak moved across the Plains into southwestern
                Minnesota by 00:00 UTC, July 5. An unusually strong front associated with this low extended
                from Wisconsin southwestward across Iowa and Kansas to a much weaker surface low centered
                over the Texas Panhandle. A strong southwesterly pressure gradient existed between this low
                                                                                                  Ita
                                                                                     0 5 N25









                and the ridge in the east producing a strong low-level southerly jet. 850-mb winds of 20 m/s
                were located over Oklahoma, increasing to 20-25 m/s across Oklahoma and Kansas by
                12:00 UTC, July 5. These 850-mb winds were much stronger than the mean values for the


                                                            B-10








             June 5-July 19 period (Figure 3-8(a)). These winds transported abundant moisture northward
             with precipitable water values east and south of the front in the 1.8- to 2-inch range at
             00:00 UTC, July 5, and to above 2 inches across northern Missouri and southern Iowa by
             12:00 UTC, July 5.

             The weak southern low tracked to northeastern Kansas by 12:00 UTC, July 5. The center of
             low-level inflow and strongest warm advection shifted across Kansas into Iowa. During this
             same period, an area of strong upper-level divergence developed along the right rear entrance
             region of the jet streak associated with the low in Canada. This upper-level divergence
             strengthened and shifted northeastward into Iowa. Along this same axis, a swath of rain
             3 inches or heavier fell across Kansas, northwestern Missouri, and southern Iowa.

             The heavy rains that fell during the period ending at 12:00 UTC, July 7, also occurred along
             the right rear quadrant of a jet streak. A stronger-than-normal, low-level jet was present with
             20 m/s 850-mb winds directed into the frontal boundary across Missouri and Kansas. Strong
             low-level convergence associated with the low-level jet juxtaposed with strong upper-level
             divergence led to strong lifting along and just north of the front. A large area of rain 4 inches
             or heavier fell along the Missouri River in the state of Missouri.

             The last widespread episode of very heavy rain during this series occurred across Iowa and
             eastern Nebraska, where strong upper-level divergence associated with the jet was juxtaposed
             with a potent overrunning pattern. The heavy rainfall was again associated with a stronger-than-
             normal low-level jet, the entrance region of an upper-level jet streak, and an east-west front.
             Southerly 850-mb winds of 20 m/s advected 18 *C dew points into Nebraska by 00:00 UTC,
             July 9. Precipitable water values exceeded 1.8 inches along the front. The series ended when
             the surface low tracked eastward from Kansas to Wisconsin, and the low-level jet pushed east
             of the area.


             B.2.2.2.2 FORECAST AND QPF DISCUSSION

             Model mass field forecasts for the deep, closed 500-mb low over western North Dakota, with
             an attendant deep (observed sea-level central pressure at 12:00 UTC, July 4, was 984 mb)
             surface low, were very good. The south-southwesterly low-level flow was very well forecast
             by the models, as was the position and depth of the low. All models overforecast the rain in
             Montana, which was correctly scaled back by the forecaster.             The models all grossly
             underpredicted the rain which fell from Minnesota southwestward across the central Plains. The
             forecaster did a much better job of predicting this rainfall pattern. The ETA had the best model
             precipitation forecast.

             By 12:00 UTC, July 5, the "vertically stacked" 500-mb and sea-level low centers (occluded
             cyclone) had moved to southwest Manitoba where, again, all models were extremely good with
             the mass field forecasts. Major rains occurred from central Kansas northeastward through
             southeast Iowa. This was associated with weak waves along the surface front in Kansas, with
             the waves being fairly well indicated by all models. Of particular note in Figure B-6, which


                                                           B-11



















                                                                                                  .25
                                          50        so                    2

                                                                        3


                                                                                (b)                        (C



                                                                         .25


                                                                     X026  _X04
                                                                111@*25                          . 6--5
                                                                       X 26              T-                I-
                                                                                (d)                        (8)


               Figure B-6. Rainfallfor 24 hours ending 12:00 UTC on July 5: (a) observed, (b) manual
               forecast, (c) A VNforecast, (d) RAFS forecast, and (e) ETA forecast.


               shows the rainfall analysis for the 24 hours ending 12:00 UTC, July 5, is the poor effort by the
               models in predicting this rainfall event. The better model was the ETA (Figure B-6(e)), which
               showed about the right axis but underplayed the rainfall by about an order of magnitude.
               Despite the area of rainfall that did not occur in Wisconsin, the forecaster version was vastly
               superior to any model effort, as can be seen in Figure B-6(b).

               Although this discussion focuses on the Day I QPFs that are issued early each morning,
               additional excessive rainfall potential outlooks are issued periodically. On the afternoon of
               July 4, one of these forecasts was issued that outlined eastern Kansas, southeast Nebraska,
               northern Missouri, southern Iowa, and southern Wisconsin for potentially excessive rains. The
               explanatory discussion, issued at 2:30 p.m. EDT, July 4, stated, "...rains are likely to be locally
               heavy to excessive ... with 2- to 3-inch amounts possible in several hours and some 4- to 5-inch
               totals possible for the remainder this period. Heaviest rains are likely to lift northeast out of the
               southern/central Plains into Iowa-northern Missouri-southern Wisconsin by the end of the
               period. "

               The model circulation forecasts for the subsequent day (July 6) were very similar and strongly
               resembled the mean pattern shown in Figures 3-7(a) and 3-8(a). Again, the mass field forecasts
               were quite good in predicting the large-scale forcing environment. Even the model precipitation
               forecasts for this day (not shown), having failed to remotely catch the initial convective outbreak
                                                                                        H@\25@ 52
                                                              Efl                                          J






               on the previous day, were good, as the major rain event of the previous day worked its way
               toward the Great Lakes.




                                                              B-12






















                                                                                                 .2
                                                                      3                         .5
                                                                                                XOSS

                                          50                              (b)                      (C)

                                                                                  X
                                                                          2



                                                                                         -2
                                                 (a)


                                                                          (d)                      (e)


             Figure B-7. Rainfall for 24 hours ending 12:00 UTC on July 7. (a) observed, (b) manual
             forecast, (c) A Wforecast, (d) RAFS forecast, and (e) ETA forecast.


             The following 24 hours, ending at 12:00 UTC, July 7, had a major outbreak of convective
             rainfall across Kansas and Missouri with significant areas exceeding 5 inches in Missouri, as
             shown in Figure B-7(a). Two of the many parameters used by the forecasters to place and
             determine outbreaks of convective rainfall are the location of diffluent thickness patterns and
             favored 1000-500 mb thickness contours'. The ETA mass field forecast was better in this
             regard than the RAFS or AVN. The favored thickness region and a diffluent thermal pattern
             focused on eastern Kansas and Missouri. Despite that, the ETA provided some misinformation
             in the precipitation forecasts, as can be seen by comparing the ETA forecast in Figure B-7(e)
             to the observed pattern. The manually forecast QPF (Figure B-7(b)) featured an excellent axis
             and strong indications of excessive amounts. An excessive rainfall potential outlook discussion
             was issued at 10:32 p.m. EDT, July 6, for the remainder of the night until 12:00 UTC, July 7.
             This included a headline, "Life threatening flash flooding rains will continue to fall over the
             central Plains/mid-Mississippi Valley tonight." This narrative then went into the reasoning for
             expecting up to 5 inches of rain the remainder of the night over eastern Kansas and Missouri.

             The 24 hours ending at 12:00 UTC, July 8, saw a respite to the onslaught of major precipitation
             events. Important rainfall continued over eastern Nebraska into Missouri, but heaviest amounts
             were generally not much more than I inch. The RAFS incorrectly moved its rain forecast into
             the lower Great Likes; the AVN focused attention on eastern Iowa and Illinois, where rainfall
                                                                                   4
                                                                                                 '2

                                                                                                -5















































                  Bohl, V.G., and N.W. Junker. 1987. Using climatologically favored thickness to locate the axis of heaviest
             rainfall. Nat. Wea. Dig., 12, No. 3, 5-10.

                                                          B-13









                was less than 0.5 inch. The ETA placed its major rainfall area in Minnesota, where some rain
                fell, but the bulk of the rain was missed. The manually forecast QPF had a much better focus
                but also missed the details.


                During the night of July 7-8, major computer outages due to power failures prevented any model
                runs except for the LFM. Little model guidance was available for the QPF for the 24-hour
                period ending 12:00 UTC, July 9, which was one of the single, major, 1-day events
                (Figure B-8(a)). The manual Day I QPF for this 24-hour period strongly focused on Iowa
                (Figure B-8(b)). This forecast must be considered as excellent, especially for a forecast that was
                issued 12-15 hours before a convectively driven rainfall event. At 2 p.m. EDT, July 7, the
                update forecast also focused attention on Iowa. The accompanying discussion headlined, "The
                broken record continues for the central states... as yet another day of heavy to excessive rains
                are likely... especially from northern Kansas/eastern Nebraska into much of Iowa and northern
                Minois/southem Wisconsin." The text also included, "... there win easily be some 3-5 inch
                rains in spots... especially from northern Missouri/southern Iowa into west-central Illinois." At
                9:40 p.m. EDT, July 8, an excessive rainfall potential forecast read, "Classical textbook flash
                flood event unfolding over eastern Nebraska/Iowa this evening. Evening radiosonde observation
                data show tremendous upper features supporting extremely heavy rainfall through tonight.
                Surface boundary across the region will be the focus for convective development .... expect
                rainfall rates of 2-4 inches in a few hours with overnight totals nearing 10 inches in some areas
                of eastern Nebraska to central Iowa."











                                                                                      3
                                    0  50                                           2

                                                                          LL
                                                                                            (b)


                                                                  (a)




                              Figure B-8. Rainfall for 24 hours ending 12:00 UTC on July 9.
                                                                         Im








                              (a) observed and (b) manualforecast.




                                                              B-14










            B.2.2.3 REVIEW OF THE JULY 21-25 RAINFALL EVENT


            B.2.2.3.1 SYNOPTIC DISCUSSION

            A strong shortwave kicked eastward from the mean trough and lifted across the northern Rocky
            Mountain region on July 21-22, lowering the pressure to the lee of the mountains. By
            00:00 UTC, July 22, an area of lower pressure extended from eastern Colorado northward
            across eastern Wyoming and Montana into Canada.          This trough of lower pressure and a
            surface high over the western Great Lakes region, which formed in a region of confluent
            upper-level flow, combined to strengthen the southerly gradient across the Plains. The southerly
            winds associated with this gradient had two effects. They advected important moisture into
            Kansas and provided a favorable pattern for overrunning north of the east-west frontal boundary.
            A Maddox frontal-type heavy rainfall event that developed across Kansas in the area of strong
            isentropic lift produced over 4 inches of rain by 12:00 UTC, July 22.

            An even heavier event occurred during the next 3 days with over 15 inches of rain reported
            across southeastern Nebraska. This 3-day period is examined in a little more detail. The
            southerly gradient weakened slightly by 12:00 UTC, July 22, but reintensifled as another
            upper-level wind maximum punched eastward and helped induce cyclogenesis over western
            Kansas at 00:00 UTC, July 23. The position of the low on July 23 mirrors the position of the
            low for the mean pressure pattern during June 5-July 19 (Figure 3-6(a)). South of the front
            850-mb winds strengthened from around 10 m/s at 00:00 UTC, July 23, to 15 m/s at
            12:00 UTC, July 23. The magnitude of the southerly 850-mb winds during this period was
            significantly higher than the mean values during June 5-July 19 (Figure 3-8(a)). The stronger-
            than-normal southerly (15-20 m/s) low-level jet remained almost stationary through 00:00 UTC,
            July 25.

            The rather stationary character of the low-level jet can be explained by the presence of an area
            of low pressure to the lee of the Rockies through the entire event. The center of the low
            pressure tried to shift eastward across Kansas and Nebraska between 00:00-12:00 UTC, July 23,
            as one weak upper-level impulse shifted out of the Rockies; but the center reformed again over
            Kansas as a new upper-level wind max and associated shortwave approached later on July 23.
            The low deepened to 1004 mb over western Kansas by 12:00 UTC, July 24, as the next and
            even stronger shortwave started to move eastward from the mean trough. During the entire
            4-day sequence, the low tried to shift eastward across Kansas more than once but kept reforming
            westward as each new upper-level impulse ejected from the mean trough. The low did not move
            out of Kansas until after 00:00 UTC, July 25, when a major shortwave shifted eastward away
            from the mountains.


            An axis of very moist, unstable air stretched from the Gulf Coast states northward into Kansas
            at 12:00 UTC, July 21. Precipitable water values within this axis ranged from 1.8 across
            Kansas to over 2 inches along the Gulf Coast. By 12:00 UTC, July 22, the precipitable water




                                                         B-15









                     values had risen to over 2 inches across Missouri. The deep moisture led to K-indices' in the
                     36-40 range; and by 00:00 UTC, July 23, K-indices had risen to above 40 while lifted indices"
                     were -8 to -12. Both the K-indices and precipitable water values were higher than the mean
                     values that Maddox et al. found for frontal-type events.

                     Analyses of the moisture flux at 850 mb every 6 hours from 12:00 UTC, July 22, through
                     00:00 UTC, July 25 (not shown), indicated an axis of stronger moisture transport aimed at
                     southeastern Nebraska, where as much as 5 inches of rain was reported each day.

                     The strong low-level jet and strong thermal and moisture gradient associated with the front
                     resulted in a concentrated area of wet-bulb potential temperature" advection at 850 mb during
                     each 12-hour period of the event. The advection of warm, moist air at low levels acted to keep
                     the air mass unstable. The axis of heavy rainfall corresponded well with an axis of low-level
                     moisture convergence.

                     B.2.2.3.2 FORECAST AND QPF DISCUSSION

                     The initial outbreak in this sequence (not shown) occurred across central Kansas during the
                     nighttime period ending 12:00 UTC, July 21, 1993, with several reports of 3.5-4 inches. The
                     AVN did not predict much rain in Kansas, the RAFS defined some of the axis of rain in western
                     Kansas, and the ETA showed a small 1-inch isohyet with a fairly good envelope. On the other
                     hand, the I- and 2-inch isohyetal area estimated by the forecaster was a little too large.

                     The subsequent 24-hours ending 12:00 UTC, July 22, 1993, Figure B-9(a), showed some
                     individual totals near 5 inches in east-central Kansas and 3-3.5 inches in northeastern Kansas.
                     The AVN, Figure B-9(c), poorly defined the rainfall forecast; the RAFS, Figure B-9(d), made
                     a gallant attempt with a 1-inch isohyet in Nebraska and Iowa; and the ETA, Figure B-9(e),
                     confined its main rainfall to Nebraska. The forecaster, Figure B-9(b), correctly included eastern
                     Kansas, western Missouri, and southeast Nebraska in the 1-inch or greater area.





                        9 The following is the mathematical definition of the K-index.
                     (850-mb temperature) - (500-mb temperature) + (850-mb dewpoint) - (700-mb dewpoint depression):

                                                             K = T&io - T5w + Tdm - (r - Td)7w

                     (Note that 500-mb temperature is always. negative and thus makes a positive contribution to K-index.)

                         10 The lifted index is defined as the difference (in degrees Celsius) between the observed 500-mb temperature
                     and the temperature of a parcel of air if it were lifted adiabatically from a low level to 500 mb.

                        I I The wet-bulb potential temperature is the temperature an air parcel would have if cooled from its initial state
                     adiabatically to saturation and thence brought to 1000 mb by a saturation-adiabatic process. This temperature is
                     conservative with respect to reversible adiabatic changes.

                                                                             B-16














                                                               .5 2




                      0                                                                     162


                                                                          (b)                    (C)






                                                                    X20

                                                                    .25 .5                .5

                                                                          (d)


                   Figure B-9. Rainfall for 24 hours ending 12:00 UTC on July 22: (a) observed,
                   (b) manualforecast, (c) AVNforecast, (d) RAFSforecast, and (e) ETA forecast.


             Over the next 3 days, portions of southeastern Nebraska received rainfall amounts totaling
             10-15 inches. Since some observations are missing, it is difficult to know the exact totals. At
             this point, it is appropriate to quote from the Extended Forecast Discussion that was issued at
             3:30 p.m. EDT on July 20, 1993, "What this means is that over the next 5 days ... portions of
             especially Iowa, Kansas and Missouri could easily receive 6-12 inches of new rainfall". It is
             most unusual to mention specific amounts of rain in this discussion, which is usually issued by
             categories. For the specific 24-hour period ending July 23, 1993, the focus of the observed
             rainfall became southeastern Nebraska, Figure B-10(a). The three models did little to highlight
             this specific region, Figure B-10(c-e). The forecaster did but was a little bit too far east,
             Figure B-10(b); and overall, the forecast area was much too large, mainly with its southward
             extension through Missouri.

             During the 24-hours ending 12:00 UTC, July 24, individual amounts up to 6 inches were
             reported from the southeastern comer of Nebraska, Figure B- 11 (a), and important rainfall
             occurred in northern Illinois.       The models did a remarkably poor job--the RAFS,
             Figure B- I I (d), showed a large I -inch isohyet, which was virtually completely outside of the
             0. 5-inch analyzed area; the AVN's 0. 5-inch isohyet, Figure B- I I (c), was completely outside of
             the observed 0.5-inch area; the ETA, Figure B-1 I (e), fared a little better but not by much. The
             forecaster, Figure B- 11 (b), showed knowledge of a major event but was either a little too far
             north for the Nebraska event or too far west for the Illinois event. The forecaster also showed
             more knowledge of the events in the Dakotas than the models.




                                                           B-17








                            b5                   2   3
                       4,
                                                       (b)

                   50

                                            XD36 .25 56     X021  .2505


                                       (a)        loot

                                                       (d)            (e)


              Figure B-10. Rainfallfor 24 hours ending 12:00 UTC on July 23: (a) observed,
              (b) manualforecast, (c) AVNforecast, (d) RAFSforecast, and (e) ETAforecast.






                          50                                XOST 5 zi
                                        4     12   14      .26

                         50                                   X001

                                                       (b



                                               xt
                                5)         -.5,  X192         .5- @;13
                                                             .25  --

                                                .25                   X0
                                       (a)         lz@---@. I
                                                                       (e)

              Figure B-11. Rainfallfor 24 hours ending 12:00 UTC on July 24.- (a) observed,
              (b) manualforecast, (c) AVNforecast, (d) RAFSforecast, and (e) ETAforecast.
                                                   XO



                                                           E2










                                           B-18


















                                                                                          X

                                               50c:25  4              3r-        -.25 .5


                                                                           (b)                   (C



                                                                         Xid
                                                            .25
                                                                .5

                                                                                    _25


                                                                           (d)                   (e)


                Figure B-12. Rainfallfor 24 hours ending 12:00 UTC on July 25: (a) observed,
                (b) manual forecast, (c) A VN forecast, (d) RAFS forecast, and (e) ETA forecast.


             On the final day of the sequence, ending 12: 00 UTC, July 25, the AVN, Figure B- 12(c), finally
             produced some precipitation--a maximum of 2.33 inches near Duluth which, unfortunately, was
             in the analyzed minimum. Without going into each detail, the overall shape of the forecaster
             1-inch isohyet, Figure B-12(b), clearly showed emphasis over eastern Nebraska-Iowa, with a
             secondary focus in the Dakotas. This was a much better definition than any of the models.

             B.2.3 SUMMARY AND CONCLUSIONS ON QUANTITATIVE PRECIPITATION
                    FORECASTS AND MODELS


             The numerical models all did a good job of defining the large-scale forcing environment except,
             as noted, for a few small problems with respect to circulation forecasts. These are characteristic
             errors of each model, which forecasters are well aware of and which were compensated for in
             the manual forecasts. The details from the models, particularly with respect to precipitation and
             the timing of events, was less than desired. It has been shown that the NMC forecasters
             provided guidance forecasts that were overall substantially better than the models. Clearly, the
             24-hour QPFs, which are issued about 6 a.m. EDT about 12-18 hours in advance of the typical
             nocturnal convective precipitation events, do not completely capture all of the details that occur.
             Quotes from some of the excessive rainfall discussions and other narratives clearly showed,
             however, that the NMC forecasters were very aware of the events prior to their occurrence.
             The major flooding which occurred in the central United States was not the result of a daily
             heavy rainfall event/flash flood but rather resulted from the sum of many days of heavy rains,
             which correlate nicely with the data shown in Figures 3-7 and 3-8. Figure B-2 showed the TSs
             for the forecaster compared to the RAFS and clearly establishes the vital role that is played by


                                                            B-19

















                             0.35-

                                       ED.-


                              0.3-

                                        13 . . . . . . . . . .


                             0.25-




                          0   0.2-



                             0.15-




                              0.1-



                             0.05-                                                              ..........



                               0
                                      0.01                  0.25                  0.75                   1.5
                                                 0.1                    0.5                    1                     2
                                                                          Threshold




                             0.35-
                                                                                                                   (b)
                              0.3-




                             0.25-


                          IV
                          o   0.2-



                             0.15-




                              0.1-




                             0.05-




                               0
                                      0.01                  0.25                  035                    1.5
                                                 0.1                    0.5                    1                     2
                                                                          Threshold


                                                               ETA         RAFS --H-- ON



                  Figure B-13. Comparative model verification for the RAFS, ETA, and A VN in terms of the
                  Equitable 7hreat Score: (a) June 1993 and (b) July 1993.

                                                                        B-20









             the NMC forecaster in the QPF process. The continued updating of information also clearly
             showed the need, both prior to and during an event, for extensive and continued dialogue
             between field hydrologists, meteorologists, and NMC forecasters.

             During the discussion of the models, it was commonly noted that the ETA was perhaps the best
             of all the models in forecasting the rainfall patterns. Figure B-13 shows the different model
             gridpoint verifications for various rainfall thresholds. This figure uses the Equitable Threat
             Score, which is similar to the usual TS; however, this score removes any effects that might
             occur from a random-chance forecast. For very low frequency occurrence events, such as
             I inch of rain, the differences between the TS and the equitable TS are negligible. Figure B-13
             shows these scores for June and July for the AVN, RAFS, and ETA models. For the 1-inch
             forecast (also for other values), the ETA shows a clear edge over the other models.

             The NMC verification program will be undergoing some changes in the near future. As
             adequate resources become available, the ETA 24-hour forecast fields will be added to the
             verification statistics. The entire verification project will be ported to a workstation where
             regionalization of results and computation of additional and useful statistics will be possible.
             Finally, 6-hour forecasts will be verified in a similar areal manner as are the 24-hour forecasts.


             B.3 HYDROLOGIC ANALYSES OF SELECTED QUANTITATIVE
                   PRECIPITATION FORECASTS


             The preceding discussion amply demonstrates that significant skill often exists in QPFs.
             However, these forecasts are not currently used on a routine basis in river forecasting. This
             section examines some reasons why this is the case.

             NMC forecasters demonstrated an excellent ability to predict the general location and magnitude
             of extreme rainfall events experienced during The Great Flood of 1993. The skill level is
             highest at the synoptic scale"; considerable skill exists to scales as small as, or somewhat
             smaller than, a typical midwestern state. At these scales, individual convective events are not
             delineated. As shown above, the models and especially the forecasters are quite successful in
             identifying general regions of excessive precipitation. But, as discussed in the preceding
             sections, the positioning of the QPF centers is a continuing challenge for NMC forecasters.
             Limits in spatial and temporal resolution of observations, limits in numerical modeling
             capabilities, and limits in scientific understanding all make it impossible to provide highly
             specific QPFs (in terms of the positioning of the smallest rainfall centers).

             On the other hand, as indicated in Chapter 4, current river forecast modeling systems are
             designed for input on the basis of subbasins that are much smaller than the current ability for
             QPFs to specify. This inherent "scale mismatch" between the spatial scale, where QPFs show



                   A synoptic scale feature is one comparable in size to a mature, winter cyclone, or 600-1,000 miles.

                                                            B-21









                their best skills, and the scale needed as input to river forecast models will continue to be a
                challenge to the meteorological and hydrologic forecasters.

                Comparisons between QPF and observed precipitation in this section are based on volumes of
                water, eiler predicted or observed, in contrast with areal precipitation coverage above a
                threshold, as used in computing the TS. In addition, the comparisons in these sections are made
                at a finer resolution than the national scale used for the TS computations. Indeed, as shown in
                Figure B-1, on a national scale, June and July 1993 precipitation was quite ordinary--hardly the
                case in the upper Mississippi basin! A volumetric comparison is most meaningful in terms of
                input to hydrologic models: river forecasting is based essentially on an accounting system that
                tracks the volume of water as it flows through the basins being modeled/forecasted.

                Section B.3.1 compares QPFs with observed precipitation amounts for 21 selected days during
                this event, including all the days discussed in the case studies of Section B.2. This is followed
                by a more detailed comparison between QPF and observed precipitation at the scale of a state
                (Section B.3.2). Iowa was chosen for this purpose, as it was one of the hardest hit states, both
                in terms of precipitation and flooding. Finally, a briefer comparison between QPF and observed
                precipitation is made in Section B.3.3 for the basins contributing to the flooding that led to the
                closing of the water treatment plant in Des Moines. This case overlaps with both the QPF case
                study discussed in Section B.2.2.2 and the hydrologic case study in Section 6.9. 1.

                B.3.1 STATE-SCALE COMWARISON OF QUANTITATIVE PRECIPITATION
                       FORECASTS AND OBSERVED PRECIPITATION

                A rough comparison was made between: (1) NMC's operational (manually analyzed) 24-hour
                QPF (Day I forecast) and (2) NMC's manually analyzed observed 24-hour precipitation. As
                discussed above, the first analysis is NMC's best estimate of future precipitation based on the
                output from several models, as well as individual forecaster judgment and experience. The
                second analysis includes observed data from the NWS's surface aviation observation network,
                all automated data used by RFCs, and available cooperative observer data.

                Five major flooding episodes were chosen for analysis: (1) major-to-record flooding along the
                Minnesota River, (2) development of a significant flood crest on the upper Mississippi River,
                (3) propagation and intensification of the flood crest downstream into the middle Mississippi
                River, (4) development of a record flood crest on the Raccoon and Des Moines Rivers in and
                near the city of Des Moines, and (5) development of a near-record-to-record flood crest along
                the lower Missouri and middle Mississippi Rivers.

                Rainfall events that contributed to these flooding episodes during The Great Flood of 1993 were
                then defined: (1) June 17-19, (2) June 23-24, (3) July 1 - 11, and, (4) July 21-25. This resulted
                in a total of 21 days for which precipitation data were analyzed.

                For each day, two maps (NMC's operational QPF, and NMC's manual analysis of observed
                precipitation) were digitized for a nine-state area, including North and South Dakota, Nebraska,


                                                             B-22















                    70000




                    600000




                    500000-



                 .9 400000-
                 1-1

                 E
                 2300000
                 0


                 0  200000

                 A_
                 0  100000

                 a-


                         0
                                 6/17 6, 19 6 24/17/2 7/4 7/6 @/S @/16 i/21I i/2i i/25
                                    6/18 6/2     7     7/3   7/5   7/7   7/9 7/11 7/22 7/24                  1
                                                                Date


                                                          OPF = Obs.


             FIgure B-14. Comparison between precipitation volumes calculated from QPF and
             observations for the nine-state area impacted by 7he Great Flood of 1993.


             Kansas, Minnesota, Iowa, Missouri, Wisconsin, and Illinois. Prior to digitizing, one difference
             was noted between these two analyses: the QPF maps are analyzed beginning with a 0.25-inch.
             isohyet, while the observed precipitation maps are analyzed beginning with a 0.50-inch isohyet.
             Thus, to ensure an internally consistent comparison, the 0.25-inch isohyets on the QPF maps
             were not digitized. Therefore, all precipitation calculations were made only for the heavier
             amounts that fell or were predicted to fall within the 0.5-inch isohyet.

             After digitizing all 42 maps, both predicted and observed precipitation volumes--product of the
             precipitation depth (in inches) and the areal "tent (in square miles)--were calculated for each
             of the nine states affected by the flooding for each of the dates chosen.

             Figure B-14 shows predicted precipitation volume (QPF) compared to observed precipitation
             volume for each of the 21 "key" precipitation days, summed over the entire nine-state area. It
             is clearly evident that for these 21 selected dates, QPF was higher than the observed
             precipitation on all days except 3 (June 23, July 4, and July 7). A positive correlation (0.43)
             exists between the predicted and the observed.



                                                           B-23





Figure B-15. Ratio of QPF to observe precititation volumes for a summation over the
21 days indicated in the text.

Figure B-15 shows the ratio of perdicted precipitation volume (QPF) compared to observed
precipitation volume for the 21-day totals over each of the nine states, as well as the ratio for
the entire nine-state area.  The ratios range from 0.79 in North Dakota (the only ratio less than
one) to 2.7 in Iowa.  The overall average is 1.65. These ratios imply a bias higher than
indicated in Section B.2.1. One possible reason for this discrepancy is that  the sample used here
is quite small and may not be respesentative of longer-term statistics.  Also, the TS used by
NMC compares areas above a given threshold and does not reflect the spatial varations in 
magnitude within the selected threshold. The TS does not fully and accurately account for the 
volume of percipitation that results form precipitation amounts in excess of whatever threshold
is selected.  High-intensity cores, which account for substantial portions of the total storm
volume, are crucial in river forecasting, in particular for situations that repeatedly occur or


b-24








             persist for long durations. The record crests observed during The Great Flood of 1993 came
             about from the cumulative effect of many intense precipitation cores over a long period of time
             (see Sections 3.3.1 and 3.3.2).

             B.3.2 DETAILED COMPARISON BETWEEN QUANTITATWE PRECIPITATION
                    FORECASTS AND OBSERVED PRECIPITATION FOR IOWA

             The period of July I- 11, 1993, over the state of Iowa, was selected for more detailed study.
             Both the observed and the QPF isohyetal patterns were interpolated to a grid of discrete points
             spaced about I mile apart. At each of these grid points, the ratio of the QPF to observed
             precipitation was calculated. An example of the two input fields, as well as the resulting ratio
             field for July 9, is shown in Figure B-16. QPF (Figure B-16(a)) showed a southwest-northeast
             oriented maximum of 3 inches or more. The observed precipitation (Figure B-16(b)) showed
             a more east-west oriented axis, with peak values about double that indicated by QPF.
             Figure B-16(c) shows that the underprediction was focused in the west-central part of the state.
             At the same time, areas in both the northwest and southeast portions of the state experienced less
             precipitation than was indicated by QPF. The median of some 55,000 ratios of QPF to observed
             precipitation was 1.38, indicative of the fact that QPF overpredicted the total volume of water
             falling in Iowa on this day.

             It is interesting to note that this overprediction occurred in spite of QPF not identifying the
             observed rainfall centers above 3 inches (see Figure B-16(b)). While these centers show
             extremely high rainfall amounts, their areal extent is rather compact. On the other hand, the
             QPF 2-inch isohyet (Figure B-16(a)) covers much of the state, whereas the corresponding
             observed areal coverage is much smaller. In this example, QPF was too broad in its delineation
             of the 1- and 2-inch isohyets and was not able to delineate the centers of heaviest precipitation.

             Similar analyses were performed for each of the first I I days in July. The results are
             summarized in Figure B-17. The horizontal tick shows the median value of the more than
             55,000 grid point ratio estimates. The vertical line for each day encompasses the ratios falling
             between the 25th and 75th percentiles. Not shown on this figure are ratios for July 3, 7, and 10.
             On both July 3 and 10, no significant precipitation (greater than 0.5 inch) was observed in Iowa,
             while QPF values ranged from 0.25 to 2 inches on July 3 and from 0.5 to 4 inches on July 10.
             On July 7, there was no rainfall and QPF also did not predict significant rain. The average ratio
             for the 8 days shown is 1.6. If July 3 and 10 were factored in, this ratio would be higher still.
             Again, as in Section B.3. 1, this analysis suggests that QPF may systematically produce estimates
             that exceed observed values while at the same time failing to delineate intense rainfall centers.
             Only one day selected (July 4) had a median ratio significantly less than one.









                                                           B-25





















                                                                         2







                                                                                                                                                   (a)














                                                                                                                                                  (b)


                                                                         2.5                   1.8

                                                                                                    0
                                                                              2.5




                                                                                                                     1.2
                                                                                                      .8         1.80              .80

                                                                                                              .50





                                                                                                      .2

                                                                                                                                                  (C)


                                                       Figure B-16. Spatial variation ofprecipitation in Iowa on
                                                       July 9, 1993: (a) QPF, (b) observed, (c) ratio of QPF to
                                                       observed.



                                                                                                      B-26






















                 5






                 4












                 2-





                  - ---------- ------- ------- ----------- ------- --------- ------------ ---------------------------------------- ---------------------------------------- ......






                 0-

                                                            July


            Fligure B-17. Ratio of QPF to observed precipitation in lowafor each of thefirst 11 days in
            July and the average for the 8-day peilod (July 3, 7, and 10 excluded).



            B.3.3 COMIPARISON BETWEEN QUANTITATIVE PRECIPITATION FORECASTS
                   AND OBSERVED PRECIPITATION FOR SUBBASINS ABOVE DES MOINES


            Figure B-18 is a map of the subbasins used to compute river stage forecasts in the Des Moines
            area. (See also the case study in Section 6.9. L) Using both QPF and observed precipitation,
            volume estimates were made for July 8- R I over each of these subbasins. The comparison
            between these two estimates for the 4-day total is shown in Figure B-19. Again, the 4-day QPF
            total consistently exceeds the observed precipitation amounts for each subbasin; however, the
            positive correlation (0.98) between forecast and observed is remarkably good for the 4-day
            aggregation.   The average ratio over the entire 4-day period for all subbasins is RA.
            Figure B-20 shows the same volumetric ratios for the total precipitation that fell over all the
            basins shown in Figure B- 18 for each day of the 4-day period. On July 8, 10 and @ 1, QPF
            characteristically overforecasted the volume of water, especially on July 10 when QPF predicted
            substantial precipitation and no significant rainfall was observed. However, on July 9, the
            region received about double the volume of water predicted by the QPF.



                                                         B-27

















                                                                                                    . ... ...... ................ ......................      ......                                                       ------- ------------------------------- ----- -
                                            ........................... ......... . .. . ................................. - --- -- ................



                                                                                                                                                                . . . .                                 . . . . . .


                                                                                                                                                                                                               ST    14
                                                                                                                                                                                                                   R
                                                                                                                                                 EFW14:-.-':      .. .. ..




                                                                                                                                                                                                                                                                  .............. .
                                                                                                                                                                                                                                                        ..........





                                                                                                                                                                                                  -:0
                                                                                                                                                                                                         M4


                                                                       Miles
                                                                                                                                                      BAY14

                                                                                                                                                                                                                                         SAY14:
                                                         0                 10                20                                                                                                                             . . . . . . .
                                                                                                                                                                                                                                                                     ... . ....... .....
                                                      . ......                                             . ......... ...                                                                   7.



                                                                                                                                                                            . . . . . .                             ... .. .. ..
                                                                                                                                                                              RED14        Y..    .
                                                                                                                                                                                                                                             mw
                                                                                                                                                                                                                                                         @DIV1014

                                                                                                                -T-
                                                                          T
                                                                                                                                                                                                                     16

                                                                                                                                    ...................... .................... ....... . ..... .........
                                                                         Ar                                                                                    ... ........
                                                                                                  J-
                                                                      E

                                                              t

                                                      L

                                         Figure B-18. Subbasins used to calculate fiver stages in the Des Moines area.




                                         BA MONTHLY AND SEASONAL PRECIPITATION OUTLOOKS


                                         NMC also produces 30- and 90-day precipitation outlooks. (See Figure B-21 for examples.)
                                         Especially for major floods that last for months (or during prolonged droughts), use of such
                                         information could prove highly beneficial to long-term forecast accuracy. Sections 6.4.2 and
                                         6.5.2 showed the significant errors that resulted on the Mississippi and Missouri Rivers when
                                         extended forecasts did not include the June through August deluge. As shown in Figure B-21,
                                         the 30-day outlook for July clearly indicated increased chances of above-normal precipitation.
                                         Had this information been incorporated into the long-term forecast procedures, the degree of
                                         underestimation should have been reduced. A prerequisite for routine use of such outlooks in
                                         river forecasting algorithms is the systematic assessment of their accuracy.





                                                                                                                                                            B-28


Figure B-19. Comparison of 4-day (July 8-11) total volume of water computed from QPF
and observed precipitation for basins above Des Moines.  See Figure B-18 for location and
boundaries of each basin.

Current widely used operational procedures do not lend themselves to incorpration of this type
of probailistic outlook.  However, systems based on ESP techniques (13) could accommmadate
information such as that presented in these outlooks. ESP provides probability forecasts based
on historical hyfrometeorological data used with advanced (physcially based) meteorological and
hydrological models. Such forecasts will provide water and emergency managers with an ability
to incoporate forecast uncertainty in their decisions.

Techniques could be developed to condition the probability distribution of the historical series
of hydrometeorological data by weighting the data series according to the outlook patterns. This
would enhance long-term river forecasts. While these techniques would not predict all-time
record flooding levels prodced by future meteorological events well outside the historical range,
such as obeserved in The Great Flood of 1993, they could produce forecasts that indicate


(13) Day, Gerald N., and Edward J. VanVlargan. 1983. The use of hydrometeorological data in the NWS
Extended Streamflow Prediction program.  Fifth Conf. Hydromet., Tulsa, Oklahoma, America Meteorological
Society.

B-29












                         25000-


                     171
                     *E
                       20000 -


                     x


                        15000-



                     E
                     2
                     0  10000-
                     C
                     .2
                     2
                         5000-


                     0-


                                           7/8            7/9            7/ 10           7/11
                                                                  Day

                                                            OPF = Obs.


                Figure B-20. Comparison of daily total volume of water over 11 basins above Des Moines
                computed from QPF and observed precipitation.


                significant probabilities of flood levels approaching record levels of the past. Incorporation
                of long-term precipitation outlooks into river forecasts within an ESP framework could
                provide credible ranges of future flood stages, allowing emergency management agencies
                at all levels of government to better prepare for flooding. The probability range of the
                forecast would provide an indicator of the level of risk. The technique would also be highly
                effective in identifying the likelihood of when the flood would recede. Finally, this same
                system would be quite useful to water managers. They could make risk-based decisions in
                their operation of water management structures, such as reservoirs, that could optimize use
                of limited water supplies, especially in areas such as the western United States. It is
                estimated that nationwide implementation of an advanced hydrologic modeling system based
                on ESP techniques would cost less than $15 million per year and would save the Nation
                more than $100 million per year.







                                                            B-30














                                                  B


                                            0          5



                                3
                                           3




                          55
                          70


                                  +35


                                  PRECIPITATION        (a)








                          CIO                0



                                    ,bowl




                                                  3
                                                3


                                                       3


                                      3
                            32
                                   11 . .... ........


                           PRECIPITATION PROBABILITIES  (b)


                      FIgure B-21. &wnples of NMC precipitation
                      outlooks for (a) 30 days (July 1993) and
                       (b) go days (July-September 1993).


                                       B-32










                 B.5 SUAINLARY AND CONCLUSIONS


                 NWS river forecasting models currently used for the upper Mississippi and Missouri River
                 basins do not routinely and objectively take advantage of QPF. One reason for this is limitations
                 in the forecast system infi-astructure. There is now no efficient way to translate QPFs into
                 subbasin input quantities needed by the river forecast models. This function, along with
                 preparation of detailed observed precipitation estimates based on in situ gages, radars, and
                 satellite information, will be accomplished by the Hydrometeorological Analysis and Support
                 functions at each RFC in the modernized Weather Service.


                 A more significant problem with incorporating QPF into river forecast models is the inherent
                 scale mismatch. As discussed above, the scientific complexity in predicting rainfall from small-
                 scale convective cells makes detailed positioning of high-intensity rainfall centers beyond our
                 current scientific capabilities. This problem increases as both the duration of the forecast
                 interval and target area (i.e., subbasin) decrease and as the forecast period moves further into
                 the future. The limited analyses in Sections B.3.2 and B.3.3 suggest that, in spite of biases
                 (which are probably tractable), the random variation of QPFs from day-to-day and/or basin-to-
                 basin can be quite large (see Figure B-20). This creates a significant challenge to incorporate
                 QPF information into the current river forecast system. Despite this challenge, it is important
                 to use the QPF in hydrologic forecasting since QPFs demonstrated a high level of skill in
                 predicting the persistence of unprecedented precipitation events that led to The Great Flood of
                 1993. As discussed above, the ESP framework is key to accomplishing this task.

                 Through the ESP approach, it may be possible to overcome the limitations in current application
                 of QPF to river forecast procedures. As outlined in Section B.4, the ESP approach is ideally
                 suited to incorporating outlooks such as those routinely prepared by NMC. If reasonable
                 uncertainty levels can be inferred for 3- to 5-day and 6- to 10-day categorical outlooks, the ESP
                 framework could also be used to incorporate this information into river forecasts. Finally, if
                 the scale mismatch between QPF and hydrologic models can be better characterized in
                 probabilistic terms, it may be possible to describe the effect of smaller scale precipitation
                 fluctuations around the QPF on the uncertainty in future hydrologic conditions.

















                                                               B-32









                                                   APPENDIX C


                                  USE OF SATELLITE DATA DURING
                                       THE GREAT FLOOD OF 1993


                                        Rod Scofield and Rao Achutuni




            C.I. GEOSTATIONARY SATELLITE EWAGERY

            The geostationary satellite has the unique ability to observe the atmosphere and its cloud
            cover from the global scale down to the storm scale, frequently and at relatively high
            resolution, through its instrument complement of sounders and imagers. This makes the
            geostationary satellite an important tool for weather analysis and forecasting including
            diagnosing flash floods. Floods are multiscale and concatenating events which occur on
            scales from "global scale" to "synoptic scale" to "mesoscale" and finally to the "storm or
            event scale." Conceptual models and satellite features have been developed to diagnose
            systems on all meteorological scales that, through the process of multiscale interaction, lead
            to flash floods.


            On the global scale to synoptic scale, the 6.7 /Am water vapor imagery detects northward
            movements or surges of mid- to upper-level moisture from the tropics into the mid-latitudes.
            These surges are called water vapor plumes and are usually associated with large-scale
            circulations (Scofield, 1991, 1990b; Thiao, 1993). As the plumes move northward into the
            United States, they often become coupled with low-level, moist, unstable air and upper-level
            forcing mechanisms, such as jet streaks'. These interactions often result in flash floods.
            Such was the case during the Upper Midwest floods of this past summer where water vapor
            plumes persisted on the back side of the subtropical ridge (located over the eastern United
            States), and jet streaks repeatedly occurred on the western and northern boundary of the
            plume. An example of a water vapor plume and rather large Mesoscale Convective System
            (MCS) over Iowa and Missouri (at M) is shown in Figure C-1. Jet streaks were located over
            Kansas and Minnesota. Over northern Missouri, 5-7 inches of rain occurred with this
            system.








                ' Jet streak is a "local wind maxima embedded within the jet stream." (Palmen and Newton. 1969.
            Atmospheric Circulation System. Academic Press [see Chaps. 4,5,8,9,13]).

                                                           C-1







                            0-2-01 0 1 JL93 193-4ZA'                      131      2 320   --1 CC3





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                                               714, 4.





                     Figure C-1. 6.7 lim water vapor imagery for 9 p.m. CDT, June 30, 1993 (02:00 UTC, July 1). Note water vapor
                     plume aabeled PLUME on photo) and Mesoscale Convective System aabeled M).








            On the synoptic scale and mesoscale, the water vapor plume along with the high equivalent
            potential temperature (0J air can produce MCSs if acted upon by a forcing mechanism, such
            as a jet streak. A water vapor plume and an accompanying jet streak (at J-S) are helping to
            produce the MCS (at M) and flash floods over Minnesota in Figure C-2.

            For this same event over Minnesota, on the mesoscale and storm scale, the enhanced infrared
            imagery (Figure C-3) depicts a rapidly growing MCS (at A). This MCS merges with smaller
            convective systems to the west (at Q; the result is a back-building MCS (at B). Back-
            building MCSs often prolong the heavy rainfall and cause flash floods, e.g., 5-7 inches of
            rain over southern Minnesota. MCSs, such as the one over southern Minnesota, often feed
            back to the larger scales by producing outflow boundaries. In this case, the visible imagery
            shows that an outflow boundary was produced ("dashed lines" in Figure C-4). This helped
            to create new convection and continued the heavy rainfall over Iowa and Minnesota. On the
            storm scale, the intensity, movement, and propagation of thunderstorms are used to
            determine how much, when, and where the heavy rain is going to move during the next
            0-3 hours.

            The Synoptic Analysis Branch (SAB) of the National Environmental Satellite, Data and
            Information Service (NESDIS) makes satellite rainfall estimates nationwide whenever heavy
            rains are threatening to produce, or are already producing, flash flooding (Borneman, 1988).
            SAB meteorologists monitor the growth trends of thunderstorms on the GOES-7
            geostationary satellite imagery using techniques developed by Scofield and Oliver (1977,
            1987) to quantify rainfall estimates. In support of the National Weather Service (NWS),
            estimates are disseminated over the Automation of Field Operations and Services (AFOS)
            system in an alphanumeric message called "SPENES" directed to the affected area through
            the alarm/alert feature of the AFOS system. In addition to the estimated amounts of rainfall,
            the message also contains information on trends as seen in the satellite imagery and short-
            range forecasting (nowcasting) information. Estimates are done on the interactive Flash
            Flood Analyzer (IFFA) that is part of the VAS Data Utilization Computer (VDUC) system
            located at the National Oceanic and Atmospheric Administration (NOAA) Science Center in
            Camp Springs, Maryland. IFFA-derived graphics products are sent to the River Forecast
            Centers (RFQ in Fort Worth, Texas, and Slidell, Louisiana.

            Throughout June, July, and August of 1993, large- and small-scale convective systems passed
            over the Midwest almost daily contributing to the devastating flooding. SAB precipitation
            meteorologists logged over 900 hours during this period monitoring the convection for heavy
            rainfall and issuing satellite rainfall estimates. Around 400 satellite rainfall messages were
            issued to the NWS Central Region, most of which were for rains that contributed to the
            flooding. This represents 50-80 percent of the total workload for the SAB precipitation
            meteorologists for that 3-month period.      There were 29 cases documented where over
            5 inches of rain were estimated in a 24-hour period over the Upper Midwest. Statistics
            computed over the past several years have shown that the current technique underestimates
            extreme rainfall events (5 inches or more in a 24-hour period) and overestimates the lighter
            events (2 inches or less). However, these statistics are computed from relatively dense rain


                                                         C-3














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                     Figure C-2. 6.7Am water vapor imagery for 9 p.m. CDT, June 16, 1993     (02:00 UTC, June 17).  Note water
                      vapor plume aabeled PLUME on photo), Mesoscale Convective System Oabeled M), and jet streak qabeled JS).








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                                         Aft,

                                                                              (b)





















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                    Figure C-3. Enhanced    inftared imagery (MB curve) during   the evening
                    hours of June 16, 1993: (a) 7.30 p.m. CDT (00.30 UTC, June 17),
                    (b) 9.30 p.m. CDT (02:30 UTC, June 17), and (c) 11:30 p.m. CDT (04.30
                    UTC, June 17). Note growh and movement of one Mesoscale        Convective
                    System (MCS) gabeled A), development of a second MCS (labeled Q, and
                    merger of two MCSs aabeled B).


                                                      C-5

















                                                                             MI
                                                                             (a)



                                                                  0

















                                                                             (b)
















                                         ... .............








                                                                             (C)


                              Figure C4. Visible    imagery  during the morning hours of
                              June 17, 1993: (a) 9 a.m. CDT (14.00 UTC), (b) 10 a.m.
                              CDT (15:00 UTC), and (c) 11 a.m. CDT (16:00 UTC). Note
                              outflow boundaries (shown as dashed lines) produced by the
                              previous evening's Mesoscale Convective System.


                                                          C-6








            gages that are not available in real-time. Therefore, these satellite estimates are useful as a
            "first guess" for determining the severity of a situation. Nevertheless, the estimates need to
            be validated and calibrated.

            The SAB generated 38, 101, 206, and 95 satellite rainfall estimates for the Central Region in
            May, June, July, and August, respectively. May is included for comparison to show the
            period prior to the onset of the heaviest rains.

            Satellite rainfall estimates are also passed on to the National Meteorological Center (NMC)
            meteorologists in the Heavy Precipitation Unit for input into their quantitative precipitation
            forecasts. The SAB has recently collocated with the Heavy Precipitation Unit to form the
            National Precipitation Prediction Unit (NPPU). During July and August, the NPPU provided
            the Federal Emergency Management Agency and the White House with daily briefings on the
            status of the heavy rains and flooding. The IFFA rainfall estimates and significant SPENES
            messages were included in these briefings.

            Examples of an IFFA-derived graphic, text messages, and an analysis based on rain gage
            observations for a flash flood event over Missouri are shown in Figures C-5, C-6, and C-7,
            respectively. The IFFA graphic shows a large area of heavy rain from eastern Kansas to just
            west of St. Louis. Estimates ranged 5-8 inches over this area with a maxima of 8.5 inches in
            Bates County, Missouri (extreme western Missouri). The Satellite Precipitation Messages
            (SPENES) in Figure C-6 mention the presence of training and back-building MCSs over
            western Missouri and a 7-7.5 inch estimate over Bates County between 12:00-21:00 UTC.
            As mentioned above, back-building MCSs are frequently associated with flash floods.
            Rainfall observations in Figure C-7 were comparable to the IFFA estimates, except they
            were somewhat lower, especially over western Missouri. The Weather Surveillance Radar
            1988 Doppler (WSR-88D) estimates (Figure C-8) show a local maximum just west of
            St. Louis of 8-9 inches of rain.     Satellite estimates and rain gage observations indicate
            rainfall amounts of 7 inches near this same location.


            In the spring of 1994, NOAA's next generation of geostationary satellites (GOES I-M) is
            scheduled for launch. The first satellite in that series in GOES 1. The GOES I-M system
            promises to be a significant advancement in geostationary environmental satellite capabilities,
            especially for mesoscale prediction such as flash floods. All major portions of the system are
            new including: (1) improved multispectral imaging capability and (2) separate sounding and
            imaging systems.     For application to flash flood diagnostics and prediction, the higher
            resolution IR (10.2-11.2 Am) and 6.7 Am water vapor data will lead to better detection of
            features that lead to heavy precipitation. Low-level water vapor can be diagnosed from the
            difference between the 11.2 Am and the 12.7 Am bands (the "split window"). Precipitable
            water, stability, and temperature can be derived from the satellite soundings. Winds at
            various levels can also be computed from the satellite data. GOES I in combination with the
            polar satellite data (discussed in the next section) places satellites at the very heart of
            understanding mesoscale weather development such as flash floods.



                                                          C-7
























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                                                                     ------------






                       FTgure C-5. 24-hour satellite-derived (IFFA) precipitation estimate for portions of central Kansas and central
                       Missouri for the period ending at 7 a. m. CDT (12:00 UTC) on July 7, 1993.



















                        SATELLITE PRECIPITATION ESTIMATES...                         DATEMME/ 7/06/93 1935Z
                        PREPARED BY THE SYOPTIC ANALYSIS BRANCHNESDIS TEL (301) 763-8444
                        VALUES REFLECT MAX OR SGFNT ESTS. OROGRAPHIC EFFECTS NOT ACCTD FOR.
                        REFER TO T?B*375 FOR DETAILS.                           LATEST DATA USED: 06190OZ SJK
                        LOCATION                                                                      RATE TOTAL                       TIME
                        E. KS CNTYS...
                          N0E ALLEN/EXT NW BOURBON/SE ANDERSEN                                         1.00         3.3"-3.8"          15-196
                          E LINN                                                                      1.0"         4.6" SE LINN
                        W CENTRAL MO...
                          W/NW BATES                                                                  1.1"         5.0"-5.5" C BATES
                          C/SW CASS                                                                   1.0"         4.3" SE CASS
                                                                                                                   3.5 S CENTRAL CASS


                        REMARKS ... REDVLPMT ON BACK END OF MCS GIVING ADDTL HVYS RAIN TO E CENTRAL
                        KS INTO W CENTRAL MO ... TRAINING AND BACK BUILDING OVER E CENTRAL KS/
                        W CENTRAL MO ... WILL MAKE FF POTNEITAL HIGH DURING THE NXT 3 HRS ... WILL
                        CONTINUE TO MONITOR WITH NXT MSG AFTER 212Z PIX...











                        SATELLITE PRECIPITATION ESTIMATES... DATEMME 7/06/93 2135Z
                        PREPARED BY THE SYOP7.1C ANALYSIS BRANCH/NESDIS TEL. (301) 763-8444
                        VALUES REFLECT MAX OR SGFNT ESTS. OROGRAPHIC EFFECTS NOT ACCTD FOR.
                        REFER TO T6?B-'375 FOR DETAILS.                                 LATEST DATA USED: 06210OZ SJK
                        LOCATION                                        3 HR RATE               TOTALS                                 TIME
                        W CENTRAL MO ... qE KS                               18-216Z
                          W/SW CASS(MO)                                       3.0"              6.0"-6.5"EXT S/SW                      12-216
                          EXT E MIAMI(KS)                                     2.6               5.0"-5.5"EXT SE MIAMI
                          NE LINN(KS)                                         1.5'              5.0"-5.5"
                          NW BATES (MO)                                       2.0"              7.0'-7.0" C BATES
                          EXT S JACKSON TO SW JOHNSON(MO)1.5-
                          NW HENRY TO SW LAFAYETE                            1.6
                          N BENTON TO MILLER TO S FRANKLIN(MO)                                  0.9'-1.2"                              18-216
                    REMARKS ... ONE LAST CONVECTIVE CELL SHUD TRAIN ACROSS SOUTHERN BACK PORTION
                    ON AREA OF CONVECTION THAT HAS BEEN AFFECTING E KS/W CENTRAL MO PAST SEVERAL
                    HRS ... WILL BE MONITORING AREAS FROM JUST SW/SSE OF MKC THRU C MO TO S IL
                    FOR HVY RAIN AND 2F POTENTAL OVER THE NXT 3 HRS...





                  Figure C-6. Satellite precipitation messages for 2:35 p.m. CDT (1952 UTQ and
                  4:35 p.m. CDT (241:35 UTC), July 6, 1993.

                                                                                    8-9
 































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                                                                                                                                            -----------



                                                       2              2






                       Figure C-7. Analysis of total observed precipitation for the 24-hour period ending at
                       7 a.m. CDT (12: 00 UTC) on July 7, 1993.







                                                                                          C-10













                                                                                                                 --STN PRECIP 00 STP
                                                    G'T UM-11 A IFG                                                 124 NN 1.1 Nr RES
                                                                                                                   C?/O?-,qS 12%3c







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                        Figure C-8. St. Louis, Missouri, WSR-88D        image shovving stonn   total precipitation ending at 7-32 a.m. CDT
                        (12:32 UTC) on July 7, 1993.









               C.2. POLAR-ORBITING SATELLITE EWAGERY

               The NOAA/NESDIS scientists used passive microwave data from the Defense Meteorological
               Satellite Program (DMSP) F-10 and F-11 series of polar-orbiting satellites to monitor the
               flooding in the Midwest.

               Satellite imagery from polar-orbiting earth resource satellites, such as SPOT (France) and
               Landsat (USA), can be used to provide imagery of flood extent with spatial resolutions of
               10 m and 30 m, respectively. Such high-resolution data are extremely useful in assessing the
               extent of damage caused by natural disasters. Corbley (1993) provides examples on the use
               of data from Landsat Thematic Mapper (M bands 7,4,3 for monitoring The Great Flood
               of 1993.


               Thermal infrared data from the Advanced Very High Resolution Radiometer (AVHRR)
               instrument on board the NOAA-N series of satellites can also be used to examine flooding at
               spatial resolutions of up to 1.1 km. It is useful to compare images of the area of interest
               prior to and during the flood.

               One of the key deficiencies of environmental satellites, such as the NOAA, Landsat, and
               SPOT series of satellites, is that they cannot see through clouds. The presence of clouds
               makes it very difficult to monitor land surface characteristics using visible (VIS) and thermal
               infrared (M) channel data. It is possible to overcome this limitation to some extent by
               compositing several images of the area of interest and selecting the relatively cloud-free
               pixels. However, in situations such as that in Iowa (where during the summer of 1993 it
               rained 40 out of 43 days), the applicability of VIS/TIR techniques for large area flood
               monitoring is somewhat limited by the requirement of relatively cloud-free days.

               Clouds and ice crystals present in cirrus are "transparent" to radiation emanating from the
               earth in the microwave (MW) frequencies. The MW radiation still cannot penetrate rain.
               However, the MW techniques do provide better cloud and vegetation penetration than optical
               waves (Ulaby et al. 1981).

               The Special Sensor Microwave/Imager (SSM/1) instrument on board the DMSP series of
               satellites measures passive MW radiation in seven frequencies: (1) 19.35 V (vertically
               polarized) GHz, (2) 19.35 H (horizontally polarized) GHz, (3) 22.235 V GHz, (4) 37.0 V
               GHz, (5) 37.0 H GHz, (6) 85.5 V GHz, and (7) 85 H GHz (Grody 1991).

               Large bodies of water (such as lakes), as well as flooding following heavy rainfall events,
               lower the brightness temperatures at all MW frequencies. McFarland and Neale (1991) used
               a threshold of VK for the difference between the 22.235 V GHz and the 19.35 V GHz
               brightness temperatures to identify large bodies of water and flooding after heavy
               precipitation events. Scattering by clouds containing large water droplets and/or ice lowers
               the brightness temperature, particularly at the higher frequencies.



                                                           C-12










            C.3 SOEL VMTNESS MEX

            The experimental, NOAA-developed Soil Wetness Index uses the difference between the
            85 GHz and 19 GHz horizontally polarized data from the SSM/I on board the DMSP
            satellites. The brightness temperature difference values in the range 10-30*K are then scaled
            between 0-255 and displayed. The experimental product is extremely useful for monitoring
            the areal extent of flooding under nearly all weather conditions, excluding actively
            precipitating cloud areas.

            The Soil Wetness Index is used by NOAA to monitor soil wetness and flooding.
            Progressively wet ground conditions are depicted in shades of green, orange, and red,
            respectively (Figure C-9). Flooded or puddled land surfaces and large water bodies are
            shown in shades of blue. One can look for persistence of high soil wetness values in order
            to infer potential flooding conditions. Precipitation failing on already saturated soil can
            result in additional flooding. The images are composited with time to identify the flooded
            areas that may otherwise be obscured by precipitation.

            The SSM/I channel data are readily available on a near real-time basis on the VDUC system
            located within the NOAA Science Center in Camp Springs, Maryland. The experimental
            Soil Wetness Index is being produced operationally on the VDUC system and is available in
            both digital and hard copy (color). SAB is already using it on an operational basis.

            Figure C-9 shows the Soil Wetness Index for four different time periods. The June 6, 1993,
            imagery shows extremely wet to puddled soil conditions in southeastern Nebraska, much of
            Iowa and east-central Illinois. The flooding situation continued to persist in Iowa through
            June and late July. The flooding in Iowa reached a peak around July 15, 1993. The July 15
            image also shows flooding in Kansas and along the Missouri River near St. Joseph, Kansas
            City, and Boonville. By July 20, surface waters were receding across farmlands in the
            Midwest.    The Missouri and Mississippi Rivers and their tributaries continued to crest
            through August. The July 29 image shows flooded areas along the Missouri and Mississippi
            Rivers. Surface water detectable by the SSM/I sensors had largely disappeared in Iowa by
            this time.


            The composite image of July 14, 1993, (Figure C-10) was used by Vice President Gore in a
            nationally televised press conference to illustrate the areal extent of the midwestern flooding.
            He said, "It is as if another Great Lake has been added to the map of the United States."
            Although the area is not really a lake, it does depict land surfaces that are either heavily
            puddled or almost submerged. Figure C-10 shows that large areas in Iowa, Illinois, Kansas,
            Missouri, Nebraska, Minnesota, and South Dakota were severely impacted by flooding at
            that time.


            The Soil Wetness Index can also be used to monitor coastal and inland flooding due to
            hurricanes. The index was able to identify flooded areas in Florida after the passage of
            Hurricane Andrew.


                                                          C-13

















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                                                     ti ,                   N 0 A A Z t- I ES:, C' IS-il 0 R. R                         I

                          Figure C-9. The SSMII Soil Wetness Indexfor.- (a) June 6, (b) July 15, (c) July 20, and (d) July 29, 1993.









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                                                                       JULY 1      1993


                                               EXTREMELY WET                                         FLOODED
                      44, ;,:W@m






                    Figure C-10. 7he SSMII Soil Wetness Indexfor July 14, 1993.









                The Soil Wetness Index is an extremely useful tool for monitoring large area flooding. In its
                present form, the index values have been scaled to identify large geographic areas that are
                either extremely wet, puddled, or flooded. The puddled and flooded fields are indicated in
                various shades of blue. However, one has to look for persistence with time of these features
                in order to infer flooding.


                CA SUGGESTIONS FOR FUTURE STUDY OF SATELLITE
                     "IFFA-DERIVED" PRECIPITATION ESTIMATES


                Additional research is needed to better use the satellite "EFFA-derived" precipitation
                estimates and the Soil Wetness Index.      This will enhance our understanding of future
                hydrometeorological events. Listed below are suggestions for future studies for the satellite
                "EFFA-derived" precipitation estimates and for the Soil Wetness Index.

                       1.     Since IFFA normally underestimates extreme rainfall, an objective correction
                              factor must be derived that will automatically enhance the estimates during
                              extreme rainfall events.

                       2.     Validate and calibrate the estimates using doppler radar estimates and dense
                              rain gage networks.

                       3.     Integrate the estimates with the doppler radar estimates and rain gages.

                       4.     Perform sensitivity studies to determine how to best insert the satellite
                              estimates into hydrological models.

                       5.     Use satellite estimates to help validate and initialize NMC's Numerical
                              Weather Prediction Models.



                C.5 SUGGESTIONS FOR FUTURE STUDY OF SOIL WETNESS INDEX

                       1.     Archives of SSM/I channel data are available in-house within the Office of
                              Research and Application for the period 1991 to present. It will be very
                              useful to develop a climatology of the index over this period.

                       2.     Compare the satellite-derived Soil Wetness Index with conventional indicators
                              such as the Palmer Drought Index (PDI) and cumulative rainfall.

                       3.     It may also be very useful to compare the Soil Wetness Index with the NOAA
                              AVHRR channel data, especially the thermal channels.




                                                           C-16









                   4.      Calibrate the index with ground-truth data (on field conditions) available
                           weekly from the U.S. Department of Agriculture field offices in the impacted
                           areas. The depth of flooding may be difficult to infer since the SSM/I
                           instrument gets saturated even with the presence of a thin film of water on the
                           surface. The index should be modified to flag desert areas.

                   5.      Establish criteria for the proper interpretation of the index and develop a
                           User's Manual for training purposes. The index could then be validated by the
                           RFCs and other Weather Service Forecast Centers during the 1994 season.

                   6.      Investigate procedures for integrating the Soil Wetness Index into hydrological
                           models, such as over the Mississippi River basin.


            C.6 REFERENCES


            Borneman, R. 1988. Satellite rainfall estimating program of the NOAA/NESDIS Synoptic
                   Analysis Branch. Nat. Wea. Dig., 13, 2, 7-15.

            Corbley, K.P. 1993. Remote sensing and GIS provide rapid response for flood relief.
                   Earth Observation Magazine, September 1993, 28-31.

            Grody, N. 1991. Classification of snow cover and precipitation using the Special Sensor
                   Microwave/Imager. Jour. of Geophys. Res., 96, 7423-7435.

            McFarland, M.J., and C.M.U. Neale. 1991. Land parameter algorithm validation and
                   calibration. In J.P. Hollinger (ed.), DMSP Special Sensor Microwave/linager
                   Calibration/Validation, Final Report, Volume 11, 9-1 to 9-108. Naval Research
                   Laboratory, Washington, DC.

            Scofield, R.A.    1991. Satellite discussion of the Shadyside, Ohio flash flood event of
                   June 14, 1990. Appendix D of the Natural Disaster Survey Report Shadyside,
                   Ohio, Flash Floods, June 14, 1990. NOAA/NWS Report, U.S. Dept. of Commerce,
                   Silver Spring, MD, D-1 to D-18.

            Scofield, R.A. 1990b. The "water vapor imagery/theta-e connection" with heavy convective
                   rainfall. Proceedings of the EUMETSAT Workshop on NOWCASTING and Very
                   Short Range Forecasting, July 16-20, 1990, Shinfield Park, England, 173-178.

            Scofield, R.A.      1987.    The NESDIS operational convective precipitation estimation
                   technique. Mon. Wea. Rev., 115, 8, 1773-1792.





                                                        C-17









               Scofield, R.A. and V.J. Oliver. 1977. A scheme for estimating convective rainfall from
                      satellite imagery. NOAA Tech. Memo, NESS 86, U.S. Dept. of Commerce,
                      Washington, DC, 47 pp.

               Thiao, Wassila, R.A. Scofield, and J. Robinson. 1993. The relationship between water
                      vapor plumes and extreme rainfall events during the summer season.
                      NOAA/NESDIS Technical Report 67, U.S. Dept. of Commerce, Washington, DC,
                      69 pp.

              Ulaby, F.T., R.K. Moore and A.K. Fung. 1981. In Nficrowave Remote Sensing: Active
                      and Passive, Vol. 1, pp 1-456. Addison-Wesley Pub, Company, Inc.








































                                                       C-18









                                                APPENDEK D


                             LOCATIONS WITH NEW RECORD AND
                                        NEAR-RECORD STAGES




            Locations with new (preliminary) record stages in the upper Mississippi River basin
            (44 locations), the Missouri River basin (49 locations), and the Red River of the North basin
            (2 locations) are given in Tables D-1, D-2, and D-4, respectively. Locations that approach
            the flood of record in the Missouri River basin (24 locations) are given in Table D-3.


































                                                       D-1









               Table D-1. Locations with new (preliminary) record stages in the upper Mississippi
               River besin.




                                                                                         PRELIMMiARY
               LOCATTON                         FLOOD            OLD RECORD              NEW RECORD
                 Index                          STAGE            Stage      Date         Stage      Date
                 Number                            (ft.)           (ft.)                  (ft.)

               Mississip?i R
                   1.  Quad Cities L/D15             15          22.5       650428       22.6       930709
                   2.  Muscatine 1A                  16          24.8       650429       25.6       930709
                   3.  Keithsburg EL                 13          20.4       650427       24.2       930709
                   4.  Burlington IA                 15          21.5       730425       25.1       930710
                   5.  Keokuk L/D19 1A               16          23.4       730424       27.2       930710
                   6.  Gregory Landing MO            15          24.6       730424       26.4       930707
                   7.  Quincy 11L                    17          28.9       730423       32.2       930713
                   8.  Hannibal MO                   16          28.6       730425       31.8       930716
                   9.  Louisiana MO,                 15          27.0       730424       28.4       930728
                 10.   Clarksville MO UD24           25          36.4       730424       37.7       930729
                 11.   Winfield MO L/D25             26          36.8       730427       39.6       930801
                 12.   Grafton IL                    18          33.1       730428       38.2       930801
                 13.   Melvin Price IL               21          36.7       730428       42.7       930801
                 14.   St Louis MO                   30          43.2       730428       49.58      930801
                 15.   Chester IL                    27          43.3       730430       49.7       930807


               Minois R
                 16. Hardin IL                      425         438.2       730429       442.3      930803


               Rock R
                 17. Joslin IL                       12          17.8       790322       18.4       930326


               Spoon R
                 18. Seville IL                      22          31.8       740624       33.1       930726

               Squaw Creek
                 19. Ames IA                         7           16.0       900617       18.5       930709


               South Skunk R
                 20. Oskaloosa IA                    15          23.1       900623       25.2       930715
                 21. Squaw Creek 1A                  9           13.9       440520       14.2       930709




                                                           D-2











                                                                                      PRELIMUNARY
             1A)CATION                       F1,OOD            OID RECORD            NEW RECORD
              Index                          STAGE             Stage     Date           Stage    Date
              Number                            (ft.)          (ft.)                    (ft.)


             Cedar R
               22. Conesville IA                  12           16.9      900618         17.2     930406

             English R
               23. Kalona I.A.                    14           21.5      650921         22.6     930706


             Beaver Creek
               24.   New Hartford IA                8          13.5      470613         13.45    930331


             Iowa R
               25.   Marshalltown IA              13           20.5      900618         20.6     930709
               26.   Marengo IA                   14           19.8      690712         20.3     930719
               27.   Lone Tree IA                 15           20.3      650922         22.9     930707
               28.   Wapello IA                   20           28.9      900619         29.5     930707
                                                                        RECORD FLOW


             E Fork Des Moines
               29. Algona IA                      14           22.0      790823         22.65    930401

             Raccoon R
               30. Van Meter IA                   13           22.7      860701         25.8     930710
               31. Des Moines SW18                12           19.8      470613         26.7     930711


             North Raccoon R
               32. Perry IA                       13           22.7      790320         23.0     930710

             Des Moines R
               33.   Des Moines 2ND AV            23           30.2      540624         31.7     930711
               34.   Des Moines SE 14TH           23           29.8      650411         34.3     930711
               35.   Ottumwa IA                   10           21.0      470607         22.1     930712
               36.   Keosauqua IA                 25           29.4      650411         32.7     930713
               37.   St Francisville MO           18           30.2      790314         32.0     930715


             Baraboo R
               38. Baraboo WI                     16           20.7      920920         22.8     930718


             Black R
               39. Galesville WI                  12           15.5      800923         16.6     930621



                                                         D-3











                                                                                        PRELIMWARY
               LOCATION                         FLOOD           OLD RECORD             NEW RECORD
                 Index                          STAGE           Stage      Date          Stage     Date
                 Numbeir


               Pecatonica R
                 40. Blanchardville WI              19          21.5       480228        22.0      930706


               Little Minnesota R
                 41. Peever SD                      11          13.4       430325        13.6      930727


               Minnesota R
                 42. Mankato MN                     19          29.1       650415        30.1      930621


               Redwood R
                 43. Marshall MN                    14          15.6       690419        17.0      930509


               Meramec R
                 44. Arnold MO                      24          43.9       821206        45.3      930801



































                                                          D-4









             Table D-2. Locations with new (preliminary) record stages in the Missouri basin.



                                                                                        PRELVVMARY
             LOCATION                           FLOOD           OLD RECORD             NEW RECORD
              Index                             STAGE           Stage      Date          Stage      Date
              Number                              (ft.)

             Pipestern Creek
               45. Pipestem Res ND                1496.3      1468.35      790510       1472.0      930804

             James R
               46. Mitchell SD                      14          18.3       690411        19.1       930704


             Weeping Water Creek
               47. Union NE                         25          29.8       580509        31.2       930723


             Wood R
               48. Grand Island NE                    4.8         6.0      670616          6.4      930722


             Salt Creek
               49. Greenwood NE                     20          26.5       840613        26.5       930724
               50. Ashland NE                       16          22.0       940613        23.0       930723


             W Nishnabotna R
               51. Hancock IA                       14          22.1       720913        23.53      930710


             Nishnabotna R
               52. Hamburg IA                       16          28.1       870527        30.52      930725

             Rock R
               53. Rock Rapids IA                     6         10.2       690408        12.5       930509

             Nodaway R
               54. Graham MO                      N/A           20.4       840615        26.1       930723


             102 R
               55. Bedford IA                       21          23.5       860714        23.79      930705
               56. Maryville MO                     14          19.3       731012        20.3       930706

             Platte R
               57. Sharps Station MO                23          34.6       840610        36.4       930726
               58. Agency MO                        20          35.1       650720        36.0       930725


                                                          D-5











                                                                                      PRELIM[INARY
              LOCATION                          FLOOD          OLD RECORD             NEW RECORD
                Index                           STAGE          Stage      Date         Stage      Date
                Number


              South Fork Solomon R
                59. Osborne KS                     14          27.7       510713       28.5       930721
                60. Waconda Res KS               1488.3      1471.3       870427     1487.0       930728


              Saline R
                61. Russell KS                     18          19.7       640901       25.4       930721
                62. Wilson Res KS                1554        1528.1       930426     1547.9       930801
                63. Lincoln KS                     30          34.7       580519       37.8       930722
                64. Tescott KS                     25          30.1       510713       30.8       930723


              Big Creek
                65. Munjor KS                      18        N/A                       26.2       930721

              Smoky Hill R
                66. Abilene KS                     27        N/A                       32.1       930722
                67. Enterprise KS                  26          34.0       510713       34.2       930723
                68. Junction City KS               22        N/A                       29.6       930722

              Delaware R
                69. Perry Res KS                  920.6       917.07      731019       920.9      930725

              Big Blue R
                70. Blue Rapids KS                 26          53.1       731018       63.3       930723
                71. Tuttle Creek Res KS          1136        1127.9       731018     1137.76      930722


              Fancy Creek
                72. Randolph KS                    11          26.5       731018       36.3       930722

              Black Vermillion
                73. Frankfort KS                   19          30.1       731011       32.2       930722


              Republican R
                74. Milford KS                   1176.2      1170.03      731017     1181.85      930725










                                                          D-6











                                                                                    PREL51INARY
            LOCATION                        FLOOD            OLD RECORD            NEW RECORD
             Index                          STAGE            Stage      Date         Stage     Date
             Number                                            (ft.)



            Grand R
              75. Pattonsburg MO                 25          34.3       470600       37.6      930724
              76. Chillicothe MO                 24          34.7       910500       38.5      930709
              77. Sumner MO                      26          39.5       470607       42.6      930710
              78. Brunswick MO                   16          26.1       510717       31.7      930713
                                             HWY 24 OBS Downtown Gage                37.7

            Chariton R
              79. Rathbun Res 1A                 926        924.46      820722      927.2      930728


            Missouri R
              80.   Plattsmouth NE               26          34.66      840614       35.7      930725
              81.   Brownville NE                32          41.2       840615       44.3      930724
              82.   St. Joseph MO                17          26.8       520422       32.69     930726
              83.   Kansas City MO               32          46.2       510714       48.9      930728
              84.   Napoleon MO                  17          26.8       510715       27.76     930727
              85.   Lexington MO                 22          33.3       510715       33.4      930708
              86.   Waverly MO                   20          29.2       840623       31.2      930728
              87.   Miami MO                     18          29.0       510716       32.4      930729
              88.   Glasgow MO                   25          36.7       510718       39.6      930729
              89.   Boonville MO                 21          32.8       510717       37.1      930729
              90.   Jefferson City MO            23          34.2       510718       38.6      930730
              91.   Gasconade MO                 22          38.7       861005       39.6      930731
              92.   Hermann MO                   21          35.8       561005       36.3      930731
              93.   St. Charles MO               25          37.5       861007       39.5      930801
















                                                        D-7









               Table D-3. Locations with near-record stages in the Missouri basin.



                                                                                          PRELINMARY
               LOCATION                         F1,001)          OLD RECORD               1"3 STAGE
                 Index                          STAGE            Stage      Date          Stage     Date
                 Number


               James R
                 94. Jamestown Res ND              1454         1444.1      690427      1440.0      930804


               Vermillion R
                 95. Davis SD                        11          15.8       690405        15.6      930705


               Ponca Creek
                 96. Verdel NE                       12          15.6       600327        14.0      930714


               Big Sioux R
                 97. Hawarden 1A                     15          24.6       690409        24.3      930712
                 98. Akron IA                        16          23.0       690409        22.6      930713


               Soldier R
                 99. Pisgah 1A                       28          28.2       500612        27.58     930710
                                                                          RECORD FLOW
               Wood R
                 100. Alda NE                        10          12.2       670616        11.2      930727


               Shell Creek
                 101. Columbus NE                    20          22.8       900617        21.5      930710


               Platte R
                 102. Louisville NE                   9          12.5       930330        12.0      930724


               Tarldo R
                 103. Fairfax MO                     17          25.9       820800        25.7      930723


               Platte R
                 104. Platte City MO                 18          37.8       650720        32.0      930726

               Solomon R
                 105. Minneapolis KS                 26          34.1       5'10713       32.4      930721
                 106. Niles KS                       24          31.8       510714        30.2      930722




                                                           D-8











                                                                                 PRELIMUNARY
           LOCATION                       FLOOD            OLD RECORD              1993 STAGE
             Index                         STAGE           Stage     Date          Stage     Date
             Number


           Salt Creek
             107. Ada KS                       18          23.3      610523        22.3      930719

           Smoky Hill R
             108. Ellsworth KS                 20          27.2      380601        26.1      930723
             109. Kanopolis Res KS            1508       1506.98     510714      1505.7      930726
             110. New Cambria KS               27          32.4      731012        31.6      930722

           Republican R
             111. Clay Center KS               15          25.7      350603        23.4      930724

           Mulberry Creek
             112. Salina KS                    24          27.4      730926        26.4      930722


           South Grand R
             113. Urich MO                     22          27.9      850223        27.1      930707


           Nfissouri R
             114. Nebraska City NE             18          27.7      520418        27.16     930723
             115. Rulo, NE                     17          25.6      520422        25.24     930724
             116. Sibley MO                    22          35.6      510715        34.6      930729

                                                                  M
























                                                      D-9









                Table DA. Locations %ith new (preliminary) record stages in the Red River of the North
                basin.




                                                                                       PRELEMINARY
                LOCA17ON                        FLOOD           OLD RECORD             NEW RECORD
                 Index                          STAGE           Stage      Date         Stage      Date
                 Number


                Buffalo R
                 117. Hawley MN                      7           9.8       750701       10.9       930718

                Two Rivers
                 118. Hallock MN                   802         807.5       850627      808.1       930815
                                                               810.2       660406 HIGH WATER MARK
                                                                     PRIOR TO GAGE INSTALLATION








































                                                          D-10









                                                  APPENDEK E


                    WEATHER SERVICE FORECAST OFFICE PRODUCT
                                           ISSUANCE SUAINIARY



            The Great Flood of 1993 began in the early spring and continued into the fall of 1993 across the
            Upper Midwest. Record flooding occurred at several forecast points in April and May.
            Nonetheless, the vast majority of the devastating flooding occurred during June, July, and early
            August. A primary goal of this disaster survey report is to assess the quality of services
            provided by the National Weather Service during the peak flooding period. Consequently, a
            summary of the Weather Service Forecast Office products, by week, from June through mid-
            August is given in this appendix. The intent is to convey the order of magnitude of the various
            weather and flood forecast products issued by the NWS field offices during the period of the
            most disastrous and intense flooding.































                                                          E-R










                                                PRODUCT ISSUANCE SUMMARY


                                                        WSFO BISMARCK

                      WEIEK        FLW FLS        RVA RVS FFA              FFW FFS      SVR TOR SVS SPS

                  06/01-06/05        0        2    0      0        0       0       0    0        0     0       1

                  06/06-06/12        0        0    0      0        0       0       0    9        0     14     24

                  06/13-06/19        0        2    0      0        0       0       0    0        0     0       9

                  06/20-06/26        0        1    0      0        0       0       1    13       3     19     23

                  06/27-07/03        0        1    0      0        0       0       1    9        5     14     39

                  07/04-07/10        0        0    0      0        0       0       0    2        0     4      27

                  07/11-07/17        2        5    0      0        5       6       27   11       0     1      27

                  07/18-07/24        1        14   0      0        8       5       23   9        3     15     39

                  07/25-07/31        1        12   0      0        5       0       13   0        1     2       7

                  08/01-W/07         0        13   0      0        0       0       0    0        0     0       2

                  08/08-08/14        0        5    0      0        1       0       1    8        0     5      28

                ITOTALS              4        55   0      0        19      11      66   61       12    74     22


                                                        WSFO CHICAGO

                      WEEK        FLW         FLS  RVA   RVS FFA           FFW     FFS  SVR   TOR     SVS     SPS

                  06/01-W/05         0        0    15     0        0       0       0    0        0

                  06/06-06/12        1        38   21     0        5       1       4    21       3

                  06/13-06/19        0        30   21     0        4       0       3    8        0

                  06/20-06/26        3        35   21     0        1       0       2    3        1

                  06/27-07/03        3        39   21     0        2       2       9    23       0

                  07/04-07/10        1        39   21     0        2       3       7    2        0

                  07/11-07/17        1        34   21     0        6       2       5    0        0

                  07/18-07/24        1        45   21     0        0       5       6    2        0

                  07/25-07/31        0        43   21     0        0       0       1    0        0

                  08/01-08/07        0        23   21     0        0       0       0    3        0

                  08/08-08/14        0        24   21     0        0       2       4    0        0


                  TOTALS             7        345  225    0        20      15      41   62       4


                       FLW-FLOOD WARNING                                   FFS-FLASH FLOOD STATEMENT
                       FLS-FLOOD STATEMENT                                 SVR-SEVERE THUNDERSTORM WARNING
                       RVA-RIVER SUMMARY                                   TOR-TORNADO WARNING
                       RVS-RIVER STATEMENT                                 SVS-SEVERE WEATHER STATEMENT
                       FFA-FLASH FLOOD WATCH                               SPS-SPECIAL WEATHER STATEMENT
                       FFW-FLASH FLOOD WARNING                             Denotes data unavailable



                                                               E-2










                                           PRODUCT ISSUANCE SUMMARY


                                                 WSFO DES MOINES

                WEEK            FLW      FLS   RVA  RVS    FFA     FFW      FFS   SVR     TOR    SVS    SPS

            06/01-06/05         0        4     1    0      0       0        0     0       0      0      0

            06/06-06/12         0        46    4    0      7       7        23    21      0      26     86

            06/13-06/19         4        42    6    4      3       4        16    19      0      24     72

            06/20-06/26         0        41    8    0      2       6        13    4       0      4      32

            06/27-07/03         1        36    9    3      9       16       33    16      0      18     72

            07/04-07/10         11       88    11   0      4       12       30    16      4      23     78

            07/11-07/17         7        34    2    0      5       14       30    2       0      3      74

            07/18-07/24         0        26    7    0      11      5        19    0       0      0      82

            07125-07/31         0        30    9           0       5        22    20      0      34     45

            08/01-08107         0        31    13   0      0       0        0     0       0      0      4

            08/08-08/14         1        16    7    0      2       3        21    12      0      10     54


            TOTALS              24       394   77   8      43      72       207   110     4      142



                                                 WSFO MINNEAPOLIS

                 WEEK           FLW      FLS   RVA RVS FFA FFW              FFS   SVR     TOR    SVS SPS

            06/01 - 06/05       0        6     5      0       0       0       0      0     0        0        0

            06/06 - 06/12       0        9     7      0       0       0       0      2     5        9        19

            06/13 - 06/19       2        28    8      0       4               4      0     0        0        7

            06/20 - 06/26       6        27    9      0       5       0       7      0     0        0        10

            06/27 - 07/03       2        11    7      0       4       0       4      2     0        7        16

            07/04 - 07/10       0        9     10     0       3       0       3      2     T        3        5

            07/11 - 07/17       0        7     7      0       2       0       2      0     0        0        T

            07/18 - 07/24       0        7     7      0       4       0       2      1     1        2        1

            07/25 - 07/31       0        8     7      0       6       0       5      4     1        9        8

            08/01 - 08/07       0        6     6      0       0       0       0      0     0        0        0

            08/08 - 08/14       0        6     7      0       2       0       0      2     0        2        4
            TOTALS              10       124   80     0      30       1     27       13    8      @3 2=7 1

                  FLW-FLOOD WARNING                                FFS-FLASH FLOOD STATEMENT
                  FLS-FLOOD STATEMENT                              SVR-SEVERE THUNDERSTORM WARNING
                  RVA-RIVER SUMMARY                                TOR-TORNADO WARNING
                  RVS-RIVER STATEMENT                              SVS-SEVERE WEATHER STATEMENT
                  FFA-FLASH FLOOD WATCH                            SPS-SPECIAL WEATHER STATEMENT
                  FFW-FLASH FLOOD WARNING



                                                          E-3











                                                PRODUCT ISSUANCE SUMMARY


                                                       WSFO MILWAUKEE

                      WEEK            FLW FLS RVA RVS FFA FFW                      FFS  SVR TOR SVS            SPS

                  06/01   06/05       0       1    5        1     0        0       0    0         0    0       4

                  06/06   06/12       0       12   7        8     0        0       0    15        8    51      39

                  06/13 - 06/19       3       12   7        10    3        3       9    11        1    30      34

                  06/20 - 06/26       8       35   7        2     1        0       2    4         2    15      20

                  06/27 - 07/03       5       16   7        3     0        0       0    7         1    20      26

                  07/04 - 07/10       8       28   7        5     1        1       1    17        1    45      37

                  07/11 - 07/17       1       35   7        2     2        0       0    0         0    0       5

                  07/18 - 07/24       1       21   7        0     4        0       4    0         0    0       7

                  07/25 - 07/31       1       21   7        3     0        0       0    7         1    21      25

                  08/01 - 08/07       0       12   7        1     0        0       0    0         0    0       6

                  08/08 - 08/14       0       9    7        1     0        0       0    0         0    0       5


                  TOTALS              27      202  75       36    11       4       16   61        14   182     208



                                                        WSFO OMAHA

                     WEEK             FLW     FLS RVA RVS         FFA FFW          FFS  SVR   TOR      SVS     SPS

                  06/01 - 06/05       0       0    0        0     0        0       0    0         0    0       8

                  06/06 - 06/12       0       1    0        0     2        0       5    2         0    2       28

                  06/13 - 06/19       1       1    0        2     2        1       8    4         0    2       15

                  06/20 - 06/26       0       4    0        1     0        0       1    5         1    7       14

                  06/27 - 07/03       5       16   0        0     0        3       10   8         3    8       35

                  07/04 - 07/10       7       27   0        0     6        1       12   4         3    2       28

                  07/11 - 07/17       15      24   0        0     8        4       23   2         0    2       24

                  07/18 - 07/24       19      35   0        0     13       8       28   0         5    5       31

                  07/25 - 07/31       8       61   0        1     2        0       6    3         0    4       15

                  08/01 - 08/07       0       1    0        0     0        0       0    0         0    0       2

                  08/08 - 08/14       0       0    0        0     0        1       2    4         2    6       13


                  TOTALS              55      170  0        4     33       18      95   32        14   38      213


                       FLW-FLOOD WARNING                                FFS-FLASH FLOOD STATEMENT
                       FLS-FLOOD STATEMENT                              SVR-SEVERE THUNDERSTORM WARNING
                       RVA-RIVER SUMMARY                                TOR-TORNADO WARNING
                       RVS-RIVER STATEMENT                              SVS-SEVERE WEATHER STATEMENT
                       FFA-FLASH FLOOD WATCH                            SPS-SPECIAL WEATHER STATEMENT
                       FFW-FLASH FLOOD WARNING


                                                               E-4











                                           PRODUCT ISSUANCE SUMMARY


                                                  WSFO SAINT LOUIS

                 WEEK         FLW      FLS    RVA    RVS    FFA FFW FFS               SVR TOR SVS          SPS

             06/01 - 06/05      3      8      30       5        2     0        2      0       0     0      0
             06/06 - 06/12      9      34     42       12       2     3        18     13      1     13     36
             06/13 - 06/19      9      24     50       10       2     3        3      3       0     5      20

             06/20 - 06/26      6      35     48       8        3     4        14     3       0     2      24

             06/27 - 07/03      16     56     42       19       11    16       24     34      5     56     43

             07/04 - 07/10      13     116    42       29       24    61       116    10      0     10     43

             07/11 - 07/17      7      107    42       21       20    10       66     4       0     7      16

             07/18 - 07/24      13     124    50       11       10    7        28     14      1     25     36

             07/25 - 07/31      2      113    48       5        6     3        15     13      3     12     42

             08/01 - 08/07      0      85     42       0        0     3        8      13      3     12     42

             08/08 - 08/14      8      54     42       7        4     6        22     1       0     2      10


             TOTALS             86     756    478      127      84    116      316    108     13    144    312



                                                  WSFO SIOUX FALLS

                 WEEK         FLW      FLS    RVA RVS FFA FFW                  FFS    SVR TOR       SVS    SPS

             06/01 - 06/05      0      7       0       0        0     0        0      0       0     0      0

             06/06 - 06/12      0      7       0       1        3     0        2      9       5     7      12

             06/13 - 06/19      2      7       0       0        2     3        4      9       0     7      17

             06/20 - 06/26      1      9       0       0        2     0        1      6       0     7      12

             06/27 - 07/03      2      8       0       0        3     11       7      61      5     37     37

             07/04 - 07/10      0      10      0       0        1     3        1      11      2     8      17

             07/11 - 07/17      0      22      0       0        2     0        6      1       0     1      15

             07/18 - 07/24      0      7       0       0        3     0        3      9       2     11     8
             07/25 - 07/31      3      7       0       0        1     1        5      7       0     6      6
             08/01 - 08/07      0      7       0       0        0     0        0      0       0     0
             08/08 - 08/14      0      7       0       0        0     1        1      1       0     2      2
                                                                                                           0




             TOTALS             8      98      0       1        17    19       30     114     14    86     126

                   FLW-FLOOD WARNING                                  FFS-FLASH FLOOD STATEMENT
                   FLS-FLOOD STATEMENT                                SVR-SEVERE THUNDERSTORM WARNING
                   RVA-RIVER SUMMARY                                  TOR-TORNADO WARNING
                   RVS-RIVER STATEMENT                                SVS-SEVERE WEATHER STATEMENT
                   FFA-FLASH FLOOD WATCH                              SPS-SPECIAL WEATHER STATEMENT
                   FFW-FLASH FLOOD WARNING



                                                           E-5











                                                PRODUCT ISSUANCE SUMMARY


                                                         WSFO TOPEKA

                      WEiK         FLW     FLS RVA RVS            FFA FFW        FFS   SVR TOR SVS             SPS

                  06/01 - 06/05       0     2      0       0      0       0      0       0      0       0      29
                  06/06 - 06/12       0     0      0       0      0       0      0       13     0       23     60

                  06/13 - 06/19       0     2      4       7      2       0      4       6      2       12     36

                  06/20 - 06/26       0    23      3       18     2       0      4       0      0       0      53

                  06127 - 07/03       4    18      4       5      5       5      20      14     9       29     69

                  07/04 - 07/10       1    65      4       5      12      10     40      21     5       49     85

                  07/11 - 07/17       4    83      7       6      5       1      7       0      0       0      45

                  07/18 - 07/24       4    141     5       3      11      14     36      9      2       15     55

                  07/25 - 07/31       1    56      7       0      2       4      13      3      0       7      32

                  08/01 - 08/07       0    23      4       2      0       0      0       0      0       0      4

                  08/08 - 08/14       0     5      4       2      0       0      0       1      0       2      29


                  TOTALS              14  418      42      48     39      34     124     67     18      137    497


                       FLW-FLOOD WARNING                                FFS-FLASH FLOOD STATEMENT
                       FLS-FLOOD STATEMENT                              SVR-SEVERE THUNDERSTORM WARNING
                       RVA-RIVER SUMMARY                                TOR-TORNADO WARNING
                       RVS-RIVER STATEMENT                              SVS-SEVERE WEATHER STATEMENT
                       FFA-FLASH FLOOD WATCH                            SPS-SPECIAL WEATHER STATEMENT
                       FFW-FLASH FLOOD WARNING









































                                                               E-6









                                                   APPENDEK F


                    ANALYSIS OF SELECTED HYDROLOGIC FORECASTS




             This appendix is closely linked with Chapter 6, and especially with Sections 6.4 and 6.5,
             which discuss hydrologic services for both the upper Mississippi and the Missouri River
             basins. Both the North Central River Forecast Center (NCRFQ and the Missouri Basin
             River Forecast Center (MBRFQ make routine hydrologic forecasts for numerous points
             along the main stems of the Mississippi and Missouri Rivers, respectively. The NCRFC has
             27 such forecast points, while the MBRFC has 18. At a few forecast points, long-term
             forecasts of river stages are generated that range from 7 to as many as 28 days into the
             future. It is possible to evaluate the skill of these long-range forecasts by comparing the
             forecast river stages with the observed river stages.

             This appendix examines long-range forecasts issued by both the NCRFC and the MBRFC for
             two points along the main stem Mississippi River (St. Louis, Missouri, and Chester, Illinois)
             and for three points along the main stem Missouri River (Sioux City, Iowa; Boonville,
             Missouri; and Hermann, Missouri), respectively.         Both River Forecast Centers (RFC)
             provided the disaster survey team with forecast and observed data for each forecast point for
             the period June-August 1993. A series of hydrographs (some of which appear in Chapter 6,
             Figures 6-6 and 6-7) were then generated for each of these five forecast points for lead-times
             out to 28 days for all forecast points except Sioux City, Iowa, which has a lead-time only out
             to 7 days. These hydrographs appear in Figures F-1 through F-13 following this discussion.

             For example, the top panel (a) in Figure F-1 shows the observed stages (solid line) and 1-day
             forecast stages (x symbol) for each day during June-August 1993 at the St. Louis, Missouri,
             forecast point along the Mississippi River.       The forecast stages plotted were actually
             generated 1 day earlier than the date which is shown, i.e., the forecast stage plotted for
             June 2 was generated and released by the NCRFC I day earlier, on June 1. Similarly, the
             middle panel (b) in Figure F-1 shows the observed stages again (solid line; note that this line
             is the same on each graph, as it represents observed river stages) and the 3-day forecast
             stages. On this graph, the forecast stages plotted were actually generated 3 days earlier than
             the date indicated, i.e., the forecast stage plotted for June 4 was generated and released by
             the NCRFC 3 days earlier, on June 1. All other graphs in this appendix are plotted in the
             same manner. Note that at longer forecast ranges, i.e., beyond 7-day forecasts, the forecasts
             are not generated by the RFC on a daily basis (see Figure F-2, top panel (a)). Also, plotted
             on each graph are the flood stage and the previous record flood stage.






                                                           F-1










               A degradation in skill is expected as forecast lead-times extend into the future. In other
               words, fozecasts are typically better at shorter time ranges than at longer time ranges. A
               principal reason for the decreased sldll with increasing lead-time is associated with the fact
               that precipitation that falls after the long-term forecast has been generated is never accounted
               for. Consequently, hydrologic forecasts tend to "underforecast," especially if significant
               precipitation falls in the drainage area of the forecast point after the forecast has been made.
               A systematic underestimate (or overestimate) is referred to as bias. The longer-duration
               forecasts clearly show a systematic underestimate, or bias. Generally, the bias increases with
               increasing forecast lead-times.





































                                                             F-2


















                              so-
                              46-     Previous Record

                              40-




                              30-
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                              28-


                              20-





                               Jun I           Jun 21          Jul 11          Jul 91         Aug 20


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                              Go-
                                      Previous Record

                              40-



                                        x
                              30 -
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                              20-


                              Is-



                               Jun I           Jun 21          Jul 11          Jul 31          Aug 20






                              so-
                              46-     Previous Record



                              36-
                              40-




                              30-


                              26-


                              20-





                               Jun I           Jun 21           Jul 11          Jul 31          Aug 20

                                                                                                             F-C]


               Figure F-1. Forecast (x) and observed (solid lines) river stages along the Mississippi River
               at St. Louis, Missouri: (a) I -day forecasts, (b) 3-day forecasts, and (c) 5-day forecasts.

                                                                  F-3










                                                                                             V-d

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                                so-
                                46-     Previous Record

                                40-                                                                  x
                                                                                         x

                                as-
                                                                             x     x
                                go---
                                sm                                 x         Flood Stage
                                                    : X
                                20-             X            x


                                Is-

                                10,
                                   Jun           Jun 2*1           Jul              Jul all         Aug 20






                                so-

                                40-      Previous Record

                                40-


                                                                                                x     X
                                                                             Flood Stage

                                                                                          x
                                                                        X       x   x

                                                             x
                                                      x
                                                                   X

                                10                                      ........ ......... .......
                                   Jun'l          Jun 21            Jul Ila          Jul 31          Aug 20






                                40 -     Previous Reoord

                                40-


                        IL
                                30-                                          Flood Stage


                                20-                                                              x
                                                                                           X
                                                             x     x            x
                                                                                     x
                                                                        x
                                -10            .......
                                   Jun I          Jun 21            Jul 11           Jul 31           Aug 20


                                                                                                                    FC-1
                                                                             X     @x


                                                                           @@Il '@Stag@e@@ @'








               Fligure F-3. Forecast (x) and observed (solid lines) river stages along the Mississippi River
               at St. Louis, Missouri: (a) 14-dayforecasts, (b) 21-day forecasts, and (c) 28-day forecasts.

                                                                      F-5

















                                    so-
                                    46-    Previous Record





                                    25 -                                                Flood Stage
                                    20-


                                    Ils-


                                    10-
                                    Jun I           Jun 21           Jul 11          Jul 31          AAjg 20


                                                                                                                     F-a]

                                    60-
                                    46-    Previous Record

                                    40-




                                    go-
                                    sm -                                                Flood Stag

                                    20-


                                    Is-


                                    10-

                                    Jun I           Jun 21           Jul 11          Jul 31           Aug 20






                                    so-
                                    46-   Previous Record

                                    4


                                    35-
                                    0-




                                    so-


                                    26 -


                                    20-




                                    10    ....... .......         ...... ..............          .......... ......

                                    Jun            Jun 211           Jul 11           Jul 31          Aug 20

                                                                                                                    FC-1
                                                                                               x
                                             x
                                                                              rROM Stan






                 Figure F4. Forecast (x) and observed (solid lines) river stages along the Mississippi River
                 at Chester, Illinois: (a) I-dayforecasts, (b) 3-dayforecasts, and (c) 5-dayforecasts.

                                                                       F-6

















                                Go-
                                46-      Previous Record

                                40-                                   :X

                                W-
                                                                  x

                                so-


                                Sm        x

                                20-


                                Is-


                                     ............                                                          ......
                                 Jun I            Jun 21           Jul 11           Jul 81           Aug 20


                                                                                                                     F-al

                                so-
                                46-      Previous Record                                    x

                                40-


                                                                    x
                                so-
                                                  x     x     x                       F
                                                                                       I-K= blage
                                            X

                                20-




                                                            ............ ....

                                                                     u
                                 Jun I            Jun 21            JU 110           Jul 31               20






                                so-
                                45-      Previous Record                                        x

                                40-




                                30-

                                2A -                       x

                                20-





                                  Jun I           Jun 21            Jul I -I          Jul 31           Aug 20


                                                                                                                     FC]
                                                                  X













                                                                                      Xj
                                                          x @-


                                                                             X












               FIgure F-5. Forecast (x) and observed (solid lines) river stages along the Mississippi River
               at Chester, Illinois: (a) 7-day forecasts, (b) 9-dayforecasts, and (c) 12-day forecasts.

                                                                      F-7

















                                        go-

                                        46-       Previous Record
                                                                                                               x
                                                                                                        X

                                                                                           x     x
                                                                                     X
                                        SM   ---N-o'             x            x      Flood Stag!]:
                                                           X            x


                                        1411-



                                           Jun'l           Jun 21              Jul 11            Jul 31             Aug 20


                                                                                                                                     Fa-]

                                        so-

                                                  Previous Record

                                        40-


                                                                                                               x
                                        30-                                          Flood Stage

                                                                                     X     x     X
                                        20-
                                                                 X      x
                                                                              X


                                        10
                                           Jun I           Jun 21              Jul 11            Jul 31             Aug 20



                                                                                                                                     Fb1

                                        so-

                                        46-       Previous Record

                                        40-

                                        30-                                      f Flood Stage      I                X      x

                                                                                                              x
                                        20-                                                             X
                                                                        x                 x
                                                                              x                  x
                                                                                     x



                                           Jun I           Jun 21              Jul 11            Jul 31             Aug 20



                                                                                                                                     A
                    L
                                                                                                        X
                                                                                          @xx

                                                                                  @Fl @@Stage@

                                                                                @FFI- WW @@Sta g @e



                    IFTgure F-6. Forecast (x) and observed (solid lines) river stages along the Mississippi River
                    at Chester, Illinois: (a) 14-day forecasts, (b) 21-day forecasts, and (c) 28-day forecasts.

                                                                                  F-8


















                                              ao -


                                              46-


                                              dGO -
                                              36-                                                                               [Flood Stage
                                              30-
                                              26-                                      X X
                                                        X                                        X
                                              24D -


                                              16-

                                              10-    ...........                     .....       ...I
                                               Jun I                  Jun 21                     Jul 11              Jul 31                Aug 20
                                                                                                                                                                        F-al



                                              40-
                                                                                                                              j Flood Stage@_
                                                                                                 X
                                              26-                                         X @)z
                                                                                         @@Ir i     .
                                                                                                         X
                                              20                                            X

                                                           X


                                                                                 ...........                    .........  ...            .......  .......
                                                Jun I                  Jun 21                    Jul 11               Jul 31                 Aug 20


                                                                                                                                                                           V





                                              45 -


                                              40-


                                                                                                                                   Flood Stage
                                              30-
                                              26-                                                X

                                              20-                                                X     X X

                                              1451.-        X


                                              10-    .................                              . ..........

                                                Jun I                  Jun 21                    Jul 11                 Jul 31                 Aug 20
                                                                                                                                                                         Fc-I
                                                                                                 X



















































                                                                                                 X

                                                                                                                  X
                                                                                                           X


                                                            X





                      Figure F-7. Forecast (x) and observed (solid lines) river stages along the Missouri River at
                      Sioux City, Iowa: (a) 1-dayforecasts, (b) 2-dayforecasts, and (c) 3-dayforecasts.

                                                                                                      P-9


















                                         so.




                                         40-


                                         so-
                                         30                                                            Flood Stage

                                         26-


                                         20-
                                                X
                                         Is-                X:

                                         10-
                                                                               ............
                                         Jun I           Jun 21            Jul 11            Jul 31           ^JUG 20


                                                                                                                                   Fa-I
                                         so-


                                         46-


                                         40-


                                         30-


                                         so-
                                                                                                      FIood   &98

                                         20-                                  :X     X      X
                                                                   X
                                                 X



                                              ...........
                                         Jun I           Jun 21            Jul 11            Jul 31          Aug 20







                                         so-


                                         46-


                                         40-


                                         w
                                         so                                                           FIood Stage


                                         20-                                           X     X
                                         16-     X            X     X      X    X
                                                                                                                X
                                                                                                         X
                                         10
                                         Jun I           Jun 21            Jul 11            Jul 31           Au@ 20



                    L
                                                                                          X
                                                                              X


                                                            X.-
























                                                                                     X      X
                                                                              -X
                                                                   X
                                                 X           X




                                           vl@                             X    X@x
                                                                    X
                                                 X            X






                    Figure F-8. Forecast (x) and observed (solid lines) river stages along the Missouri River at
                    Sioux City, Iowa: (a) 4-day forecasts, (b) 5-day forecasts, and (c) 7-day forecasts.

                                                                               F-10

















                              40-
                              W-       Previous Record          x

                              So-


                              20-                                                  Stage
                                                                           Flood Stage

                              10-




                               01
                                                          ..........  ............
                               Jun 1           jul@ 21         Jul 11          Jul 31          Aug 20


                                                                                                                F-al

                              40-
                              36-      Previous Record

                              30-                               x
                                                               x           x
                              25-                             x                                  x
                                                               x
                              20-                                       @IoodStage


                               01                                                             .......
                               Jun I           Jun 21           Jul 1 *8        Jul 31         Aug 20







                              40-

                              SO -     Previous Record

                                                                           x         X
                              26-                                              x

                              20-
                                    j                                      Flood Sta
                              16-       x                                             981
                                              x               x







                               Jun I           Jun 21          Jul 11          Jul 31          Aug 20


                                                                                                                FC-1

                       ----------
                                                                x











                                                                                                 xx@,x












                                                                  j x      Flood Stage









             Figure F-9. Forecast (x) and observed (solid lines) river stages along the Missouri River at
             Boonville, Missouri: (a) I-dayforecasts, (b) 3-dayforecasts, and (c) 7-dayforecasts.

                                                                  F-11














                                             Previous Record

                                    00-
                                    20-      ILS                      Flood,'S@t@@age
                                        I-J                                                X
                                                                                     x
                                                    x
                                                         x     x               x
                                                                          x



                                     0                         ..........                                 .........
                                     Jun I           Jun 21           Jul 11         Jul 31          Aug 20


                                                                                                                      Fa-I

                                    40-

                                    W-       Previous Record

                                    30-




                                    20-
                                                                                                       x
                                                                      Flood Stage
                                                                                           x     x
                                                         x
                                                                x
                                                                      x              x
                                                                                x




                                     Jun I           Jun 21           Jul 11          Jul 31         Aug 20



                                                                                                                      Fbj

                                    40-

                                    35-      Previous Record

                                    30-


                                                                      Flood Stag                            X--N
                                                                                                       x
                           OD                                   x                                x
                                    10-                               x
                                                                          x
                                                                                     x     x


                                                       I.                               T.                    ......
                                     Jun I           Jun 21           Jul 11         Jul SI          Aug 20


                                                                                                                      F-C]


                   Figure F-10. Forecast (x) and observed (solid lines) river stages along the Missouri River at
                   Boonville, Missouri: (a) 14-day forecasts, (b) 21-day forecasts, and (c) 28-day forecasts.

                                                                        F-12


















                                 40-
                                           Previous Record

                                                                                                     >ï¿½<

                                           x


                                 20-






                                  45-

                                  0  1-  .............                       .......
                                  Jun I             Jun 21           JUIVU              Jul 31          AAJg 20


                                                                                                                            F-al

                                 40-
                                           Previous Record

                                                                                                           x

                                                                     xx
                                 20-       6S@                                                    age
                                     -40K                                               Rood St
                                 145-


                                 ,go-
                                  01
                                                                              ...........
                                  Jun I             Jun 21            JU1,010           Jul 31           Aug 20







                                 40-
                                           Previous Record              x
                                 36-                                           x                            x
                                 30-




                                 20
                                                                                        Rood S       a
                                                           W





                                  0-1                                             ..........
                                  JunE              Jun 21            Jul V9            Jul 31           Aug 20


                                                                                                                            F-C]
                                                                        x
                                     =
                                           X



                                                          x



















                                                                                                           X


























                                                                                                            X
                                     =w









               Figure F-11. Forecast (x) and observed (solid lines) river stages along the Missouri River at
               Hennann, Missouri: (a) 1-dayforecasts, (b) 2-dayforecasts, and (c) 3-dayforecasts.

                                                                         F-13



















                                              40-
                                                    Previous Record
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                                                                                           x
                                              so-
                                                                                  X.
                                              26-

                                              20--

                                                                                                                                  x




                                                                                                                        .F-
                                              Jun I          Jun 21             Jul 11             Jul 31           ^ug 20


                                                                                                                                         F-al

                                              40-
                                                   Previous Record
                                              36

                                                                                     x
                                              30-                                       X

                                                                                         x
                                              Sm -                            x x

                                              20-








                                              0
                                                                      ..........
                                              Jun I          Jun 2'l            Jul 'I I           Jul 31            Aug 20






                                              40-
                                                   Previous Record
                                              36-


                                              30-


                                              26-

                                              20-                                         Fk)od
                                                                                                               x
                                                                                                                      x

                                              10-
                                                                                     X                   X
                                                                                                   X
                                              All-                                          x

                                              0                                                                  ........ ..........
                                              Jun I         Jun 21              Jul 11             Jul S1           ^ug 20



                                                                                                                                        FC
                                                                                  x     X,-X>7@-              )N@
                                                                  @.@x X,


                                                                                          Fk)od Stag@e.@
                                                                        x









                      Figure F-12. Forecast (x) and observed (solid lines) river stages along the Missouri River at
                      Hennann, Missouri: (a) 4-dayforecasts, (b) 5-dayforecasts, and (c) 7-dayforecasts.

                                                                                   F-14


















                                 40-
                                          Previous Record


                                 30-


                                 26-
                                                                      Flood Stage

                                                                                 x
                                                        X
                                                                x
                                                                      x    x


                                   Jun'l            Jun 21            Jul 11            Jul *I            L@ 21


                                                                                                                            Fa-]

                                 40-
                                 36-       Previous Record

                                 30-


                                 go-


                                 acu -
                                                                      Flood Stage             x
                                 1145-                  x                                           x
                                 10-                            x
                                                                      x                 X





                                   Jun              Jun 21            Jul ,I            Jul 31           Aug 20







                                 40-
                                 36-       Previous Record


                                 26-


                                 20-
                                                                      Flood Stage
                                                                x                                   x
                                                                                                          x
                                 Io-                                  X
                                                                           X                  X



                                                                                                              ..........
                                   Jun              Jun 21            Jul 11            Jul 31           Aug 20


                                                                                                                            FC-1
                                                                      @FlStage


                                                                      r










               Figure F-13. Forecast (x) and observed (solid lines) river stages along the Missouri River at
               Hermann, Missouri: (a) 14-day forecasts, (b) 21-day forecasts, and (c) 28-day forecasts.

                                                                         F-15
































                   Owl









                                              February 1994