[From the U.S. Government Printing Office, www.gpo.gov]

                                                                            Task 19       FINAL PRODUCT VMRC
                                                                            FY 1993     Cam. Impacts Carrying Capacity Creeks A
                                                                                                      Inlets




                            Mode g Cumulative Impacts
                                                      and the
                                          Carrying Capactiy
                                                             of
                             Small Tidal Creeks and Inlets






                                                       Bruce J. Neilson
                                                        Carl Hershner
                                                        Megan Greiner








                                                 Virginia Institute of Marine Science
                                                     School of Marine Science
                                                    College of William and Mary
                                                  Gloucester Point, Virginia 23062







                                This report was funded, in part by the Department of Environmental
                                 Quality's Coastal Resources Management Program through Grant
                            #NA47OZO287-01 of the National Oceanic and Atmospheric Administration,
                                                                     (9W-)










                            0
                             ,ffice of Ocean and Coastal Resource Management, under the Coastal Zone
                                              Management Act of 1972, as amended.








             Modeling Cumulative Impacts and the Carrying Capacity of

                                      Small Tidal Creeks and Inlets








             INTRODUCTION



                    Estimation of water quality impacts associated with use changes on land or water is
             primarily dependent on knowledge of what will be added to the water as a consequence of the
             change in use. Understanding of the mixing and transport of substances added to water bodies is
             reasonably advanced, with numerous mathematical models available to generate assessments of
             dilution and dispersion. The accuracy of model output is constrained, however, by the accuracy of
             the estimates of what is being added to the water (loadings). Frequently, loading of pollutants is
             unknown and extremely difficult to measure.


                    When pollutant loading occurs as a result of point source discharge, measurement of

             amounts added can be determined if concentrations and flow rates are known. While not a trivial

             problem, it is usually possible to mount an outfall sampling program sufficient to generate the
             required estimate. The problem is much more intractable when dealing with nonpoint source
             pollution. Addition of nutrients, sediments, biological and chemical oxygen demand, fecal
             coliforms and other substances to water bodies from surrounding lands is generally variable in
             both time and space. Estimating a time and space averaged loading is a difficult undertaking
             requiring extensive long term sampling of all the various delivery pathways. Few studies have
             undertaken the comprehensive sampling necessary to generate such numbers.


                     Even when estimates of pollutant loadings are developed, application of the estimates to


                                                             1









              areas outside of the original sampling site entails an enormous number of assumptions about
              modes and rates of delivery, assumptions which are rarely documented or tested. As a
              consequence, prediction of water quality impacts, and particularly cumulative impacts, remains a
              speculative undertaking. Model output can be no better than the quality of the data used as input.


                     'Me purpose of this project was to identify pollutant loading values which might be used
              as input for a series of water quality models applied to small tidal creeks and inlets in Virginia's
              coastal plain. The intent was to identify values from literature sources which might be used in
              application of the models, absent better or more site specific information. Estimates of biological
              oxygen demand, chemical oxygen demand and fecal coliform loadings were of specific interest.




              FINDINGS



                     Numerous studies have sought to determine pollutant loads associated with different land
              uses through intensive field work and long term sampling ( eg. Clesceri et al., 1986; Beulac et al.
              1982; Sonzogni, 1980). The majority of these works measure pollutant input through surface
              runoff following rainfall events. Runoff export coefficients are calculated as average annual
              pollutant loads per unit area. There are several limitations to braod application of these values.
              While studies have suggested that land use is the most important factor controlling pollutant loads
              in runoff waters (eg. Rast et al. 1983, Whipple et al. 1978), the net input of pollutants is
              understood to be a result of rainfall intensity and frequency, soil type, watershed slopes, and small
              scale patterns of land cover/use. Transport through groundwater pathways is also understood to
              be locally important and highly variable. Incorporation of all of these considerations in water
              quality models, while an objective of ongoing work, is not yet practical. Current models, and
              particularly those developed in the related work for this project, rely primarily on measures of
              land use and a generalized runoff coefficient.


                     Uttormark et al. (1974) concluded from a survey of literature that there is little


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              justification for the delineation of land useage beyond categories of urban, agriculture, forest and
              pasture. Thus, most studies report values for these classes of land uses. A survey of the
              literature indicates loading values can vary widely, generally over one to two order of magnitude
              for any single pollutant and land use type.


                     This report provides a summary of values for both runoff coefficients (TABLE 1) and
              storm water runoff load estimates (TABLE 2) for total suspended solids, biological oxygen
              demand, coliform levels, chemical oxygen demand, total nitrogen and total phosphorus.




              SPECIAL NOTE FOR FECAL COLIFORMS



              Estimation of fecal coliform loadings is particularly important in efforts to evaluate projects
              proposing marina construction. At the present time, the number of boat slips available in a marina
              is used as a predictor of probable pathogen concentrations in surrounding waters. The purpose of
              this determination is to set shellfish harvest controls, hopefully preventing the harvest and/or
              marketing of shellfish which might contain unacceptably high concentrations of pathogens. The
              assumption that slip number is an adequate predictor of pathogen concentrations is generally
              viewed as grossly oversimplified, but it has served as a practical solution absent more
              sophisticated methods of prediction.


                      One of the goals of this project was generation of mathernatic models which might
              enhance the ability of managers to assess probable pathogen loading around marinas. The models
              basically estimate dispersion of fecal coliforms (used as an indicator of pathogen levels) based on
              circulation patterns. Model output is clearly dependent on the initial loading assumption. This
              number is extremely difficult to estimate with any accuracy.


                     In 1985, the United States Environmental Protection Agency developed a Coastal Marinas
              Assessment Handbook. The purpose of the handbook was to provide guidance in the design and


                                                               3









              evaluation of marina projects. As part of that undertaking, the EPA contractor conducted an
              extensive review of available information in an effort to determine the fecal coliform loading
              attributable to each boat in a marina. The handbook referenced work done by Carstea et al.
              1975 in identifying the assumptions necessary to develop an estimate. These assumptions include:
                     - average persons per boat is three;
                     - average per capita discharges of coliform bacteria and BOD are 2 billion and 75.6 g
                     respectively;
                     - half of the people on board contribute fecal material in 24 hours;
                     - coliform bacteria populations do not increase;
                     - a boat in use spends one hour in the marina;
                     - 25 to 40 percent of boats present are in use and evenly distributed.


              The difficulties associated with use of a number based on all these assumptions is self-evident.


                     The estimation of fecal coliform loading per boat in a marina is further complicated by the
              increased use of on-board marine sanitation devices. An even greater uncertainty derives from the
              potential influx of fecal coliforms from non-point sources. Schima et al. 1994 investigated the
              relationships between fecal coliform levels at 2,614 sampling stations and their landscape
              positions. They found a basic pattern of increasing fecal coliform bacteria densities with distance
              upstream in tidal creeks and inlets. They refered to this as a "land mass" effect, or simply the
              amount of land within a fixed radius of sample locations. Regression analysis of the MPN
              concentrations at sampling points along the Eastern Shore of Virginia indicated the following
              variables (in order of decreasing importance) were significant in explaining changes in the sampled

              MPN values:

                     - surface area of water in a 400 rn raduius around the sampling point

                     - season

                     - tide stage during sampling
                     - rainfall amounts in the 2 days prior to sampling
                     - surface area of urban land in a 400 m radius around the sampling point


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                      - near shore groundwater hydraulic gradient
                      - slinity
                      - proximity to nearest shoreline
                      - near shore soil permeability

                      - near shore runoff events

                      - surface area of agricultural land in a 400 m radius around the sampling point
                      - near shore Darcy velocity

                      - water temperature
              One conclusion to be drawn from all of this is that while fecal coliform inputs from nonpoint
              sources on land may be very important, they are also very variable and difficult to predict, even on

              the basis of land use.









































                                                               5








                                                           TABLE 1



                                        LOADING RATES BY LAND USE (kg/ha/yr)



              LANDUSE                  TSS             BOD               COLIFORM               SOURCE

              residential              420             35                -                      Wanielista, 1978

                                       11-487              -             -                      Bannerman et al., 1984

                                       360-390                           -                      Marsalek, 1978

                                       620-2,300           -             -                      Sonzogni, 1980
                                           -           30-50             -                      Loehr, 1974

                                                           -             25,621-                Ellis, 1986
                                           -               -             82,500(mpn/g)



              commercial               840             87                                       Wanielista, 1978

                                       957                 -                                    Bannerman et al., 1984

                                       360                 -                                    Maralek, 1978
                                       50-830              -                                    Sonzogni, 1980
                                           -               -             36,900(mpn/g)          Ellis, 1986


              agriculture      mean    450             18                -                      Wanielista, 1978
                               range   180-4,200       4-31              -



              pasture          mean    343             11.5              -                      Wanielista, 1978
                               range   10-840          6-17              -



              forest           mean    85              5                 -                      Wanielista, 1978
                               range   15-132          2-7               -





                                                                         6







                                                       TABLE I (continued)


                                               LOADING RATES BY LANDUSE (kg/ha/yr)


                       LANDUSE                 TN               TP              SOURCE
                       residential             5.0-7.3                          Sonzogni, 1980
                                               9-11.2           1.6-3.4         Marsalek, 1978

                                               5.4-18.0         1.00-2.47       EPA, 1983

                                               6.6              1.8             Wanielista,1978
                                                  -             1.2-8.0         Whipple et al., 1978


                       commercial              1.9-11             -             Sonzogni, 1980

                                               11.2             3.4             Marsalek, 1978

                                               16.3             2.22            EPA, 1983

                                               14.5             2.7             Wanielista, 1978


                       pasture         mean    6.2              0.5             Wanielista, 1978
                                       range   2.0-12.0         0.1-2.1

                                               4.94             0.74            Beulac & Reckhow, 1982

                                                  -             0.34-0.56       Mackiernan, 1985



                       agriculture             8.89             2.22            Beulac & Reckhow, 1982
                                       mean    26.0             1.05            Wanielista, 1978

                                       range   15.0-37.0        0.18-1.62
                                                                1.68-5.6        Mackiernan, 1985

                                                                0.06-2.9        Loehr,1974







                                                                          7







                                                     TABLE 1 (continued)


                                              LOADING RATES BY LANDUSE (kg/ha/yr)


                      LANDUSE                 TN             TP              SOURCE

                      forest          mean    3.0            0.10            Wanielista, 1978

                                     range    2.0-5.1        0.01-0.86
                                              2.47           0.25            Beulac & Reckhow, 1982

                                                -            0.06-0.11       Mackiernan, 1985

                                                             0.03-0.9        Loehr, 1974


































                                                                      8









                                                                   TABLE2



                                              STORM WATER RUNOFF ESTIMATES (mg/1)



               POLLUTANT                                                                          SOURCE

               TSS                                               141-224                          EPA, 1983

                                                                 1,401-2,909                      Wanielista, 1978

                                urban                            227                              Carstea et al., 1975

                                Durham, NC mean                  1,440                            Colston, 1974

                                                  range          194-8,620
                                agricultural                     90-5,000                         Dombush et al., 1974

                                watershed                        180-6,000

                                cultivated                       1,021
                                pasture                          38


               BOD              urban area                       12-160                           Loehr,1974

                                                                 17                               Carstea et al., 1975
                                Cincinnati, OH mean              19                               Weibel et al., 1964

                                                  range          2-84
                                agricultural                     7                                Loehr,1974
                                watershed                        5-30                             Dornbush et al., 1974

                                                                 3-15



               COLIFORM                                          1,000-

                                                                   21,000 MPN/100ml               EPA, 1983

                                                                 > 2,000 MPN/100ml                Olivieri et al,. 1977
                                Washington, DC                   76,100                           Wanielista, 1978
                                Durham, NC         mean          23,000                           Colston, 1974
                                                   range         100-200,000

                                                                        9








                                                  TABLE 2 (continued)


                                         STORM WATER RUNOFF ESTIMATES (mg/1)


              POLLUTANT                                                                     SOURCE
              COD             Durham, NC       mean          170                            Colston, 1974
                                                range        20-1042
                              Cincinatti, OH   mean          99                             Weibel et al., 1964
                                               range         20-610
                              agricultural                   50-360                         Dornbush et al., 1974

                              watershed                      70-780

                              pasture                        49


              TN                                             5.6-7.1                        EPA, 1983

                              urban area        mean         3.1                            Weibel et al., 1966

                                                range        0.3-75
                                                             3.1                            Carstea et al., 1975

                              forested                       0.3-1.8                        Loehr, 1974
                              agriculture                    9.0                            Loehr, 1974




              TP                                             0.4-0.5                        EPA, 1983
                              agriculture                    0.04-2.4                       Dornbrush et al., 1974

                              forested                       0.01-0.11                      Loehr, 1974

                              agriculture                    0.02-1.7                       Loehr, 1974
                              urban area                     0.2-1.1                        Loehr, 1974

                                                             1.1                            Carstea et al., 1975



                                                                    10










                                                       REFERENCES



             Bannerman, R., K. Baun, M. bohm. P.E. Hughes and D.A. Graczyk. 1984. Evaluation of
                    Urban Nonpoint Source Pollution Management in Milwaukee County, Wisconsin.
                    Report No. P1384-114164. Chicago, 111. EPA Region V.


             Beulac, M.N. and K.H. Reckhow. 1982. An examination of landuse nutrient export
                    relationships. Water Resources Bulletin. 18:1013-1023.


             Carstea, D., A. Binder, R. Strieter, L. Boberschmidt, L. Thomas and J. Golden. 1975.
                    Guidelines for the environmental impact assessment of small structures and related activities in
                    coastal bodies of water. Prepared by MITRE Corporation for U. S. Army Corps of Engineers,

                    New York District.



             Clesceri, N.L. S.J. Curran, and R.I. Sedlak. 1986. Nutrient Loads to Wisconsin Lakes:

                    Part I: Nitrogen and Phosphorus export coefficients. Water Res. Bull. 22(6):983-1000.



             Colston, N.V. Jr. Characterization and treatment of urban land runoff. Environ. Protection

                    Technol. Series. EPA 670/2-74-096. 1974.



             D'Elia, F. 1987. Nutrient Enrichment of the Chesapeake Bay: Too much of a good thing?

                    Env. 29:6-33.



             Dombush, J.N., J.R. Anderson, L.L. Harms. 1974. Quantification of pollutants in agricultural
                    runoff. EPA-660/2-74-005. US EPA. Washington, D.C.


             Ellis, J.B. 1986. Pollutional aspects of urban runoff. pp. 1-38 in H.C. Torna, J. Marsalek,
                    and M.Desbordes, fd- Urban Runoff Pollution. Springer-Verlag, NY, Inc.




                                                              11








            Loehr, R.C. 1974. Characteristics and comparative magnitude of non-point sources.
                    Journal WPCF 46(8):1849-1872.


            Mackiernan, G.B., D.A. Flemer, Nehlsen, W. V.K. Tippie and R.B. Biggs. 1985. Chesapeake
                    Bay: A profile of environmental change. EPA, Annapolis, MD. Chesapeake Bay Program.


            Marsalek, J. 1978. Pollution Due to Urban Runoff: Unit Loads and Abatement Measures.
                    Windsor, Canada: Pollution by Land Use Activities Reference Group of the

                    International Joint Commission.



            Nagnien, R.E., R.M. Summers and K.G. Sellner. 1992. External Nutrient Sources, Internal
                    Nutrient Pools, and Phytoplankton Production in Chesapeake Bay. Estuaries
                    15(4):497-516.



            Olivieri, V., C. Kruse, K. Kawata, and J. Smith. 1977. Microorganisms in Urban Stormwater.
                    Report No. EPA 600/2-77-087. Cincinnati, OH: EPA Municipal Environmental
                    Research Laboratory.


            Overton, D.E. and M.E. Meadows. 1976. Stormwater Modeling. NY Academic Press.


            Rast, W. and G.F. Lee. 1983. Nutrient Loading Estimates for Lakes. J.Env. Engineering. ASCE
                    109(2):502-517.


            Schima, F.J., W.G. Reay, D.L. Gallagher, G. M. Simmons, Jr., J.L. WaIdon and K.K. Reay.
                    1994. Groundwater transport of fecal coliform bacteria to open coastal waters of Virginia's
                    coastal plain: A GIS approach. Final Report to Virginia's Coastal Resource


            Sonzogni, W.C. 1980. Pollution from land runoff. Environ. Sci. and Tech. 14:148-153.




                                                             12









             United States Environmental Protection Agency. 1985. Coastal Marina Assessment Handbook.
                    USEPA 904/6-85-132. Region 4, Atlanta, Georgia.


             United States Environmental Protection Agency. 1983. Results of the Nationwide Urban
                    Runoff Program: Volume 1. USEPA, Washington, D.C.


             Uttormark, P.D., J.D. Chapin and K.M. Green. 1974. Estimating Nutrient Loading of Lakes
                    from non-point sources. US EPA 600/3-74-020. US EPA. Corvallis, OR.


             Wanielista, M.P. 1978 Stormwater Management: Quantity and Quality. Ann Arbor

                    Science Publishers.



             Weibel, S.R. et al. 1964. Urban land runoff as a factor in stream pollution. J. WPCF.
                    36(7):914-924.


             Weibel, S.R. et al. 1966. Pesticides and Other Contaminants from Raingall and Runoff as

                    Observed in Ohio. Jour. Amer. Water Works Assn. 58:1075-1084.



             Whipple, W. Jr. J.V. Hunter, and S.L. Yu. 1978. Runoff pollution from multiple family housing.

                    Water Res. Bull. 14:288-301.





















                                                              13








                                                 Coastal Screening Model
                                                                   User Manual


                                                                             Version 0.95



                                                                            Developed for:
                                            Virguilia Marine Resource Commission









                                           Virginia Polytechnic Institute and State University
                                        Division of Envirorunental Engineering and Sciences
                                                          Department of Civil Engineering


                                                                       Mary Ann Parcher
                                                                         Research Assistant

                                                                     Dr. Daniel Gallagher
                                                                        Associate Professor



                                                                             June 20, 1995

                                          This brochure was reprinted by the Department of Environmental Quality's Coastal Resource
                                        Management Program through Grant #NA370ZO360-01 of the National Oceanic and Atmospheric
                                          Admini tration, Office of Ocean and Coastal Resource Management, under the Coastal Zone
                                                                    Management Act of 1972, as amended.
                           C I PC FI/         The views expressed herein are those of the authors and do not necessarily reflect the
                                                                   views of NOAA or any of its subagencies.









                                                                                          Table of Contents
                                  1. Introduction             .................................................................................................                  1-1
                                      1. 1 Model Overview              .......................................................................................................   1-1
                                      1.2 Notation Review              .......................................................................................................   1-2
                                      1.3 System Requirements                  ................................................................................................  1-4
                                      1.4 Installation Procedures                ..............................................................................................  1-4
                                      1.5 Getting Started           ..........................................................................................................   1-4
                                 2. Model Selection Advisor                          ............................................................................                2-1
                                      2.1 Model Types               ............................................................................................................. 2-1
                                        2. 1.1 Land Use Models              ........................................................................................................... 2-2
                                        2.1.2 Water Quality Models                 .................................................................................................... 2-2
                                      2.2 Operating the Advisor                 ...............................................................................................  2-2
                                      2.3 Water Quality Parameters                   ..........................................................................................  2-3
                                        2.3.1 Dimensions            .................................................................................................................... 2-4
                                        2.3.2 Time        .............................................................................................................................. 2-4
                                        2.3.3 Loadings              ........................................................................................................................ 2-4
                                        2.3.4 Tidal       .............................................................................................................................. 2-4
                                        2.3.5 Water Quality Parameters                  ............................................................................................... 2-4
                                      2.4 Model Selection              ........................................................................................................  2-5
                                 3. Watershed Model                    .......................................................................................                   3-1
                                      3.1 Modeling Approach                 ....... 7**                           . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3-1
                                        3.1.1 Septic Systems           ............................................................................................................... 3-3
                                      3.2 Model Format              ...........................................................................................................  3-3
                                      3.3 Program Options              ........................................................................................................  3-4
                                        3.3.1 Hydrologic Unit Data               .............................................................................0 ....................... 3-4
                                        3.3.2 Climate Data          .................................................................................................................. 3-5
                                      3.4 Initial Conditions           .......................................................................................................   3-6
                                      3.5 Land Use Information                 ................................................................................................  3-8
                                        3.5.1 Runoff Curve Numbers                   .................................................................................................. 3-9
                                        3.5.2 Universal Soil Loss Equation Factors                      ............................................................................ 3-13
                                      3.6 Nutrient Input            .........................................................................................................    3-20
                                      3.7 Point Sources             ..........................................................................................................   3-21
                                      3.8 Evapotranspiration Conditions                      ................................................................................    3-22
                                      3.9 Septic Systems            ........................................................................................................     3-23
                                      3. 10 Model Results           .......................................................................................................      3-24
                                        3. 10.1 Tabular Output            ...........................................0 .............................................................. 3-24
                                        3.10.2 Graphical Output             ........................................................................................................ 3-25
                                4. Marina Water Quality Model                                ......................................................................              4-1
                                      4.1 Model Format              .................................................................0............................. 0 ........... 4-2
                                      4.2 Parameters          ................................................................................................................   4-3)
                                        4.2.1 Hydraulic Pa6meters                 ..................................................................................................... 4-33
                                        4.2.2 Contaminant Parameters                 ..........0 ....................................................................................... @@3
                                        4.2.3 Region to be Modeled               ................................................................0 .................................... 4-3
                                      4.3 Options      ...............................................  0 ...................................................................... 4-4
                                      4.4 Model Results             ...........................................................................................................  4-4










                                   4.4.1 Tabular Output          ................................................................................................................
                                   4.4.2 Transects         ....................................................................................................................... 44
                             5. Tidal Prism Model                ......................................................................................         5-1
                                5.1 Modeling Approach               .................................................................................................. 5-2
                                5.2 Model Format           ........................................................................................................... 5-3
                                5.3 Parameters        ................................................................................................................ 5-4
                                5.4 Stream Geometry             ...................................................................................................... 5-5
                                5.5 Segmentation           ............................................................................................................ 5-6
                                5.6 Loading Data           ............................................................................................................ 5-6
                                5.7 Table Results          ............................................................................................................ 5-7
                             6. Finite Section Model                 ..................................................................................         6-1
                                6.1 Modeling Approach               ................................................................................................... 6-1
                                6.2 Model Format           ........................................................................................................... 6-2
                                6.3 Options      ...........................................................................................................A ........ 6-3
                                   6.3.1 Water Quality Variables            ................................................................................................. 6-3
                                   6.3.2 Boundary Conditions            ...................................................................................................... 6-4
                                   6.3.3 Differencing Options           ...................................................................................................... 6-4
                                6.4 Input Data        ................................................................................................................. 6-5
                                6.5 Model Results          ........................................................................................................... 6-5
                                   6.5.1 Graph Output        ................................................................................................................. 6-6
                                   6.5.2 Table Output        .................................................................................................................. 6-6
                             7. Spill Model           ............................................................................................       * .... 7-1
                                7.1 Model Format           ........................................................................................................... 7-1
                                7.2 Parameters        ................................................................................................................ 7-2
                                7.3 Model Results          ........................................................................................................... 7-2
                                   7.3.1 Graph Results         ................................................................................................................ 7-3
                                   7.3.2 Table Results       ................................................................................................................. 7-3
                                7.4 Calibration       ................................................................................................................ 7 - ")
                             8. Utility Models             ............................................................................................         8-1
                             9. References            .................................................................................................         9-1









                                                                                      List of Tables

                               Table 3-1.      Weather File Locations and Record Lengths                 .................................................................. 3-6
                               Table 3-2.      Sediment Delivery Ratio Based on Watershed Size                    ........................................................ 3-7
                               Table 3-3.      Runoff Curve Numbers for Cultivated Agricultural Land                      ............................................. 3-10
                               Table 3-4.      Runoff Curve Numbers for Other Rural Land                   .............................................................. 3-11
                               Table 3-5.      Runoff Curve Numbers for Urban Areas                  ...................................................................... 3-12
                               Table 3-6.      Description of Soil Hydrologic Groups              ........................................................................ 3-13
                               Table 3-7.      Values of Soil Erodibility Factor (K) in t1a,           .................................................................. 3-14
                               Table 3-8.      Values for the Topographic Factor (LS)               ...................................................................... 3-16
                               Table 3-9.      Values of C for Cropland, Pasture, and Woodland                   ....................................................... 3-16
                               Table 3-10.      C Factor Values and Slope-Length (LS) Limits for Construction Sites                          ....................... 3-17
                               Table 3-11.      Values of P for Agricultural Lands             ............................................................................ 3-18
                               Table 3-12.      Values of P for Construction Sites            ............................................................................. 3-18
                               Table 3-13.      Estimated Values for Land Uses in the Hydrologic Unit Database                         ............................... 3-19
                               Table 3-14.      Dissolved Nutrients in Agricultural Runoff               ................................................................ 3-21
                               Table 3-15.      Nutrient Accumulation Rates for Northern Virginia Urban Areas                         ............................... 3-21








                                                                               Table of Figures

                             Figure 2- 1. Model selection advisor parameter options                   .................................................................... 2-3
                             Figure 3-1. Conceptual model of a watershed, adapted from Haith et al., 1992                            ................................ 3-1
                             Figure 3-2. Watershed sediment delivery ratio, adapted from Vanon@ 1975                            ..................................... 3-7
                             Figure 5-1. Elevation view of a hypothetical river illustrating the volumes of water exchanges between
                                    adjacent. segments during a complete tidal cycle              . ...................................................................... 5-4
                             Figure 6-1. Finite Section Con                         on  . ................................................................................. 6-1
                             Figure 6-2. Components of mass balance equation, adapted from Thomann and Mueller (1987)                                     . ..... 6-2












































                                                                                                                                                                    iv








                        1. Introduction
                        Significant demand exists for housing and marina development along tidal creeks and inlets around the
                        Chesapeake Bay. These changes in land use have the potential to adversely impact the water quality of
                        Virginia's waterways. Existing water quality models can predict these water quality changes, but
                        existing models require extensive field data, model calibration, and expertise to use. The Virginia
                        Marine Resource Commission (VMRC) issues permits fbr most coastal development and does not have
                        the necessary resources to apply such models on a routine basis. 'Me Coastal Screening (CS) Model
                        was developed to provide the VMRC with a tool for a preliminary evaluation of development
                        applications and to identify those projects with relatively insignificant water quality impacts.

                        As the name implies, the CS Model is a screening-level model. The unavailability of measured field
                        values requires that the model contain, many assumptions to reduce the amount of required input. As
                        model complexity and site-specific information is reduced, the uncertainty of the predicted values
                        increases. Therefore, the goal of the CS Model is not to predict a specific water quality concintration,
                        but only to identify those projects that can be permitted without further in-depth analysis. A proposed
                        project passing the screening model would indicate no major impacts with a fair degree of uncertainty.
                        Projects with greater impacts or with high degrees of uncertainty would require additional analysis and
                        modeling effirt.


                        1.1 Model Overview
                        The Coastal Screem*ng Model is a PC-based computer model that operates in the Windows
                        environment Ile components of the CS Model are several water quality models, a land use model, a
                        few utility codes, and a model selection advisor.

                        The model selection advisor is designed to aid the user in determining which model is most applicable
                        for the current assessment. The advisor contains a checklist of various water quality parameters and
                        model options that the user can select for each modeling effort. Based on the options selected by the
                        user, the advisor determines the appropriate model(s). A description of model characteristics and
                        parameters and a brief discussion of required inputs is provided for each model to further aid the user
                        in the selection process. A complete discussion of the model selection advisor and all its components is
                        provided in Chapter 2.

                        The Watershed Model is a lumped parameter, watershed-scale land use model. It is based on empirical
                        equations for runoff, erosion, and sediment yields. The model will estimate strem flow, runoff,
                        sediment yield, total and dissolved nitrogen, and total and dissolved phosphorus at the watershed outlet.
                        It can be used to estimate potential pollutant loads entering coastal waters as a result of land use
                        changes. A comprehensive discussion of the Watershed Model and its required inputs is provided in
                        Chapter 3.

                        The Manna Water Quality Model is a steady-state, two-dimensional model that can be used to estimate
                        coliform bacteria concentration, carbonaceous biochemical oxygen demand (CBOD), and nitrogenous
                        biochemical oxygen demand (NBOD). It is based on three analytical mixing and transport models that
                        describe the physical processes in wide channels, narrow channels, or sermi-enclosed bays. A
                        comprehensive discussion of the Marina Water Quality Model and its required inputs is provided in
                        Chapter 4.











                      The Tidal Prism Model is a dynamic, one-dimensional, segmented water quality model that considers
                      the tidal effects in estuaries and rivers. It can be used to estimate coliform bacteria concentration,
                      CBOD, or other contaminants subject to a first order decay. Each contaminant must be simulated
                      separately. A comprehensive discussion of the Tidal Prism Model and its required inputs is provided in
                      Chapter 5.

                      The Finite Section Model is a steady-state, one-dimensionaL segmented water quality model that does
                      not consider tidal effects m. the stream channel. It can be used to estimate coliform bacteria
                      concentration, DO, CBOD, and NBOD from point or known nonpoint sources. A comprehensive
                      discussion of the Finite Section Model and its required inputs is provided in Chapter 6.

                      The Spill Model is a dynamic, one-dimensional water quality model that can be used to estimate the
                      concentration of a pollutant "spilled" into a river or creek. The contaminant is assumed to be
                      completely Truxed vertically and axially and decrease over tune through first order decay. A detailed
                      discussion of the Spill Model and its required inputs is provided in Chapter 7.

                      The CS Model also includes several utility models to aid the user with quick, simple calculations.
                      Currently, there are utility models for determining dispersion coefficient estimation, DO saturation, and
                      Manning's open channel flow. A complete discussion of these models is provided in Chapter 8.

                      1.2 Notation Review
                      The following conventions are used throughout the user manual.

                      ï¿½   Keyboard strokes, menu choices, command buttons, and anything you are asked to type are printed
                          in boldface.


                      ï¿½   Keyboard strokes are surrounded by < >. For example, the "Enter" key is denoted as <Enter>.

                      ï¿½   Command buttons are surrounded by         For example, a "Close" command button is denoted as
                          [Close].

                      ï¿½   The terms "click on" and "select" refer to a specified mouse action. When you are told to click on
                          or select an item, locate the mouse cursor over the selected item and press the left mouse button. If
                          you prefer to use the keyboard instead of the mouse, you can navigate the model by using <Alt>
                          and the underlined letter of the desired menu or command option.

                      This manual uses standard Windows terminology. For users who are not familiar with the Windows
                      environment, some common elements of a window are described below.

                      Title Bar: Ile title bar displays the window@ title. Ile window title displayed in the CS Model
                      corresponds to the currently selected modeling option, however, when a component model is minimi@
                      the title bar returns to the general Coastal Screening Model title.

                      Menu Bar: - The menu bar at the top of each window displays the commands available for that
                      window. The main menu bar of the CS Model provides access to the individual models. When a
                      component model is selected, its menu bar becomes active. Menu bars for individual models provide
                      file and printer access.


                                                                                                                            1-2











                        Minimize Button: This is the button with the down arrow on the night side of the title bar. When this
                        button is selected, the window is reduced to its icon. Ile window can be maximized (returned to its
                        original size) by double-clicking on the icon. Ile CS Model and all its component models have
                        mmunize buttons and can be reduced to an icon.


                        Dialog Boxes: A dialog box requests or provides information, but does not have a menu bar. For
                        example, a dialog box will appear when the File/Open menu option is selected in any of the models.

                        List Boxes: A fist box provides a fist of available choices from which you must make a selection. To
                        select an item from the fist, move the mouse pointer to the desired item and click the left mouse button,
                        or access the list boxes by pressing the <Tab> key until the desired list box gains the focus and then
                        use the arrow keys until the desired item is highlighted. When space is limited, a "drop-down" list box
                        may be used. A drop-down list box displays only one entry. To access all of the available items, click
                        on the down arrow button next to the displayed fist item. A list box will appear beneath the originally
                        displayed item. Items in a drop-down fig box are selected in the same manner as a regular list box.

                        Scroll Bars: Some dialog and list boxes may contain more information than can be viewed in the
                        allocated area, so scroll bars will be added to allow the user to access all of the information. Scroll
                        bars contain an up and a down arrow as well as a scroll button. To scroll information line by line,
                        click repeatedly on one of the scroll arrows until the desired information comes into view. To page
                        through the fist quickly, click the scroll bar above or below the scroll button, or drag the scroll button
                        up or down the scroll bar.

                        Command Buttons: A command button performs a command or action when chosen by a user. When
                        selected, a command button not only carries out the appropriate action, but appears as if it's being
                        pushed in and released.

                        Option Buttons: Option buttons allow the user to select one option from the group. An option button
                        is activated by clicking on it or its description.

                        Check Boxes: Check boxes allow the user to decide whether or not some action should be taken. A
                        check box-is activated by clicking on it or its description. If a check box is selected, then its value is
                        true and the action it describes will occur. Unlike option buttons, check boxes operate independently of
                        each other and more than one can be selected within a group.

                        Text Boxes: A text box displays text that can be edited by the user. To change information in a text
                        box, click on the text box and t)W the new information. Text boxes can also be accessed by pressing
                        the <Tab> key until the desired text box gains the focus. In the CS Model, text boxes are used to
                        allow user input for model parameter values and can usually be distinguished by their white
                        background.

                        Spin Buttons: Spin buttons are a set of up and down arrows associated with a text box. Clicking on
                        either of the spin buttons will incrementally change the value in the text box.

                        Notebook: The component models utilize a notebook format to enter data and display model results.
                        Each page of the notebook can be accessed by clicking on the corresponding tab or pressing <Alt>
                        plus the underlined letter of the tab header.







                     1.3 System Requirements
                     You will need an EBM or EBM-compatible personal computer and a monitor that are capable of
                     running MicroSoft Windows (version 3.1 or higher). 'Me minimum system requirements include:

                           0 A 386-33 CPU
                           0 4 mega bytes (MB) of random access memory (RAM)
                           0   5 M]3 of fi-ee hard disk space
                           0   A VGA monitor with 16 colors


                     A 386-based system is technically sufficient, but depending on which component model is selected, the
                     processing time could be quite slow, particularly since the models are designed to run in an interactive
                     rather than a batch mode. The recommended system requirements are:


                           0 A 486-33 DX or 486-66 DX CPU
                           0 8 M13 of RAM
                           0   5 MB of fi-ee hard disk space
                           0   A VGA monitor with 256 colors


                     ï¿½ monitor operating in 256 color mode increases the clarity of map and picture displays.

                     ï¿½ mouse or other type of t-acking device is not strictly required by the program, but will greatly
                     improve the ease with which the models can be accessed and used.

                     1.4 Installation Procedures
                     'Me current setup process requires two steps. 'Me first install the CS model itself. Insert Disk I into
                     your disk drive. From the Fide menu of the Program Manager or File Manager, choose Run. Type <a:
                     setup (or b: if you are using the b drive). The set-up routine will prompt you for the path where you
                     want to install the program files. (Follow the set-up instructions on the screen). 'rhe second step
                     installs the ancillary data files and maps. Insert the Ancillary Disk 1 and run the setup.bat file. You
                     wiI1 be asked for the path where you insta lied the CS model.

                     1.5 Getting Started
                     To access the Coastal Screening Model, click on the Coastal icon from your Windows program
                     manager. The title bar and menu bar for the Coastal Screening Model will appear. The model
                     selection advisor or any of the component models can be accessed from Models on the menu bar.















                                                                                                                       1-4








                        2. Model Selection Advisor
                        The model selection advisor is designed to aid the user in determining which model is most applicable
                        for the current assessment Ile advisor divides the component models into two types: (1) water quality
                        models and (2) land use models. Since this version of the CS Model contains only one land use model,
                        the model selection advisor is most appropriate for selecting among the water quality models. If a land
                        use model is desired, the advisor can be used to view a brief description of the Watershed Model or to
                        activate the model, however, the Watershed Model can be activated directly from the menu bar.

                        The advisor contains a checklist of various water quality parameters and model options that the user
                        can select for each modeling effort. Based on the options selected by the user, the advisor determines
                        the appropriate model(s). If only one model fits the selected criteria, a screen containing a brief model
                        description appears. The user then has the option to perform another search or activate the selected
                        model. If the advisor selects more than one model, a model choice screen will appear, and the user can
                        view a description for each of the selected models. The user then has the option to perform another
                        search or activate one of the selected models.


                        Section 2.1 contains a detailed discussion of modeling and types of models. Section 2.2 discusses how
                        to access and navigate through the advisor. A description of all the water quality parameter options
                        available within the advisor is provided in Section 2.3. Criteria for final model selection am discussed
                        in Section 2.4.

                        2.1 Model Types
                        The CS Model is composed of both a land use model and several water quality models. These model
                        types are explained in greater detail in the following subsections. While all of these models are
                        available, none of them are linked together. Each component model operates seperately.

                        Models are a conceptualization of how the "real" world operates. No model completely reflects reality,
                        but models can be useful improving our understanding of natural systems and in assessing
                        anthropogenic impacts on these systems. Models can be defined in a vari ety of ways.

                        Empirical models are commonly termed "black box" models. These models use equations that are
                        derived from measured data, but do not attempt to describe all of the physical properties that are
                        involved in assessing the data. For example, fide charts have been developed based on the measured
                        tidal cycles. The use of these values does not require a complete understanding of how tides are
                        generated. It just important to know under what conditions the charts are valid. Empirical equations
                        explain the measured data for the given conditions. As conditions vary from the ones applied during
                        the equation development, the validity of the empirical equation is reduced. With greater number of
                        measured values and testing conditions, the applicability of the equations increases.

                        Many models use equations that attempt to reflect the processes involved. The factors in the equations
                        are based on real world processes. The advective-dispersive transport equation applied in many water
                        quality models is an example of a process model.







                                                                                                                           2-1









                      2.1.1 Land Use Models
                      Land use models evaluate the loadings of some constituent from the upland areas to a water body.
                      Typically modeled parameters include sediment and nutrients. Most land use models examine the
                      loadings from an entire watershed, are a commonly termed watershed models.

                      Watershed models can be either lumped or distributed parameter models. A lumped parameter model
                      will assess the loadings from each land use without considering the spacial variations or stream
                      routing. Each designaW land use is assumed to be uniform and have constant soil and cover
                      properties. A distributed parameter model allows for spatial variation. Typically, the watershed is
                      divided into a grid of cells, where each cell has defined land use, topography, and soil properties. ne
                      overland flow is routed from cell to cell or to a defined stream channel. A distributed parameter model
                      provides loadings throughout the watershed, not just at the watershed oudeL It also allows for
                      upstream land uses to impact downstream land use.

                      2.1.2 Water Quality Models
                      Water quality models evaluate the water quaI4 constituents in the water column of a stream or river.
                      Ile complexity of the model will depend on the number of stream dimensions that are being modeled,
                      whether temporal variations are being considered, and whether the solution is analytical or numerical.

                      Most water quality models are based on the principle of the conservation of mass. All system outputs
                      must equal system inputs. T'he mass balance calculation is performed for specified volumes of water
                      over a given time period. Material balances typically involve dissolved or suspend substances, such as
                      organic carbon, nitrogen, phosphorus, suspended sediment, and dissolved oxygen. This principle can
                      be applied to any substance whose transformation kinetics am known (McCutcheon and French, ?).
                      2.2 Operating the Advisor
                      To access the model selection advisor, select Models/Advisor from the main menu. The advisor
                      prompts you to select the type of model desired.

                      To select a land use model, click on the corresponding option button or enter <Alt L>. A screen
                      displaying the description of the Watershed. Model will appear. The model can be activated by
                      selecting [Run Model]. If you do not wish to run the model at this time, choose [Close] to return to
                      the main advisor screen.


                      To select a water quality model, click on the corresponding option button or enter <Alt W>. A screen
                      displaying all the parameter options will appear (Figure 2- 1). Ile various model options are grouped
                      by parameter type. Each of these parameter options is explained in Section 2.3. Select the desired
                      options by clicking on the appropriate option buttons or check boxes. The parameter option groups
                      can also be accessed by using the <Tab> key. Once the focus is on the desired parameter option
                      group, individual options can be selected using the up and down arrow keys.









                                                                                                                             2-2














                                                              Model Selection Advisor
                                 . . . ........... .... .....


                                                                             .. ........ .
                                                                             pa, M-M

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


                                                                                . .........


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


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


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


                                           ........ . .......
                                                                                  11 ...                          .......


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


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

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


                                                                                                   .................
                                                                                                   ..... . ....... ... ...
                                                                                           X, EX@--@:i
                                                                   .............


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


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




                                           ......................
                                                                                  .......... .                      ...
                                                                                   ..............-
                                                                       ........................
                                          Rim                                            . . . . . . . .
                                                                                   . .....                          ....
                                                                                                                . . . . . . . . . .
                                                                                        . . . . . . . . . . . . . .

                              Figure 2-1.  Model selection advisor parameter options.



                       After all the desired parameter options are selected, choose the [Start Advisor] button by either
                       clicking on it or pressing <Alt A>. The advisor will determine which models best match the desired
                       criteria. If only one water quality model matches the selected parameter options, a screen will appear
                       that provides a brief description of the model. You can either choose [Run Model] to activate the
                       selected model or [Close] to return to the parameter options screen. If more than one model meets the
                       desired criteria, a model choice screen will appear. The names of the water quality models that best
                       match the selected options are displayed on command buttons. To learn more about a particular model
                       or to activate a model, click on the command button displaying its name or press <Alt> and the
                       underlined letter in its name. A screen will appear that provides a brief description of the model.
                       Choose (Run Model] to activate the selected model, [Return] to return to the model choice screen to
                       evaluate other model options, or [Close] to return to parameter options screen.

                       2.3 Water Quality Parameters
                       The parameter options for water quality models are divided into five categories. Each of these
                       categories and the possible options are discussed in detail in the following subsections. Several of the
                       categories contain an (Unimportant] option. If this option is selected in any of the categories, then
                       that category is not used by the advisor during the model selection process. T'he water quality
                       parameters option group does not contain an [Unimportant] option. It is assumed that the user will
                       always be trying to model for at least one of these parameters.







                                                                                                                           2 - _3










                       To select the desired water quality parameters simple click on the appropriate option button or check
                       box. Ile various frames housing the options can be accessed using the <Tab> key. Once the desired
                       fi-arne has gained the focus, use the arrow keys to select the desired option(s).

                       2.3.1 Dimensions
                       Water quality models are classified based on the importance of longitudinal, laterad, and vertical
                       variations in the water quality constitutents. As more aspects of the stream are considered, the
                       complexity of the equations required to describe the variations increase. While water quality models
                       can be zero-, one-, two-, or three-dimensional, the component models included with the CS Model are
                       only one- or two-dimensional.

                       A one-dimensional model considers only the longitudinal variations in describing stream water qualiy.
                       It is assumed that "mixing processes will provide complete mixing both laterally and vertically, such
                       that the concentrations gradients are only along the axis of the river" (Thomann and Mueller, 1987).

                       A two-dimensional model will consider the water quality variations in two directions. Most two-
                       dimensional water quality models describe variations in the longitudinal and lateral direction and
                       assume complete vertical integration.

                       The selection screen includes a branching one dimensional model option which will be implemented in
                       future versions.


                       2.3.2 Time
                       This option addresses how water quality models address temporal variations. A model is classified as
                       being either steady-state or dynamic. A steady-state model provides an analysis for a specific set of
                       input conditions for some point or period of time (Basta and Moreau, 1982). A steady-state model can
                       also consider two or more time periods that are seperated by some number of time periods if there is no
                       analysis of these intervening time periods. In contrast, a dynamic model will examine successive time
                       periods, where the inputs from the first time period will affect the inputs into the second time period.
                       The analysis is much more complex than for models utilizing steady-state conditions.

                       2.3.3 Loadings
                       Point sources provide a constazit input to the stream from a specified location along the channel.
                       Typical point sources include wastewater treatment plants and processing plants. Nonpoint source
                       discharges are generated by overland flow and do not originate from one fixed location. Nopoint
                       source loadings are typically calculated by the use of a watershed model. However, some models can
                       consider a known nonpoint source load as an additional input.

                       2.3.4 Tidal
                       This option allows the user to decide if the effects of tidal variations should be explicitly considered.
                       Most water quality models address average tidal responses in the dispersion coefficient.

                       2.3.5 Water Quality Parameters
                       The water quality parameters are the constituents that one of the component water quality models will
                       be evaluating. Except for salinity, these parameters are typically selected as indicators of stream health
                       and water contamination. Salinity is typically modeled to establish dispersion coefficients.



                                                                                                                                 2-4









                         Carbonaceous Biochemical Oxygen Demand (CBOD)@. CBOD is an indicator of organic pollution
                         measured in terms of the oxygen demand that can develop as the organics are degraded. Units are
                         commonly in mg/L.

                         Nitrogenous Oxygen Demand (NBOD): NBOD is the equivalent measure of the organic nitrogen
                         and ammoma, that will consume oxygen as they are converted to mtrite and nitrate. Units are
                         commonly in mg/L.

                         Dissolved Oxygen (DO): A direct measure of the amount of oxygery dissolved within the water. Units
                         are commonly in mg/L.

                         Coliforms: Colifbnns are bacteria in the Enterobacteriaceae fiiniily and are commonly use as an
                         indicator of fecal contamination. The coliforin group includes Escherichia coli, Enterobacter
                         aerogenes, and KkbsielZa pneumoniae. These organisms make up approximately 10 percent of the
                         intestmal microorganisms found in humans and other ammals. Coliforms are used as an indicator
                         species because they lose viability in water at slower rates than most of the major intestinal bacterial
                         pathogens (Prescott et aL, 1990). Water quality and potability is commonly evaluated by testing for
                         the presence of coliforni bacteria. Units are usually measured in the number of organisms/L.

                         Salinity: Salinity is a measurement of the salt concentrations in the water column. It is commonly
                         used to calibrate a finite section model for dispersion. It is trwted as a conservative material. Usually,
                         the only loads for salinity arise at the mouth of the estuary or river.

                         2.4 Model Selection
                         The model selection advisor counts the total number of options selected by the user and compares this
                         value to the number of these options that apply to each of the water quality models. The model that
                         matches the greatest number of options is selected. Under this scheme, each option has equal value.
                         This assumption may not reflect the needs of the user. The user may want one of the criteria to be
                         more significant than the others and this is not possible with the current equal weighting scheme. If
                         there is a critical option, the user can run the advisor with only that option selected and the other
                         parameters set to [Unimportant].

                         The model selection advisor can be a useful tool for model selection, especially when the user is first
                         becoming fluniliar with the various component models, however, there is no substitute for good
                         professional judgment. The user should become familiar with the characteristics, assumptions, and
                         limitations of all the component models to be able to accurately estimate input parameters and to assess
                         the model results.


















                                                                                                                                 2-5









                     3. Watershed Model
                     The Watershed Model is based on the Generalized Watershed Loading Functions model developed by
                     Haith et al. (1992) at Cornell University. The model predicts monthly and annual sediment, nitrogen,
                     and phosphorus loadings from complex watersheds. The Soil Conservation Service (SCS) Curve
                     Number Equation and the Universal Soil Loss Equation are used to predict runoff and erosion,
                     respectively. Individual land uses, point sources, and septic systems are evaluated. The Watershed
                     model is a lumped parameter model, and therefore, land use is considered uniform with respect to soil
                     and cover.

                     3.1 Modeling Approach
                     'Me Watershed model features a simple, daily time step hydrologic budget as depicted in Figure 3-1.
                     The daily unsaturated and shallow saturated zone water budget for day t in cm is



                        Precipitation
                          I I      I
                                         Evapotranspiration






                                               Inf, tmtion


                        Unsatura
                        Zone                                        Runoff



                                                  Percolation
                                                                                                               Soil
                                                                                                               Surface


                                                                                         Stream Channel











                     Figure 3-1. Conceptual model of a watershed, adapted from Haith et al, 1992.




                                                                                                                          3-1






				U t+1 = Ut + Rt + Mt - Qt - Et - PCt

				S t+1 = St + PCt - Gt - Dt

			where Ut    = unsaturated zone soil moisture
				St	= shallow saturated zone soil moisture
				Rt	= rainfall
				Mt	= snowmelt 
				Qt	= watershed runoff Qxt, for all land uses k
				Et	= evapotranspiration
				PCt	= percolation into the shallow saturated zone
				Gt	= groundwater flow into the stream
				Dt	= deep seepage flow into the deep saturated zone
		
		Values for rainfall and snowmelt are provided by the included weather files.  Watershed
		runoff is calculated by the SCS Curve Number Equation as

				Qkt	= (Rt + Mt - 0.2DSkt)2
					   __________________
						
					   Rt + Mt + 0.8DSkr

		where DSkt is the storage detention parameter.  A more detailed discussion of curve numbers and how
		either (CVtPEt) or (Ut + Rt + Mt - Qt), where CVt is a cover coefficient and PEt is the potential
		evapotranspiration.  Hamon (1961) described the potential evapotranspiration as

				PEt	= 0.021H2tet
					  __________

					  Tt + 273

		where Ht is the number of daylight hours per day during the month containing day t, et is the saturated
		water vapor pressure in millibars on day t, and Tt is the temperature on day t in degree C.  When Tt is 
		less than or equal to 0, then PE is set to zero.  Bosen (1960) approximated teh saturate vapor pressure as

			et = 33.8639 [(0.00738Tt + 0.8072)8 -0.000019(1.8Tt + 48) + 0.001316], for Tt greater than or = to 0

		Percolation occurs when unsaturated zone water exceeds the available soil water capacity (U*) and is 
		the maximum of either zero or (Ut + Rt + Mt - Qt - Et - U*).

		The groundwater discharge and deep seepage are modeled as a simple linear reservoir as described by
		Haan (1972) by the following equations:

			Gt = r St
	
			Dt = s St

		where r is the groundwater recession coefficient and s is the seepage coefficient.  These coefficients are
		described in Section 3.4.

	


																			3-2	 	







                       3.1.1 Septic Systems
                       The septic system option in the Watershed Model is based on research presented by Mandel (1993).
                       The model will calculate the dissolved nutrient loads from septic system under four conditions:
                       nomt-A short-circuited, ponded, and direct discharge. These loads are determined from the per capita
                       daily effluent loads and the monthly population being served by septic system in each condition.

                       Normal Systems: These septic systems conform with guidehnes and standards suggested by the
                       USEPA and are in compliance with state regulations. The effluent from these systems infiltrates into
                       the shallow saturated zone. Nitrogen in the effluent is considered to be either removed by plant uptake
                       or converted to nitrate and transported to the stream by ground water discharge. While normal systems
                       contribute to dissolved nitrogen, the model does not consider phosphorus inputs. It is assumed that any
                       phosphorus from the effluent becomes adsorbed to soil particles, and hence, does not leave the system.
                       Since normal septic systems are operating properly, they are generally located away from streams.
                       This means that as the dissolved nitrogen from the effluent move through the shallow saturated zone, it
                       is diluted by other groundwater sources. Thus, the Watershed Model makes the monthly dissolved
                       nitrogen load proportional to the groundwater discharge to the stream.

                       Short-Circuited Systems: These septic systems have been placed in an inappropriate location, and
                       the effluent is not being properly treated by the septic field. These systems are located too close to
                       surface waters, and therefore, negligible adsorption of phosphorus occurs. The only mechanism for
                       nutrient removal is plant uptake. The Watershed Model computes dissolved loads for both nitrogen
                       and phosphorus.

                       Ponded Systems: Ponded septic systems are the result of hydraulic overload or hydraulic failure.
                       The effluent from these systems "ponds" over the adsorption field. If the temperature is below
                       fiwzing, than the ponded effluent is assumed to fi-eeze and nutrients can accumulate. Monthly nutrient
                       loads from these systems consider whether or not nutrients have accumulated due to frozen conditions.

                       Direct Discharge: These systems are illegal and discharge effluent directly to surface waters. The
                       nutrient loads from these systems are based solely on the per capita tank effluent and the population
                       served. Removal by plant uptake is not considered. These systems contribute to dissolved loads of
                       both nitrogen and phosphorus.

                       3.2 Model Format
                       The Watershed Model utilizes a notebook format to enter data and display model results. The first eight
                       notebook pages provide screens for input data and the last two notebook pages are used to present
                       tabular and graphical model results, respectively. Each page of the notebook can be accessed by
                       clicking on the corresponding tab or pressing <Alt> plus the underlined letter of the tab header.
                       Comprehensive discussions regarding model input and parameter estimation are provided in Section 3.3
                       to Section 3.9. Each of these sections corresponds to an individual notebook page in the Watershed
                       Model. Simulation results and model output are discussed in Section 3. 10.

                       For each notebook page used to enter data, there is an example data set. This data set can be used as a
                       tutorial for the Watershed Model. To access this data click on the [Example Data] buttons on each
                       notebook page. There is data available to meet all model options. The example weather file must also
                       be selected from the weather file list box. These data can be used to become familiar with how to
                       navigate through the model and it provides an example of typical input and model results.



                                                                                                                                3-3











                        The first notebook page, Project Info, serves as the Watershed Model's introductory screen. This
                        notebook page can be used for record keeping purposes. There are text boxes available to enter in the
                        project title, project number, date, and the names of the individuals involved with the model run. This
                        notebook page may be omitted if desired.

                        "Me menu bar on the Watershed Model provides the user with file access, editing capability, and help
                        information. Selecting FiJe will display a drop-down menu list with the following items: New, Open,
                        Save, Save As, Print, and Exit. New deletes the current data set. A message box will ask for
                        verification prior to deleting current values. Open calls up the Open File dialog box to select an
                        existing data set. Save will save the current data set using the existing file name. If a file name has not
                        been defined, the Save As File dialog box will appear prompting the user to enter a file name. Save As
                        opens the Save As File dialog box to allow the current data set to be saved with a new file name.
                        Selecting Print will call up the Print File dialog box. The user can select to print the input data and/or
                        any of the tabular output displays. Note that graphs are not printed from this menu item. The graphs
                        are printed directly from the Graphical Output notebook page using the [Print Graph] command
                        button. Eidt closes the Watershed Model and returns the user to the main CS Model window. If the
                        current data set has not been saved, it will be lost. Selecting Edit will display a drop-down menu fist
                        with Cut, Copy, and Paste. These menu items can be used to edit input data. Cut will remove the
                        selected text and move it to the windows clipboard. Copy will place a duplicate of the selected text on
                        the clipboard, but not remove the original text. Paste can be used to put text placed on the clipboard
                        back onto one of the input screens. Help will provide information pertaining to the Watershed Model.

                        3.3 Program Options
                        rhe Watershed Model will simulate stream flow, sediment yields, nutrient loads, and septic system
                        inputs. Click on the desired model option or press the <Tab> key to gain access to the option group
                        and use the arrow keys to select the desired model option. The required input parameters will vary
                        depending on the model option selected. Any notebook pages that contain unnecessary input
                        information for the selected model option Will have "greyed' tabs. These tabs are disabled, which
                        means that the user no longer has access to these pages. This feature aids the user 'in determining what
                        information is required to run the model.

                        3.3.1 Hydrologic Unit Data
                        Regardless of which model option is selected, land use data must be entered. If the land uses of the
                        watershed being modeled are not known, land use values can be retrieved from the Hydrologic Unit
                        Database (HUD). Hydrologic units define watershed boundaries and the HUD contains land use
                        information for each hydrologic unit in Virginia. The database information was provided by the
                        Virginia Department of Conservation and Recreation, Division of Soil and Water Conservation.
                        Acreage values were supplied for 13 land uses: cropland, hay, orchard, idle hawiland, Agricultural
                        Stabilization and Conservation Service (ASCS) set aside, Conservation Reserve Program (CRP) land,
                        pastureland, forest, urban residential, urban industrial, urban other, waterbodies, and Christmas trees.
                        This data was restructured to provide the VMRC with more manageable land use categories and to
                        meet the input requirements of the Watershed Model. Data for waterbodies were discarded because
                        they are not applicable to the Watershed Model. Acreage values for orchards and Christmas trees were
                        combined into one land use category since these two land uses would have similar model *input values.
                        Farmland that is enrolled in the CRP or has been designated as an ASCS set aside is not in production.
                        These land uses are likely to have model input values which are similar to idle farmland, and therefore-



                                                                                                                             3-4









                       their acreage values were combined with the acreage valu Ies for idle flirmland in each hydrologic unit.
                       This restructuring of the database information yielded nine land use categories in the HUD. Upon
                       completion of the database restructuring, the acreage values for these nine land uses were converted to
                       hectares to meet the model input requirements.

                       To access the HUD, select the [Yes] option under "Use Hydrologic Unit data?". A frame will appear
                       that contains a drop-down list box for selecting the appropriate hydrologic unit If the appropriate
                       hydrologic unit is not known, it can be determined by using the map viewer. The map viewer list box
                       contains the names of all the counties in tidewater Virginia. Select the name of the county where the
                       watershed currently being modeled is located and choose the [View] command button. A picture box
                       containing a map of the selected county will be displayed. The map defines all of the hydrologic units
                       within the county. Various parts of the map can be viewed by'selecting one of the command buttons
                       beneath the picture box or using the horizontal and vertical scroll bars. Once the appropriate
                       hydrologic unit has been determined, select that value from the hydrologic unit list box and choose
                       (Close] to exit the map viewer. The types of land uses and their corresponding areas will automatically
                       be entered into the Land Uses notebook page.

                       Because land use information changes over time, the Virginia Department of Conservation and
                       Recreation, Division of Soil and Water Conservation should be periodically contacted to obtain the
                       most recent data.


                       3.3.2 Climate Data
                       The Watershed Model requires temperature and precipitation data. This data is provided for nine
                       locations in Virginia@ Table 3-1 contains a detailed description of the location where the climate data
                       was collected and can be used to select the most appropriate weather file for the area being modeled. A
                       tenth weather file provides climate data that corresponds to the example data seL Use the scroll bar to
                       view all the available weather files and select the desired weather file by clicking on it.

                       The weather files are organized by month. The first entry is the number of days in the month and
                       subsequent entries are daily temperature ( *Q and precipitation (cm) values. The weather files are
                       arranged to correspond to the assumptions of the model. "Both the groundwater and sediment portions
                       of the model require that simulated years begin at a time when soil moisture conditions are known and
                       runoff events have flushed the watershed of the previous year's accumulated sediment" (Haith et al.,
                       1992). In Virginia, this corresponds to early spring, and therefore, the weather files provided with the
                       model are arranged in April to March weather years.

                       The climate data was provided by the USGS and converted to the format required by the model. Daily
                       maximum and minimum temperatures were averaged and then converted from Fahrenheit to Celsius.
                       Daily precipitation values were converted from inches to centimeters. Some of the weather files
                       contained data gaps. For a missing daily temperature measurement, the temperatures from the day
                       prior to and after the missing measurement were averaged. For a missing daily precipitation
                       measurement, the value was set to zero. If there were numerous missing measurement points or
                       consecutive missing measurement points, then the data for the entire year was discarded.

                       After a weather file has been selected, the length (number of years) of the climate record will be
                       displayed in the simulation time text box. The simulation length cannot exceed this value, but a shorter
                       simulation time may be entered. To enter a value in the text box, move the mouse cursor to the text




                                                                                                                            3-5









                         box and click the left mouse button to set the focus to the text box and then type the desired simulation
                         length.



                                             Table 3-1. Weather File Locations and Record Lengths

                                                         Station
                         Location                          No.           Lat              Long                     Dates
                         Blackstone FAA Airport            773        N37:05:00       W077:57:00       April 1949 - March 1972
                         (Nottoway County)                                                             (23 years)
                         Corbin                            2009       N38:12:00       W077:22:00       April 1959 to March 1992
                         (Caroline County)                                                             (33 years)
                         Louisa                            5050       N38:02:00       W078:00:00       April 1949 to March 1992
                         (Louisa County)                                                               (minus 1968, incomplete)
                                                                                                       (42 years)
                         Nassawadox                        5931       N37:28:00       W075:52:00       April 1957 to March 1976
                         (Northampton cEintj)                                                          (19 years)
                         Onley 1 S                         6362       N37:41:00       W075:43:00       April 1930 to March 1955
                         (Accomack County)                                                             (25 years)
                         Richmond WSO Airport              7201       N37:30:00       W077:20:00       April 1942 to March 1992
                         (Henrico County)                                                              (minus 1951, incomplete)
                                                                                                       (42 years)
                         Wallops Island WSSF               8849       N37:56:00       W075:28:00       April 1967 to March 1980
                         (Accomack County)                                                             (13 years)
                         Warsaw 2 N                        8894       N37:59:00       W076:46:00       April 1951 to March 1992
                         (Richmond County)                                                             (I =*Us 1970, incomplete)
                                                                                                      1(40 years)
                         Washington WB; Chantilly          8903       N38:57:00       W077:27:00       April 1963 to March 1992
                         (Loudon County)                                                               (29 years)


                         3.4 Initial Conditions
                         The values for the initial conditions can be entered directly into each text box by clicking on it and then
                         entering the desired value from the keyboard. The text boxes may also be accessed using the <Tab>
                         key. As each text box becomes active, its corresponding label win turn blue.

                         Unsaturated Available Water Capacity (U*): 'Me available unsaturated zone soil moisture capacity
                         is used to estimate percolation to the groundwater, which occurs when the unsaturated zone water
                         exceeds the available soil water capacity (Haith et al., 1992). "In principle, U* is equivalent to a mean
                         watershed maximum rooting depth multiplied by a mean volumetric soil available water capacity. The
                         latter also requires determination of a mean unsaturated zone depth, and this is impractical for most
                         watershed studies. A default value of 10 cin can be assumed for pervious areas, corresponding to a
                         100 cm rooting depth and a 0. 1 cm/cm volumetric available water capacity" (Haith et al., 1992).
                         Selecting the [Defaultj button will assign a value of 10 cm to U*.

                         Sediment Delivery Ratio: Ile sediment delivery ratio is the ratio between the amount of sediment
                         yield and the gross erosion in a watershed (Gottschalk, 1964).



                                                                                                                                  3-6










                       Table 3-2 shows the effect of drainage basin size on the sediment delivery ratio. Figure 3-2 provides a
                       commonly used area-based relationship from Vanoni (1975) that can be used to estimate the sediment
                       delivery ratio based on the area of the watershed being modeled. Since the sediment delivery ratio is
                       very site specific, selecting the [Default] button will not provide a value for this parameter.



                                       Table 3-2. Sediment Delivery Ratio Based on Watershed Size
                                            Drainage Area (lan)                Sediment Delivery Ratio (percent)
                                                       0.1                                       53.0
                                                       0.5                                       39.0
                                                       1.0                                       35.0
                                                       5.0                                       27.0
                                                      10.0                                       24.0
                                                      50.0                                       15.0
                                                      100.0                                      13.0
                                                     200.0                                       11.0
                                                     500.0                                       8.5
                                                    26,000                                       4.9
                                   Sow=. Robiuson, 1979.






                                                          Watershed Sediment Delivery Ratio



                                                                            I lit        I   I   III





                                .2


                                                                             it
                                M                                              @.- I               I
                                     0.1


                                                                                           1 17%- 1           1 It








                                    0.01
                                         1                 10                 100                1000               10000

                                                                     Watershed Area (kmj


                              Figure 3-2. Watershed sediment delivery ratio, adapted from Vanoni, 1975.


                       Recession Coefficient (r): The baseflow recession coefficient is used to determine ground water
                       discharge to stream flow. Standard hydrograph separation techniques can be used to estimate the
                       recession coefficient from stream flow records.




                                                                                                                               3-7











                        Recession coefficients are measured for a number of hydrographs and an average value is used for the
                        simulations. Typical values range from 0.0 1 to 0.2. The [Defaulti button supplies an arbitrary value
                        Of 0. 1.


                        Seepage Coefficient (s): ne rate constant for deep seepage loss is used during the calculation of the
                        groundwater discharge to stream flow. The seepage coefficient is multiplied by the daily shallow
                        saturated zone soil moisture to determine the amount entering into the deep saturated zone, and thereby
                        leaving the watershed. There are no standard techniques available fbr estimating the seepage
                        coefficient. If the coefficient cannot be determined by calibration, then a conservative approach is to
                        assume that all precipitation exits the watershed by either evapotranspiration or stream flow, and
                        therefore deep seepage equals zero. Selecting the [Default] button will set s to zero.

                        Unsaturated Storage - The initial unsaturated soil zone moisture in cm.
                        Saturated Storage - The initial shallow saturated soil zone moisture in cm.
                        Snowmelt Water - The amount of snow melt water in cin at the beginning of the simulation.
                        Antecedent Rain and Melt - The amount of ram and snow melt for the five previous days.

                        'Me preceding four parameters are difficult to characterize, but they will not affect simulation results
                        beyond the first several months. To ameliorate this problem, assign arbitrary values to these initial
                        conditions and discard the results from the first year of the simulation. A common approach is to
                        assign the value of the unsaturated available water capacity (U*) to the unsaturated storage and zero to
                        the remaining variables. The [Defaultl button will assign a value of zero to all the following variables,
                        except for unsaturated storage, which is assigned 10 cm.

                        Selecting the [Example Data] button will provide initial conditions data for the example watershed.
                        To provide reasonable output data, this data should be used in conjunction with the example data
                        provided for the other input parameters and the example weather file.

                        The (Cancel] button will clear all values from the initial conditions text boxes. If this button is
                        selected, a message box will appear asking for verification prior to deleting current values.

                        3.5 Land Use Information
                        A minimum of one land use with a non-zero area (in hectares) must be specified prior to beginning any
                        simulation. A land use without a corresponding area value- is not allowed. To model land use changes
                        over time, a run must be performed with the initial land use cover and then a second run must be
                        performed with the modified land uses.

                        Land uses are divided into two categories: rural and urban. This separation is required because of
                        model formulation. The Watershed Model uses a modification of the Universal Sod Loss Equation
                        (USLE) to determine erosion from rural sources. The USLE was not developed for urban land uses,
                        and is therefore not applied to these areas. In addition, the model will calculate both a dissolved and a
                        solid phase nutrient load from rural sources, but urban nutrient loads are modeled as being entirely a
                        solid phase.

                        To enter land use values into either the Rural Land Use or the Urban Land Use spreadsheet simply
                        click on the desired cell. "Me spreadsheets can also be accessed using the <Tab> key. Once the
                        desired spreadsheet.has gained the focus, use the arrow keys to move from cell to cell. For each land


                                                                                                                            3-8










                       use in the watershed, enter its name and area in hectares. : If the land use name you wish to enter is two
                       words, enter the name without a hyphen. When the model graphs the results, it will use the first two
                       letters from each word in the name for the graph label if the name consists of two discrete words. For
                       example, the land use "Impervious Residential" would have a graph label of "Im-Re". but a land use
                       designated as "Impervious-Residential" would have a graph label of "Imper".

                       Rows my be removed or added to either the Rural or the Urban Land Uses spreadsheets by clicldng on
                       the (Delete Row] or [Insert Row] buttons. When either of these command buttons are selected, the
                       active raw in the spreadsheet will be altered accordingly.

                       Selecting the (Example Data] button will provide land use data fbr the example watershed. To provide
                       reasonable output data, this land use data should be used in conjunction with the example data
                       provided for the other input parameters and the example weather file.

                       The [Cancel] button will clear aU values from both the Rural and the Urban Land Uses spreadsheets.
                       If this button is selected, a message box will appear asidng for verification prior to deleting all cell
                       values.


                       3.5  *1 Runoff Curve Numbers
                       For each rural and urban land use entered in the spreadsheet, a runoff curve number (CN) must be
                       assigned. Curve numbers represent a relationship between precipitation and runoff volume. Ile Soil
                       Conservation Service developed a method to estimate excess rain volume (runoff) based on the
                       precipitation volume and the volume of total storage. The storage parameter (DS) in centimeters is
                       obtained from the equation
                                           DS = 2540 - 25A
                                                   CN
                       Curve numbers exist for three antecedent moisture conditions: (1) CNlk is for below-average (dry)
                       moisture conditions; (2) CN2k is for average moisture conditions; and (3) CN3,, is for above-average
                       (wet) moisture conditions. The Watershed Model requires CN2k to be input. The model computes the
                       values for CN I k and CN3k from CN2k. During simulations, the model will evaluate the current
                       moisture conditions and supply the appropriate curve number. Table 3-3 to Table 3 )-5 contain
                       suggested curve numbers for average antecedent moisture conditions (CN20 for a variety of land uses
                       and are based on soil hydrologic groups. A description of the four soil hydrologic groups, for both
                       undisturbed and disturbed soils, is provided in Table 3-6. Disturbed soils are characterized by a major
                       alteration of the soil profile, as would occur from construction or development.















                                                                                                                                  3-9









                                  Table 3-3. Runoff Curve Numbers for Cultivated Agricultural Land
                                                                         Hydrologic           Soil Hydroi Zic Group
                        Land Use/Cover'                                  Conditionb        A         B       C    I  D
                        Fallow Bare Soil                                 N/A               77        86      91      94
                        Crop Residue Cover                               Poor              76        85      90      93
                                                                         Good              74        83      88      90
                        Row Crops               SR                       Poor              72        81      88      91
                                                                         Good              67        78      85      89
                                                SR + CR                  Poor              71        80      87      90
                                                                         Good              64        75      82      85
                                                C                        Poor              70        79      84      89
                                                                         Good              65        75      82      86
                                                C+CR                     Poor              69        78      83      87
                                                                         Good              64        74      8 r     85
                                                                         Poor              66        74      so      82
                                                                         Good              62        71      788     81
                                                C&T + CR                 Poor              65        73      79      81
                                                                         Good              61        70      77      80
                        Small Grains            SR                       Poor              65        76      14      11
                                                                         Good              63        75      83      87-
                                                SR+CR                    Poor              64        75      83      86
                                                                         Good              60        72      80      84
                                                C                        Poor              63        74      82      85
                                                                         Good              61        73      81      84
                                                C+CR                     Poor              62        733     81      84
                                                                         Good              60        72      80      83
                                                C&T                      Poor              61        72      79      82
                                                                         Good              59        70      78      81
                                                C&T + CR                 Poor              60        71      78      81
                                                                         Good              58        69      77      80
                        Close-seeded or         SR                       Poor              66        77      85      89
                        Broadcast Legumes                                Good              58        72      81      85
                        or Rotation Meadow      C                        Poor              64        75      83      85
                                                                         Good           1  55    1   69      78      83
                                                C&T                      Poor              63        73      80      83
                                                                         Good              .51       67      76 f    80
                        Source. Soil Conservation Service, 1986.
                        ' CR = Crop Residue; SR = Straight Row, C = Contoured-, C&T = Contoured and Terraced
                        bHydrologic condition is based on a combination of factors that affect infiltration and runoff, including: (1) density and
                        canopy of vegetative areas, (2) amount of year-round cover, (3) amount of close-seeded legumes in rotations, (4) percent
                        of residue cover on the land surflice (good @: 20%), and (5) degree of surface roughness.












                                                                                                                     3-10











                                                Table 3-4. Runoff Curve Numbers for Other Rural Land

                                                                                          Hydrologic                So' Hydrol *c Gro P
                          Land Use/Cover                                                  Condition              A           B          C         D
                          Pasture, grassland or range - continuous forage                 Poor                   68          79         86        89
                          for grazine                                                     Fair                   49          69         79        84
                                                                                          Good                   39          61         74        80
                          Meadow - continuous grass, protected from                       N/A                    30          58         71        78
                          grazing,_ generally mowed for hay                                                                                   I
                          Brush - brush/weeds/grass mixture with brush the                Poor                   48          67         77        83
                          major elemen?                                                   Fair                   35          56         70        77
                                                                                          Good                   30          48         65        73
                          Woods/grass combination (orchard or tree fim)c                  Poor                   57          73         82        16
                                                                                          Fair                   43          65         76        82
                                                                                          Good                   32          58         7Z        79
                          Wood?                                                           Poor                   45          66         77          3
                                                                                          Fair                   36          60         73        79
                                                                                                                                                  77
                                                                                          Good               1   30          55         70
                          Farmsteads                                                      N/A                    59     1    74         82        86
                          Source: Soil Conservation So-vice, 1986.
                            Poor. <50% ground cover or heavily grazed with no mulch; Fair. 50-701/6 ground cover and not heavily grazed; Good:
                            >75% ground cover and lightly or only occasionally grazed.
                          b poor
                                 . <50% ground cover, Fair. 50-70% ground cover, Good: >75% ground cover.
                            Estimated as 50% woods and 50% pasture.
                          d Poor. forest litter, small trees and brush are destroyed by heavy grazing or regular burning; Fair. woods are grazed but
                            not burned and some forest litter covers the soils-, Good: woods are protected from grazing and litter and brush
                            adequately cover the soil.











                                                 Table 3-5. Runoff Curve Numbers for Urban Areas

                                                                                                           Soil Hydrolozic Gro v
                          Land Use/Cover                                                                 A          B        C        D
                          Open space (lawns, parks, golf courses, cemeteries, etc.):
                             Poor condition (grass cover < 50%)                                          68         79       86       89
                             Fair condition (grass cover 50-75%)                                         49         69       79       84
                             Good condition (grass cover> 75 %)                                          39         61       74       80
                          Paved parldng lots, driveways, roofs, etc.                                     98         98       98       98
                          Streets and roads:
                             Paved with curbs and storm sewers                                           98         98       98       98
                             Paved with open ditches                                                     83         89       92       93
                             Gravel                                                                      76         85       89       91
                             Dirt                                                                        72         82       87   _j  89
                                                                  Average Imperviousness" (0/0)                                 -
                          Residential average lot size,
                             0.05 ha (1/8 acre)                                 65                       77         85       90       92
                             0. 10 ha (1/4 acre)                                38                       61         75       83       87
                             0. 15 ha (1/3 acre)                                30                       57         72       81       86
                             0.20 ha (1/2 acre)                                 25                       54         70       80       85
                             0.4 ha (I acre)                                    20                       51         68       79__,    8@
                          Commercial and business                            85 (@@)                     89         92       94       95
                          Industrial districts                                     72                    81         88       91       93
                          Source: Novotny and Olem, 1994 and the Soil Conservation Service, 1986.
                          ' The remaining pervious areas (lawns) are considered to be in good pasture condition for these curve numbers.
                          b Curve numbers are computed assummg the runoff from the house and driveway is directed toward the street with a
                           minimum of roof water directed to lawns where additional infiltration could occur.



































                                                                                                                                      3-12










                                               Table 3-6. Description of Soil Hydrologic Groups

                         Soil
                      -Group                                               Description
                                                                   Undisturbed Soils
                           A      Low runoff potential and high infiltration rates even when thoroughly wetted. Chiefly deep,
                                  well to excessivelv drained sands or gravels. High rate of water transmission (>0.75 cm/hr).
                           B      Moderate infiltration rates when thoroughly wetted. Chiefly moderately deep to deep,
                                  moderately well to well drained soils with moderately fine to moderately coarse textures.
                                 IModerate rate of water tz-ansmission (0.40-0.75 cnVhr).
                           C      Low infiltration rates when thoroughly wetted. Chiefly soils with a laver that impedes
                                  downward movement of water, or soils with moderately fine to fine texture. Low rate of
                                  water transmission (0. 15-0,40 cm/hr).
                           D      High runoff potential. Very low infilti-ation rates when thoroughly wetted. Chiefly clay soils
                                  with a high swelling potential, soils with a permanent high water table, soils with a claypan
                                  or clay layer at or near the surface, or shallow soils over nearly impervious material. Very
                                 Ilow rate of water transmission (0-0. 15 cnvhr).
                                                                     Disturbed Soils
                           A      Sand. loamy sand. sandy loam
                           B      Silt loam, loam
                           C      Sandy clal, loam
                           D     IClav loam siltv clay loam, sandy'clay, silty clay, clay
                        Source: Soil Conservation Service, 1986.



                        3.5.2 Universal Soil Loss Equation Factors
                        The Universal Soil Loss Equation (USLE) is the most widely accepted estimator of sod loss caused by
                        upland erosion (Novotny and Chesters, 198 1; Schwab and Frevert, 1985; Wischmeier and Smith,
                        1978). The USLE is an empirical equation that was developed through statistical analysis of more
                        than 40 years of measured soil losses from many small, experimental plot studies. The Agricultural
                        Research Service of the USDA established soil erosion experiment stations at different geographic
                        locations throughout the country that represented a wide range of sod and climatic conditions. The
                        USLE was developed by Wait Wischmeier and Dwight Smith from the dam collected at these
                        experiment stations and other available information from a network of state and federal research units
                        (Browning, 1979; Sandels, 1986). The USLE was originally developed to provide a reliable means of
                        selecting adequate erosion control practices for farm fields and construction areas. More recently, the
                        USLE has been used to predict sediment losses for pollution control programs or as an erosion
                        estimator in land use models.


                        Variables influencing upland erosion are: climate, soil properties, vegetation, topography, and human
                        activities (Novotny and Chesters, 198 1). The USLE accounts for these erosion variables by estimating
                        average annual soil loss by the following six major fiactors:
                                          A = RKLSCP

                        where.
                               A = average annual soil loss mi tons per acre (t/a),










                                R =    raimUl and ninoff factor, which is the number of rainfall erosion index units plus a
                                       factor for runoff from snowmelt or applied water where such runoff is significant,
                                K =    soil-erodibility fiLctor *in t1a, which is the average soil loss per unit of erosion index for a
                                       soil in cultivated continuous fallow with a slope length of 72.6 ft and slope of 9 percent,
                                L =    slope-length factor, which is the ratio of soil loss from the field slope length to that from
                                       a 72.6 ft length under identical conditions,
                                S =    slope-steepness flictor, which is the ratio of soil loss from the field slope gradient to that
                                       from a 9 percent slope under otherwise identical conditions,
                                C =    cover and management flictor, which is the ratio of soil loss for given conditions to that
                                       from cultivated continuous fallow, and
                                P =    conservation practice factor, which is the ratio of soil loss for a given practice to that for
                                       straight row firming up and down the slope.


                        Ile Watershed Model uses a modification of the USLE to calculate erosion from rural sources. Since
                        the USLE is an empirical equation which was derived from data for agricultural and rural land uses,
                        applying it to urban land areas is not appropriate. For each rural land use, an "erosion product" must
                        be specified. This is the product of KLSCP. The Watershed Model uses this erosion product to
                        calculate the erosion from each source area k on day t in Mg as
                                          Xkt = 0. 132 RE, Xk (LS)k Ck PkI ARk
                        where, ARk is the area of source area k and RF, is the rainffl erosivity on day t. Unlike all it's other
                        inputs, the Watershed Model expects that the value of K will be in English units. 'Me model converts
                        the erosion product to metric units with the flictor 0. 132.

                        The Watershed Model estimates rainfall erosivity by the empirical equation developed by Richardson et
                        al. (1983) as
                                          REt = 64.6 at &1-81
                        where, at is the rainfall erosivity coefficient and R, is the rainfall on day t. Ile rainfall erosivity
                        coefficient is *input on the Evapotranspiration Conditions notebook page and the model uses the values
                        in the weather file for rainfall values.


                        Estimating the USLE Factors

                        A brief description of each of the factors and a means to estimate them is provided. This is only an
                        abbreviated overview of usm*g the USLE. A comprehensive discussion of the equation's derivation,
                        fiLctors and their estimation, applications, and limitations can be obtained in Wischmeier and Smith
                        (1978).

                        Soil Erodibility Factor (K-): This is a measure of the potential erodibility of the soil. It is based on
                        soil properties. Values for K have been experimentally determined. Table 3 )-7 contains values of K
                        based on soil texturt and organic matter content. Representative values of K for most soils types and
                        texture classes can be obtained from SCS offices. Site-specific values of K can also be calculated
                        using soil erodibility nomograph techniques.


                                            Table 3-7. Values of Soil Erodibility Factor (K) in t/a











                                                                                         Organic Matter Content %)
                          Texture                                             < 0.5                      2                        4
                          Sand                                                0.05                     0.03                      0.02
                          Fine sand                                           0.16                     0.14                      0.10
                          Very fine sand                                      0.42                     0.36                      0.28
                          Loamy sand                                          0.12                     0.10                      0.08
                          Loamy fine sand                                     0.24                     0.20                      0.16
                          Loamy very fine sand                                0.44                     0.38                      0.30
                          Sandy loam                                          0.27                     0.24                      0.19
                          Fine sandy loam                                     0.35                     0.30                      0.24
                          Very fine sandy loam                                0.47                     0.41                      0.33)
                          Loam                                                0.38                     0.34                      0.29
                          Silt loam                                           0.48                     0.42                      0.33
                          Silt                                                0.60                     0.52                      0.42
                          Sandy clay loam                                     0.27                     0.25                      0.21
                          Clay loam                                           0.28                     0.25                      0.21
                          Silty clay loam                                     0.37                     0.32                      0.26
                          Sandy clay                                          0.14                     0.13                      0.12
                          Silty clay                                          0.25                     0.23)                     0.19
                          Clay                                                                      0.13-0.29
                          Sou=: Stewart et al., 1975.



                          Topographic Factor (LS): The effects of slope-length and slope-steepness have been research
                          separately and represent individual factors in the USLE, but they are commonly combined into a single
                          topographic factor for application purposes. Table 3-8 provides LS values for some common slope
                          lengths and percent slopes. Other combinations of length and gradient can be determined by
                          interpolating between the values in Table 3-8. The values in Table 3-8 were calculated by
                                              LS = (V72.6)- (65.41 sin29 + 4.56 sinO + 0.065)
                          where, I is the slope length in feet, 0 is the angle of slope, and in is the slope-length exponent based on
                          percent slope. For slopes of 5 percent or greater, m equals 0.5. For slopes of 3.5 to 4.5 percent, m
                          equals 0.4. On slopes of I to 3 percent, in equals 0.3, and on uniform gradients of less than I percent,
                          rn equals 0.2

                          Cover and Management Factor (C): Also called the cropping management factor and the vegetative
                          cover factor, C "estimates the effect of ground cover conditions, soil conditions, and general
                          management practices on erosion rate" (Novotny and Chesters, 198 1). 'Me C Factor reflects the
                          amount of protection against raindrop impact and the subsequent soil particle displacement. C is a
                          dimensionless factor with values ranging between 0 and 1. A cover and management factor of I
                          represents continuous fallow tilled up and down the slope. This condition would potentially yield the
                          greatest amount of erosion. As the value of C approaches zero, the vegetative cover or management
                          efforts have reduced the potential for erosion. Table 3 )-9 provides some common values for C for
                          agricultural land uses. The cover and management factor can also be applied to construction sites.
                          Table 3-10 contains C Factor values and slope-length limits for construction sites. Factor C is usually
                          provided in terms of an average annual value for a particular combination of crop systems and
                          management (Wischmeier and Smith, 1978).










                                                            Table 3-8. Values for the Topographic Factor (LS)
                              Percent                                                     Sl ve Leneth (feet)
                               Slope         25        50         75       100        150       200       300       400    1  500       600        800       1000
                                  0.2        .060      .069       .075     .080       .086      .092      .099      .105      .110      .114       .121      .126
                                  o.5        .073      .083       .090     .096       .104      .110      .119      .126      .132      .137       .145      .152
                                  0.8        .086      .098       .107     .113       .123      .130      .141      .149      .156      .162       .171      .179
                                  2          .133      .163       .185     .201       .227      .248      .280      .305      .326      .344       .376      .402
                                  3          .190      .233       .264     .287       .325      .354      .400      .437      .466      .492       .536      .573
                                  4          .230      .303       .357     .400       .471      .528      .621      .697      .762      .820       .920      1.01
                                  5          .268      .379       .464     .536       .656      .758      .928      1.07      1.20      1.31       1.52      1.69
                                  6          .336      .476       .583     .673       .824      .952      1.17      1.35      1.50      1.65       1.90      2.13
                                  8          .496      .701       .959     .992       1.21      1.41      1.72      1.98      2.22      2.43       2.81      3.14
                                  10         .685      .968       1.19     1.37       1.68      1.94      2.37      2.74      3.06      3.36       3.87      4.33
                                  12         .903      1.28       1.56     1.80       2.21      2.55      3.13      3.61      4.04      4.42       5.1-1     5.71
                                  14         1.15      1.62       1.99     2.30       2.81      3.25      3.98      4.59      5.13      5.62       6.49      7.26
                                  16         1.42      2.01       2.46     2.84       3.48      4.01      4.92      5.68      6.35      6.95       8.03      8.98
                                  18         1.72      2.43       2.97     3.43       4.21      3.86      5.95      6.87      7.68      9.41       9.71      10.9
                                  20     1   2.04   1  2.88   1   3.53  1  4.08   1   5.00   1  5.77 1    7.07 1    8.16 1    9.12 1    10.0       111.5  1  12.9
                              Source: Wischmeier and Smith, 1979.



                                                  Table 3-9. Values of C for Cropland, Pasture, and Woodland

                                                                         Land Use                                                                  C
                              Continuous fallow tilled up and down slope                                                                           1.0
                              Shortly after seeding or harvesting                                                                             0.3-0.8
                              For crops during main part of growing season
                                     Corn                                                                                                     0.1 -0.3
                                     Wheat                                                                                                   0.05-0.15
                                     Cotton                                                                                                        0.4
                                     Soybeans                                                                                                 0.2-0.3
                                     Meadow                                                                                                  0.01-0.02
                              For permanent pasture, idle land, unmanaged woodland
                                     Ground cover 95 - 100% as grass                                                                               0.003
                                     Ground cover 95 - 100% as weeds                                                                               0.01
                                     Ground cover 80% as grass                                                                                     0.01
                                     Ground cover 80% as weeds                                                                                     0.04
                                     Ground cover 60% as grziss                                                                                    0.04
                                     Ground cover 60% as weeds                                                                                     0.09
                              For managed woodland
                                     Tree canopy of 75 -100%                                                                                       0.001
                                     Tree canopy of 40 - 75%                                                                               0.002 - 0.004
                                     Tree canopy of 20 - 40%                                                                                 0.003-0.01
                              Source: Novotnv and Chesters, 1981








                                                                                                                                                                  6










                            Table 3-10. C Factor Values and Slope-Length (LS) Limits for Construction Sites

                                                                    Application
                       Mulch Type                                   (tonnes/ha)      Slope (%)             C                LS
                       No mulch or seeding                                                All              1.0
                       Straw or hay tied down by anchoring                2.25            <5               0.2              60
                       and UwJdng equipment used on slope                 2.25            6-10             0.2              30
                                                                          3.4             <5               0.12             90
                                                                          3.4             6-10             0.12             45
                                                                          4.5             <5               0.06             100
                                                                          4.5             6-10             0.06             60
                                                                          4.5             11-15            0.07             45
                                                                          4.5             16-20            0.11             30
                                                                          4.5             21-25            0.14             23
                       Crushed stone                                      300             <15              0.05             60
                                                                          300             16-20            0.05             45
                                                                          300             21-33            0.05             30
                                                                          540             <20              0.02             90
                                                                          540             21-35            0.02             60
                       Wood chips                                         15              <15              0.08             23
                                                                          15              16-20            0.08             15
                                                                          27              <15              0.05             45
                                                                          27              16-20            0.05             23
                                                                          56              <15              0.02             60
                                                                          56              16-20            0.02             45
                                                                          56              21-331           0. 2             30
                       Asphalt emulsion 12 m'/ha                                                           0.03
                                                                                       C - During first 6       C - After the 6th
                                                                                       weeks of gro              week of growth
                       Temporary seeding with grain or fitst-
                       growing grass with:
                            No mulch                                                          0.70                     0.10
                            Straw                                         2.25                0.20                     0.07
                                                                          3.4                 0.12                     0.05
                            Stone                                         300                 0.05                     0.05
                                                                          540                 0.02                     0.02
                            Wood chips                                    15                  0.08                     0.05
                                                                          27                  0.05                     0.02
                                                                          ;.6                 0.02                     0.02
                       Sod                                                                    0.01                     0.01
                       Source: Novotny and Olern, 1994.










                         C onservation Practice Factor (P): The conservation practice factor accounts for management
                         activities which slows runoff water and thus reduces sediment transport capacity, thereby retaining
                         detached soil particles near their sources. This includes contouring, compacting, strip cropping, and
                         establishing sediment basins. P is a dimensionless factor with values ranging between 0 and 1. The P
                         Factor has a value 'of I when no management activities are applied. Table 3-11 and Table 3-12
                         provide values for the conservation practice factor.


                                                  Table 3-11. Values of P for Agricultural Lands

                                                                                        Strip Croppina and Terr          9
                         Slope (percent)                   Contouring           Alternate Meadows               Closegrown
                         0-2.0                                 0.6                        0.3                        0.45
                         2.1-7.0                               0.5                        0.25                       0.40
                         7.1-12.0                              0.6                        0.30                       0.45
                         12.1-18.0                             0.8                        0.40                       0.60
                         18.1-24.0                             0.9                        0.45                       0.70
                         > 24                                  1.0-                       1.0                        1.0           j
                         Source: Novotny and Olem, 1994.


                                                  Table 3-12. Values of F for Construction Sites

                         Erosion Control Practice                                                                      P
                         Surface Condition with No Cover
                            Compact, smooth, scraped with buffdozer or scraper up and down hiR                       1.30
                            Same as above, except raked with bulldozer or scraper up and down hifl                   1.20
                            Compact, smooth, scraped with bulldozer or scraper across slope                          1.20
                            Same as above, except raked with bulldozer or scraper across slope                       0.90
                            Loose as a disked plow layer                                                             1.00
                            Rough irregular surface, equipment tracks in all directions                              0.90
                            Loose with rough surface > 0.3 in depth                                                  0.80
                            Loose with smooth surface < 0.3 in depth                                                 0.90
                         Structures
                            Small sediment basins - 0.09 ha basintha                                                 0.50
                            Small sediment basins - 0. 13 ha basin/ha                                                0.130
                            Downstream sediment basin with chemical flocculants                                      0.10
                            Downstrearn sediment basin without chemical flocculants                                  0.20
                            Erosion control structures - normal rate usage                                           0.50
                            Erosion control structures - high rate usage                                             0.40
                            Strip building                                                                           0.75
                         Source: Novotny and Olem, 1994.



                         Estimation of KLSCP for the Hydrologic Unit Database: The following is a rough estimate of
                         USLE factor values to use for the land uses in the HUD. These values are for the tidewater area of
                         Virginia and are based on the following assumptions:
                              ï¿½   Fairly permeable sandy to sandy loamy soils
                              ï¿½    Fairly level terraMi with a percent slope of 5 percent










                            ï¿½ A slope length of 500 feet
                            ï¿½ No support practices are being applied
                       When evaluating a potential source of poflution, the worst case scenario is often used to ensure that any
                       water quality impacts would be detected. This rationale was applied during the selection of the slope-
                       length factor and the conservation practice flictor. As slope length increases, the potential for soil
                       detachment and transport also increases, therefore a slope length of 500 feet was selected as a
                       conservative value. By using a large value for the slope length, a greater potential for erosion exists.
                       Although Table 3-8 contains data extrapolated to 1000 feet, these values have not been validated with
                       field measurements, and could increase the uncertainty of model calculations. A conservation practice
                       flictor of I was selected, since this implies that nothing is being done to minimize erosion on any of the
                       land uses.


                       Selection of the soil erodibility flictor is somewhat arbitrary. This factor should be estimated based on
                       the average of known sod types for each land use. A constant value was selected for all land,uses and
                       is based on general property values of the Coastal Plain area.

                       A percent slope value of 5 percent was selected as an average value for the tidewater area. As slopes
                       steepen, soil loss increases much more rapidly than runoff and a large slope value could have
                       tremendous impact on model results. There are certainly slopes 'in the tidewater area that are steeper
                       than 5 percent, but to use the maximum value for this ffictor would present a very unlikely scenario for
                       a watershed.


                       Values selected for the cover and management factor are average values for each land use and have
                       been selected from the literature values.


                       The estimates contained in Table 3-13 are an educated best guess, and could be inaccurate if the area
                       being modeled does not match the assumptions. It is always best to use the most site-specific
                       information whenever possible.


                              Table 3-13. Estimated Values for Land Uses in the Hydrologic Unit Database

                       Land Use                               K              LS              C              P           KLSCP
                       Cropland                              0.24            1.20           0.35            1.0         0.1008
                       Forest                                0.24            1.20           0.005           1.0         0.0014
                       Hay                                   0.24            1.20           0.02            1.0         0.0058
                       Idle Farmland                         0.24            1.20           0.1             1.0         0.0288
                       Orchards/Christmas Trees              0.24            1.20           0.1             1.0         0.0288
                       Pasture                               0.24            1.20           0.08            1.0         0.0230



                       Limitations


                       The USLE estimates gross erosion from sheet and rill erosional processes. It does riot consider gully or
                       channel erosion, which can be a significant source of erosion in some watersheds. Also. the USLE does
                       not address soil loss by wind erosion.





                                                                                                                              3-19










                       "Me USLE is designed to predict longtimc-average sail losses for specified conditions" (Wischmeier
                       and Smith, 1978). It is not recommended for trying to predict soil losses from a specific storm event.

                       The USLE estirriates only erosion potential. It does not estimate transport or deposition, and therefore
                       it does not provide a direct estimate of sediment yield. To estimate the sediment yield, the USLE must
                       be multiplied by a delivery ratio for the watershed.

                       "Soil losses computed with the USLE are best available estimates, not absolutes. They will generally
                       be most accurate for medium-textured soils, slope lengths of less than 400 feet, gradients of 3 to IS
                       percent, and consistent cropping and management systems that have been represented in the erosion
                       plot studies. The farther these limits are exceeded, the greater will be the probability of significant
                       extrapolation error" (Wischmeier and Smith, 1978).

                       3.6 Nutrient Input
                       The Nutrient Info notebook page contains two spreadsheets: one for rural land uses and one f6r urban
                       land uses. The land use category names entered into the land uses spreadsheets on the Land Uses
                       notebook page will be automatically transferred to the nutrient spreadsheets. For the rural land uses,
                       the dissolved nitrogen and phosphorus concentrations in mg/L must be entered. Table 3-14 contains
                       flow weighted nutrient concentrations measured by Dornbush et al. (1974) for several agricultural land
                       uses. For urban land uses, the nutrient build-up in kg/ha-day must be entered. Table 3-15 provides
                       nutrient accumulation rates for urban areas around northern Virginia as measured by Kuo et al. (1988).

                       'Me Watershed Model requires groundwater concentration values for nitrogen and phosphorus in mg/L.
                       These values should be computed from area weighted averages for land use type. According to Reay
                       (1994), typical ground water nitrogen concentrations as N03-N are < I ing/L for forest, 2 mg/L for
                       pasture and residential areas, and 10 mg/L for agriculture. Typical phosphorus concentrations are
                       0. 15 mg/L for all mentioned land uses.

                       Soil nutrient levels must be entered in mg/kg for both nitrogen and phosphorus. These values should be
                       computed from area weighted averages for land use type.

                       Ile values for the groundwater and soil nutrient parameters may be entered by selecting the
                       appropriate text box with the mouse or using the <Tab> key until the desired text box gains the focus.
                       As each text box gains the focus, it's label will turn blue for easy identification.

                       Selecting the [Example Data] button will provide nutrient concentration and loading data for the
                       example watershed. To provide reasonable output data, this data should be used in conjunction with
                       the example data provided for the other input parameters and the example weather file.

                       'Me [Cancel] button will clear all values from the nutrient information text boxes and spreadsheets. If
                       this button is selected, a message box will appear asking for verification prior to deleting current
                       values.










                                            Table 3-14. Dissolved Nutrients in Agricultural Runoff

                        Land Use                                      Nitrogen (mg/L)                      Phosphorus (mg/L)
                        Fallow                                                2.6                                   0.10
                        Corn                                                  2.9                                   0.26
                        Small grains                                          1.8                                   0.30
                        Bay                                                   2.8                                   0.15
                        Pasture                                               3.0                                   0.25
                        Source: Donibush et al., 1974.


                              Table 3-15. Nutrient Accumulation Rates for Northern Virginia Urban Areas

                        Land Use                                   Total Nitrogen ftlha-day) Total Phosphorus ft/ha-day)
                        Impervious Surfaces
                          Single family residential
                             Low density (uniwha < 1.2)                         0.045                               0.0045
                             Medium density (units/ha 2:1.2)                    0.090                               0.0112
                          Townhouses and apartments                             0.090                               0.0112
                          High rise residential                                 0.056                               0.0067
                          Institutional                                         0.056                               0.0067
                          Industrial                                            0.101                               0.0112
                          Suburban shopping center                              0.056                               0.0067
                          Central business district                             0.101                               0.0112
                        Pervious Surfaces
                          Single flunily residential
                             Low density (units/ha < 1.2)                       0.012                               0.0016
                             Medium density (units/ha @: 1.2)                   0.022                               0.0039
                          Townhouses and apartments                             0.045                               0.0078
                          High rise residential                                 0.012                               0.0019
                          Institutional                                         0.012                               0.0019
                          Industrial                                            0.012                               0.0019
                          Suburban shopping center                              0.012                               0.0019
                          Central business district                             0.012                               0.0019
                        Source: Kuo et al., 1988.


                        3.7 Point Sources
                        The Watershed Model can account for nitrogen and phosphorus loadings from continuous point source
                        discharges. If there are known continuous point source discharges into the watershed, they should be
                        modeled to provide the most accurate picture of watershed nutrient loadings.

                        To enter nutrient loads into the Point Sources spreadsheet, click on the spreadsheet or use the <Tab>
                        key until the spreadsheet gains the focus. The monthly loadings should be entered in kilograms.

                        Selecting the [Example Data] button will provide point source data for the example watershed. To
                        provide reasonable output dam this data should be used in conjunction with the example data provided
                        for the other input parameters and the example weather file.










                        The [Cancel] button will clear all values from the point sources spreadsheet. If this button is selected,
                        a message box Will appear asking for verification prior to deleting current values.
                        3.8 Evapotranspiration Conditions
                        The parameters on the Evapotranspiration Conditions notebook page are used to determine the water
                        balance in the Watershed Model. Default values for all of the monthly ET parameters have been
                        provided. They are based on Virginia's geographic location and typical grow mig season.

                        Evapotranspiration Cover Coefficient (CV,): The amount of daily evapotranspiration is determined
                        by multiplying the potential ET by the cover coefficient. This parameter can be difficult to es@rimate,
                        but Haith et al. (1992) has developed a simplified procedure:
                             1 . Cover Coefficients should vary between 0 and 1, in principle.
                             2.  Cover coefficients will approach their maximum value when plants have developed fiffl foliage.
                             3.  Because evapotranspiration measures both transpiration and evaporation of soil water, the
                                 lower limit for cover coefficients will be greater than zero. This lower limit essentially
                                 represents a situation without any plant cover.
                             4.  The protection of soil by impervious surfaces prevents evapotranspiration.
                        Cover coefficients for forests reach minimum values of 0.2 to 0.3 as leaf area indices approach zero.
                        Similarly, cover coefficients for farmland with annual crops can fall to 0.3 prior to planting and after
                        harvesting. Cover coefficients for perennial crops and conifers tend towards 1. 0. "11iis suggests that
                        monthly cover coefficients can be given the value 0.3 when fbliage is absent and 1.0 otherwise" (Haith
                        et al., 1992). For urban area , a constant value of 1.0 can be assigned to pervious surfaces and 0.0 to
                        impervious surfaces. The monthly values for the cover coefficient should reflect the area weighted
                        average for the various land use types in the watershed. Assuming that the amount of impervious
                        surfaces is small in relation to the watershed extent, default values have been selected based on
                        seasonal foliage development in Virginia. The values can be displayed by selecting the [Default]
                        button. If the watershed being modeled contains substantial urban development or unusual conditions,
                        the default cover coefficients might not be applicable.

                        Daylight Hours: This value represents the mean daylight hours for each month. This parameter is
                        fairly constant for most of Virginia. The mean daylight hours for 38' latitude are used as default
                        values (USEPA, 1984). Selecting the [Default] button will display these values in the
                        Evapotranspiration spreadsheet.

                        Growing Season: The monthly value is classified as either dormant or growing and is represented by
                        either a 0 or a 1, respectively. The growing season parameter determines the breakpoints between
                        antecedent moisture conditions. For months in the dormant season, AM 1 = 1. 3 cm and AM2 = 2. 8 cm.
                        For months in the growing seasons, AM I = 3.6 cm and AM2 = 5.3 cm. The growing season for
                        Virginia is considered to be April to October. Selecting the (Default] button will display the growing
                        season values 'in the Evapotranspiration spreadsheet.

                        Rainfall Erosivity Coefficient (a,): The rainfall erosivity coefficient is used to deterrruine rainfall
                        erosivity and contributes to the calculation of erosion by the USLE. 'ne coefficient varies with season
                        and aeoaraphic location. but can be estimated by using the methods developed by Seiker et al. ( 1990).
                        According to the rainfall erosivity zones defined by Wischmeler and Smith (1978), all of tidewater
                        Virginia is located in Zone 30. For this zone. Selker et al. has defined the cool season (October to



                                                                                                                               3 -2 2









                       March) value to be 0. 12 and the warm season (April to September) value to be 0.30. Selecting the
                       [Default] button Will display these values in the Evapotranspiration spreadsheet.

                       Selecting the (Example Data] button will provide evapotranspiration data for the example watershed.
                       To provide reasonable output data, this data should be used in conjunction with the example data
                       provided for the other input parameters and the example weather file.

                       The [Cancel] button will clear all values from the evapotranspiration spreadsheet- If this button is
                       selected, a message box will appear asking for verification prior to deleting current values.

                       3.9 Septic Systems
                       The per capita nutrient load must be specified for both nitrogen and phosphorus. The USEPA (1980)
                       reports loadings of 10.4 g/day of total nitrogen and 3.5 g/day of phosphorus. Loading values can also
                       be determined from representative septic tank wastewater flow and effluent concentrations. The
                       USEPA (1980) indicates that a typical on-site wastewater disposal system will discharge 170 L/day
                       per person. Mean nitrogen concentrations in septic tank effluent were measured as 73 mg1L, while
                       mean phosphorus concentrations were 14 mg/L when phosphate detergents were being used and only
                       7.9 mg/L when non-phosphate detergents were used (Alhajar et al., 1989). These values yield a per
                       capita septic tank effluent of 12.0 gtday for nitrogen, 2.5 g/day for phosphorus if phosphate detergent
                       is used, and 1.5 g/day if non-phosphate detergent is used.

                       The per capita growing season nutrient uptake in g/day must also be specified. This refers to the
                       uptake of nutrients from septic tank effluent by the ground cover (usually grasses) over the septic field.
                       There has not been much research in this area. Haith et al. (1992) provided estimates of 1.6 g/day for
                       nitrogen and 0.4 g/day for phosphorus, but these are speculative values. The most conservative
                       approach is to assume that plant uptake is minimal and enter a value of zero. If predicted nutrient
                       loadings from septic systems are within acceptable limits when nutrient uptake by plants is not
                       considered, then the septic systems are probably not contributing nonpoint nutrient loadings.

                       The values for these parameters may be entered by selecting the appropriate text box with the mouse or
                       using the <Tab> key until the desired text box gains the focus. As each text box gains the focus, it's
                       label will turn blue for easy identification.

                       The number of individuals served per month by the four different conditions of septic systems should
                       be entered into the Septic Systems spreadsheet. These four conditions are described in Section 3. 1.
                       'Me number of individuals served by each system can be obtained by perfbrming surveys or by
                       contacting local public health officials. To input data, click on the desired spreadsheet cell or use the
                       <Tab> key until the spreadsheet gains the focus, and then use the arrow keys to move around in the
                       spreadsheet.

                       Selecting the [Example Data] button will provide septic system data for the example watershed. To
                       provide reasonable output data, this data should be used 'in conjunction with the example data provided
                       for the other input parameters and the example weather file.

                       The [Cancel] button will clear all values from the septic system text boxes and spreadsheet. If this
                       button is selected, a message box will appear asking for verification prior to deleting current values,









                        3.10 Model Resuft
                        Simulation results from the Watershed Model can be examined as either tabular or graphical output.
                        To view the tabular results, click on the Tabular Output notebook tab or press <Alt T>. A compete
                        description of this notebook page is provided in subsection 3.10.1. To view the results in a graphical
                        format, click on the Graphical Output notebook tab or press <Alt G>. A complete description of this
                        notebook page is provided in subsection 3.10.2. Selecting the Graphical Output notebook page will
                        run the Watershed Model. If simulation results have not been previously calculated or if any of the
                        input parameters have been altered since the simulation results were generated, the Watershed Model
                        will begin a new'simulation. The time required to complete the simulation will depend on the number
                        of years being modeled and the processing power of your computer. The mouse pointer will change to
                        an hourglass while the simulation is being processed.

                        3.10.1 Tabular Output
                        The simulation results can be viewed in the following five ways:
                             I . Summary by Month
                             2.  Summary by Source Oand use category)
                             3.  Annual Results
                             4.  Annual Results by Source (land use category)
                             5.  Monthly Results
                        Selecting Summary by Month win provide the average monthly values for precipitation, ET,
                        groundwater flow, stream flow, runoff@ erosion, sediment yield, dissolved and total nitrogen, and
                        dissolved and total phosphorus. These are the average values for the entire simulation period. The
                        average annual value for each parameter is also provided in this summary.

                        Selecting Summary by Source will provide average parameter values for each land use category.
                        Results include runoff, erosion per hectare, dissolved and total nitrogen, and dissolved and total
                        phosphorus. The area of each land use is also provided. In addition to the designated land uses,
                        dissolved nutrient loadings are also provide for the groundwater discharge, as well as point sources and
                        septic systems if either has been modeled.

                        Annual Results provides the average annual values for precipitation, ET, groundwater flow, stream
                        flow, runoff, erosion, sediment yield, dissolved and total nitrogen, and dissolved and total phosphorus
                        for each year in the simulation period.

                        Annual Results by Source provides the same information as Summary by Source, but instead of values
                        averaged over the entire simulation period, the values are presented for each year of the simulation.
                        For large simulation periods, output for the entire simulation may not be desired. To give the user the
                        flexibility to view only selected output years, an input dialog box appears when this display option is
                        selected. Enter the desired beginning and ending years of the output you wish to view and then [Close]
                        the input box.

                        Selecting Monthly Results provides the same information as Summary by Month, but instead of
                        monthly values averaged over the entire simulation period, the monthly values are presented for each
                        year of the simulation. For large simulation periods, output for the entire simulation may not be
                        desired. To ive the user the flexibility to view only selected output Years. an input dialog box appears
                                     91










                     when this display option is selected. Enter the desired beginning and ending years of the output you
                     wish to view and then [Close] the input box.

                     The default option is Summary by Month. To select a different option, use the mouse or press the
                     <Tab> key. After the desired display option has been selected, click on (Show Output]. If simulation
                     results have not been previously calculated or if any of the input parameters have been altered since the
                     simulation results were generated, the Watershed Model will begin a new simulation. Ile time
                     required to complete the simulation will depend on the number of years being modeled and the
                     processing power of your computer. The mouse pointer will change to an hourglass while the
                     simulation is being processed. 'Me results will be displayed in a noninteractive spreadsheet,

                     Any of the simulation results spreadsheets can be printed by selecting File/Print from the menu bar. A
                     Print dialog box will appear with check boxes fbr all the output options. Select as many output options
                     as desired by using the mouse or by pressing <Alt> and the underscored letter in the option name.
                     Once all desired options have been selected, choose the [OK@ command button. This will send the
                     selected files to the designated windows printer. Tle output spreadsheets will print in color if a color
                     printer is designated. Select the [Cancel] button when the print option is no longer desired.

                     3.10.2 Graphical Output
                     Tliere are four types of graphs:
                          1. Annual Mean by Source (land use category)
                          2. Monthly Mean
                          3. Annual
                          4. Monthly
                     When you select the desired graph option, a parameter option box will appear with the applicable
                     parameter types. When a parameter type is selected, the corresponding graph will be displayed. This
                     graph can be sent to the printer by clicking on the [Print Graph] button. Annual Mean by Source and
                     Monthly Mean graphs are bar graphs. Annual and Monthly graphs are line graphs. When the Monthly
                     graph option is selected, an input dialog box will appear requesting the yearly range over which to
                     graph the data. Since data for all months is displayed for each specified year, the Monthly graph
                     option is more applicable for viewing simulations with short time periods or smaller portions of
                     simulations with large time periods.







                        4. Marina Water Quality Model
                        'Me Mmina, Water Quality (MWQ) Model is an analytical model for steady-state, two-dimensional
                        contaminant transport from a continuous shoreline source. The model is based on the work of Hamrick
                        and Neilson (1989). A marina was designated as the continuous shoreline contaminant source. The
                        model is applicable to marinas located along theL shoreline of a wide channel. Hamrick and Neilson
                        define a wide channel as being typically wider than I 00m and having "measurable net fi=h water
                        discharge in addition to tidal driven flow". The MWQ Model considers advection, dispersion, and first
                        order decay.

                        Two analytical solutions are included in the MWQ Model: an infinite channel solution and a finite
                        channel solution. T"hese solutions are designated, respectively, by selecting either the neglect channel
                        end effects or the consider channel end effects option on the Options notebook page. Both solutions
                        assume constant water depth, decay coefficient, longitudinal and trarisverse dispersion coefficients, and
                        longitudinal velocity. The solutions are based on depth and tidal cycle average conditions. Dierefore,
                        the contaminant concentration is constant with depth. In addition, the MWQ Model assumes that the
                        tidal range is significantly less than the water depth. TIle contaminant is assumed to be uniformly
                        mixed over the water depth at time T,
                                         T_ = 120   h
                                                   qM
                        where, h is the mean water depth and q. is the maximum tidal velocity magnitude (Hamrick and
                        Neilson, 1989). If Tz is less than or equal to the inverse of the decay coefficient and to the semi-
                        diurnal tidal period, than the vertical uniformity condition is satisfied.

                        The infinite channel solution is based on the assumption that any contaminant will decay before it
                        reaches the boundaries. Advective transport is limited to the longitudinal direction. This solution is
                          C =        M  -   exp[      U__7               K.[
                               -7hVY                _K, D
                                       ,D,       14                  -0

                        where,  C    =   depth and tidal cycle averaged contaminant concentration
                                M    =   mass of the contaminant
                                D,,  =   longitudinal dispersion
                                Dy   =   transverse dispersion
                                u    =   tidally averaged mean discharge velocity
                                K,i  =   the decay coefficient
                                x    =   the current value along the channel
                                y    =   the current value across the channel
                                Y,   =   the modified Bessel function of the second kind of order zero
                                B    =   channel width


                        The finite channel solution is for a stream with a no flow (closed) upstream boundary and a
                        downstream boundary, open to another water body. The downstream boundary is infinitely diluted.
                        Because of the no flow upstream boundary, longitudinal advective transport is assumed to be
                        negligible. This solution is






                        C=- M             .0 00   (- ly K.                      +@&()@,B)2 +IYK.                X+2j4)2+@&(Y+2iB)2
                                 -        Z Z                   (x+21, +jr,)'
                             *JD@y (i-j-                  @ @D.                   Dy                    FD.                 DY

                        where, L, is the upstream boundary location and Ld is the downstream boundary location.

                        The major weakness of the MWQ Model is the use of idealized stream geometry, topography, and flow
                        fields. This allows for the use of analytical solutions, but site-specific data cannot be used, even if it is
                        known.


                        4.1 Model Format
                        The Mum Water Quality Model utilizes a notebook format to enter data and display model results.
                        'Me first three notebook pages provide screens fbr input data and the last two notebook pages are used
                        to present tabular and graphical model results. Each page of the notebook can be accessed by clicking
                        on the corresponding tab or pressing <Alt> plus the underlined letter of the tab header. Discussions
                        regarding model input and parameter estimation are provided in Sections 4.2 and 4.3. Both of these
                        sections corresponds to an individual notebook page in the MWQ Model. Simulation results and model
                        output are discussed in Section 4.4.

                        The fir-st notebook page, Project Info, serves as the MWQ Model's introductory screen. This notebook
                        page can be used for record keeping purposes. There are text boxes available to enter in the project
                        title, date, and the names of the individuals involved with the model run. This notebook page may be
                        omitted if desired.


                        On the Parameters notebook page, there is an example data set. This data set can be used as a tutorial
                        for the MWQ Model. To access this data click on the [Test Data Set] button. This data can be used to
                        become fluniliar with  "how to navigate through the model and it provides an example of typical input
                        and model results. There is data available to rneet all model options.

                        The menu bar on the MWQ Model provides the user with file access, editing capability, and help
                        information. Selecting File will display a drop-down menu list with the following items: New, Open,
                        Save, Save As, Print, and Exit. New deletes the current data set. A message box will ask for
                        verification prior to deleting current values. Open calls up the Open File dialog box to select an
                        existing data set. Save Will save the current data set using the existing file name. If a file name has not
                        been defined, the Save As File dialog box will appear prompting the user to enter a file name. Save As
                        opens the Save As File dialog box to allow the current data set to be saved with a new file name.
                        Selecting Print will send the current model data and results to the default Windows printer. Exit closes
                        the MWQ Model and returns the user to the main CS Model window. If the current data set has not
                        been saved, it will be lost. Selecting Edit will display a drop-down menu fist with Cut, Copy, and
                        Paste. These menu items can be used to edit input data. Cut will remove the selected text and move it
                        to the windows clipboard. Copy will place a duplicate of the selected text on the clipboard, but not
                        remove the oniginal text. Paste can be used to put text placed on the clipboard back onto one of the
                        input screens. Help will provide information pertaining to the MiWQ Model.







                                                                                                                                        4-2










                          4.2 Parameters
                          'Me hydraulic and contaminant parameters and the region to be modeled must de defined- Ile values
                          for these parameters can be entered directly into each text box by clicking on it and then entering the
                          desired value from the keyboard. Ile text boxes may also be accessed using the <Tab> key. As each
                          text box becomes active, its corresponding label will turn blue. Clicking on the label fbr the various
                          input parameters will display a pop-up message box with help information.

                          The (Cancel] button wiH clear aU values from the parameter text boxes. If this button is selected, a
                          message box wifl appear asking for verification prior to deleting current values.

                          4.2.1 Hydraulic Parameters
                          Mean Water Depth: T"his is the water depth averaged over the area to be modeled. The depth is
                          assumed to be constant.

                          Maxiinum Tidal Velocity: The magnitude of maximum tidal velocity. Units are meters per second.
                          Mean Discharge Velocity: Tidally averaged mean discharge velocity. A conservative estimate can
                          be obtained by setting this value to zero.
                          Channel Width: The width of the channel is assumed to be constant over the region being modeled.
                          This value should be entered in meters.

                          Tidal Period: 'Me tidal period is usually 12.4 hours.
                          Distance Downstream to Open End: This is the distance downstream          to the open end of the channel,
                          and it must be greater than or equal to the downstream distance to be modeled.
                          Distance Upstream to Closed End: This is the distance upstream to the closed end of the channel,
                          and it must be gre:ater than or equal to. the upstream distance to be modeled.

                          4.2.2 Contaminant Parameters
                          The MWQ Model will predict results for coliforms, CBOD, and NBOD. Subsection 2.3 ).5 contains a
                          detailed discussion of these parameters. Check boxes allow for the selection of the contaminants to
                          model. More thari one contaminant can be modeled simultaneously. Both a loading and a first order
                          decay rate must be specified for each parameter that will be modeled. Loadings for all parameters are
                          considered to be continuous and steady-state, and the contaminant is introduced into the water body at
                          a point along the shoreline. Required units for loading of CBOD and NBOD are kg/day. Coliform
                          loadings are in organisms per second. Decay rates for all parameters should be per day.

                          4.2.3 Region to be Modeled
                          Distance DownstreArn: Distance downstrearn from the contaminant source being modeled.
                          Distance Upstream: Distance upstream from the contaminant source being modeled.

                          Width Across Channel: The distance across the channel to be modeled. This distance must be less
                          than or equal to the actual channel width.
                          Display Length: This value will control the interval used to display the distance aiong the channel
                          the tabular display of the MWQ Model's results on the Tabular Output notebook page. Units are Uil










                      meters. A value can be entered directly into the text box or the spin buttons can be used to select the
                      desired interval.

                      Display Width: This value will control the interval used to display the distance across the channel in
                      the tabular display of the MWQ Model's results on the Tabular Output notebook page. Units are in
                      meters. A value can be entered directly irito the text box or the spin buttons cm be used to select the
                      desired interval.

                      4.3 Options
                      Selecting the Options notebook page will provide a preliminary assessment of the initial data. 'Me
                      longitudinal and transverse dispersion coefficients are calculated and the model assumptions are
                      evaluated. If you do not want to use the calculated dispersion coefficients, select the check box and
                      enter the desired values in the user selected text boxes. Model assumptions are evaluated based on the
                      chosen selection option to consider or neglect channel end effects. If the displayed values are much
                      greater than 1, thari the given assumption is valid. If any of the assumptions are not valid, different
                      parameter values should be entered prior to starting a simulation.

                      4.4 Model Results
                      Selecting the Tabular Output notebook page will run the MWQ Model. The mouse pointer will change
                      to an hourglass while the simulation is being processed. Results from the MWQ Model can be
                      exan-dned as either concentrations plots or 'in a tabular format. To run the model and view the tabular
                      results, click on the Tabular Output notebook tab or press <Alt T>. A compete description of this
                      notebook page is provided in Subsection 4.4. 1. To view the results in a graphical format, click on the
                      Transects notebook tab. A complete description of this notebook page is provided in Subsection 4.4.2.

                      4.4.1 Tabular Output
                      "Me MWQ Model displays the results in a spreadsheet format. Ile distance along the channel, as
                      specified on the Parameter notebook page, is displayed 'in the first column. The values are for the
                      specified interval in both the upstream and downstream direction. The first row of the spreadsheet
                      displays the distance across the channel, as specified on the Parameter notebook page. The rest of the
                      matrix contains the values for the modeled water quality variable. There is a set of options buttons to
                      the right of the spreadsheet that can be used to change which water quality parameter is being
                      displayed. All values are displayed in exponential notation.

                      4.4.2 Transects
                      For each of the water quality variables, the longitudinal concentration can viewed for the transects
                      across the channel. The distance upstream and downstream from the discharge point is set on the x-
                      axis and the parameter concentration is placed along the v-axis. To change which transect is being
                      displayed, click on one of the scroll arrows. 'Me new transect value will be displayedin. the text box.
                      The transect value will correspond to the display width value selected on the Parameter notebook page.
                      Once the desired timisect value is selected, click on the [Redraw] button to refresh the graphical
                      display.









                         5. Tidal Prism Model
                         The Tidal Prism Model was developed by Jason Luettinger as a part of his master's degree research.
                         The model description contained in this section is provided from his thesis with his permission.

                         The Tidal Prism Model is a one-dimensi6nal tidal flushing model capable of predicting the longitudinal
                         distribution of contaminant concentrations at high tide intervals. The algorithm was first proposed by
                         Ketchum in 1951 and later modified by Kuo and Neilson in 1988. The model differs from traditional
                         finite segment models in that the segmentation of a water body is based upon the geometry and
                         hydrodynamic flow characteristics of the water body rather than a manual segmentation process.
                         Instead of solving a large set of simultaneous equations as is necessary for typical finite segment
                         models, the Tidal Prism Model successively solves one mass balance equation progressively from the
                         mouth to the upstream boundary segment for each tidal cycle increment. Concentrations are initialized
                         after each tidal cycle such that the model uses the previous tidal cycle concentrations as the initial
                         conditions for the next time step. This iterative process continues until a specified time period has
                         elapsed or the system reaches a steady-state condition.

                         Ketchum's original Tidal Prism Model was proven to be fiindamentally sound in theory, but some
                         minor flaws were shown to exist in later revisions of the model. Ketchum's model based the
                         segmentation of a water body on the fact that the upstream river flow was a non-zero parameter.
                         Segmentation was proposed to begin at the upstream limit of tidal current reversal and continue
                         downstream to the mouth of the water body. Because a non-zero flow was required in Ketchum's
                         proposed model, it was not applicable to tidal embayments or dammed tidal rivers were an inflow may
                         not always exist. Ketchum demonstrated that the Tidal Prism Model could accurately predict salinity
                         distributions in three very different estuaries including the Raritan River and Bay, Alberni Inlet- and
                         Great Pond (Ketchum, 195 1).

                         Three major revisions have been proposed to Ketchum's original model. Dver and Taylor (1973) first
                         corrected a fundamental error in the model's mass balance equation and also proposed a fitting
                         parameter associated with the mixing. This unnamed parameter is referred to 'in later articles as the
                         44return flow factor" or the "returning ratio", and was identified as a relatively important parameter in
                         fitting the model (Sanford et al., 1992). Wood (1978) fiirther expanded this concept by proposing an
                         alternative to the "inter-segment exchange" in terms of an average dispersion coefficient. This
                         dispersion coefficient was included to account for the relative mixing which occurs between the
                         neighboring segments of a water body. Wood's proposed model was calibrated to Ketchum's data on
                         the Raritan Estuary for comparison of fit. It was shown that there was no single dispersion index
                         which could provide an accurate representation of the salinity profile, but that a combination of low
                         dispersion near the freshwater source and high dispersion near the seaward boundary produced a fairly
                         accurate fit.


                         Wood's model combined the basic ideas proposed by Ketchum (195 1) and Dyer and Taylor (1973),
                         but still required that the flow be a non-zero parameter for segmentation of the water body. Kuo and
                         Neilson (1988) later expanded the model such that it became applicable to cases where the water body
                         is branched and/or the freshwater discharge is negligibly small. Kuo and Neilson proposed a
                         flindamental change in the segmentation of the water body 'in order to allow for the zero flow case. In
                         this version of the model, the segmentation begins at the mouth of the water body and continues
                         upstream until a cutoff point is reached. This cutoff may be a physical barrier such as a dam or
                         embayment, or a hydraulic barrier such as the point where current reversal stops and pure advecuive










                      flow begins in a tidal river. Kuo and Neilson's final modification of the Tidal Prism Model is capable
                      of simulating point and non-point discharges and can handle both conservative and non-conservative
                      substances. The application of the model is relatively simple as it requires a minimal amount of
                      physical data including depth, surface area and tidal range.

                      Ile Tidal Prism Model has been demonstrated to be successful in predicting water quality in many
                      small coastal embayments in Virginia, including the Lynnhaven Bay system on the lower Chesapeake
                      Bay (Kuo and Neilson, 1988).

                      5.1 Modeling Approach
                      As the surface of the river rises during flood tide, this increase in water volume must be accounted for
                      from some source. In a tidal river, this increase in volume is accounted for from both the landward
                      river flow and the seaward flooding tide. This increase in water volume is referred to as the "tidal
                      prism" of the river. For every given flow volume in a river, there exists an imaginary boundary in the
                      river where the entire volume change dunng the rise in tide can be equated to the volume of ri@er flow
                      during that same time period. In other words, there exists a boundary where the prism volume is
                      exactly equal to the river flow (P(x) = R(x)). The entire river landward of this boundary, where P(x)
                      R(x), can be considered a purely advective river because there is no flow reversal, and therefore no
                      influence from the flooding waters from downstream. Ile portion of the river downstream of this
                      boundary experiences flow reversal and tidal mixing. This part of the river is truly under tidal
                      influence, and therefore experiences much different hydraulic mixing conditions. The Tidal Prism
                      Model was developed to model this portion of the river. Note that when there is negligible flow, the
                      entire river is influenced by this type of tidal mixing.

                      The feature that makes the Tidal Prism Model unique when compared to other finite section tidal
                      models is in the process by which the water body is segmented. During flood tide, large amounts of sea
                      water pass through the mouth of the water body and nuix with the inland fresh water. Because this
                      water mixes with the fi-eshwater during high tide, a portion of the contaminant is flushed out during ebb
                      tide. This process is known as "tidal flushing". Rather than hypothetically dividing the estuary into
                      finite segments, the tidal prism model assures complete mixing within each segment throughout a tidal
                      cycle by segmenting the water body according to its physical characteristics, i.e. tidal oscillation,
                      upstream flow and topography.

                      Segmentation begins at the mouth of the water body. The segment length is defined as the distance a
                      particle of water may travel upstream during one flood tide. Longitudinal segmentation is achieved by
                      continuing upstream from the mouth placing segment U-ansects at lengths according to the flooding
                      distance. Because the segment length is always equal to or less than the distance water will travel
                      during a flooding cycle, complete mixing is assured throughout the water body. The Tidal Prism
                      Model is a mathematical simulation of this tidal flushing process. 'Me model is capable of predicting
                      the longitudinal distribution of contaminants within a body of water and is therefore well suited for
                      long coastal embayments or tidal rivers (Kuo and Neilson, 1988). The Tidal Prism Model is
                      considered a dynamic model because it is able to predict the distribution of contammants at any given
                      point *in time, and is therefore not restricted to the steady-state condition.

                      The Tidal Prism Mass Balance Equation

                      The Tidal Prism Model mass balance equation is based upon the exchange of mass between segments
                      over an entire ebb to flood tide cycle. This equation is soived from the mouth (segment 1) toward the



                                                                                                                               j _'@









                         landward segments, successively solving for the high tide concentration in each segment. Ile equation
                         requires only the upstream and downstream boundary concentrations and the initial concentrations
                         existing in the water body. The equation begins at cycle 1, using the initial concentration fields that are
                         entered for the first time period, and solves successively upstr=m for the final concentrations in each
                         segment. These calculated concentrations in each segment then become the new starting point for the
                         second cycle and the process continues. ne cycling process continues at intervals equal to one tidal
                         cycle until the desired period of time has elapsed or a steady-state condition is reached. Figure 5-1 is
                         an elevation view of a hypothetical water body. This figure illustrates the exchanges which take place
                         between each segment. During flood tide, a volume of water equal to the prism volume minus the river
                         flow (P(n)-R(n)) moves into the landward segments from the downstream segments. Because the
                         model assumes that complete mixing takes place within each segment, this water that has flooded from
                         the downstream segments mixes completely with the water in the adjacent landward segments. During
                         ebb tide, a volume of water equal to the prism volume plus the river flow (P(n)+R(n)) moves seaward
                         from each segment. This exchange of volume between the ebb and flood tides creates what is re&rred
                         to as tidal flushing. Mass is slowly transported out of the water body by the constant dilutioq of the
                         sea water which floods into the coastal embayments or tidal rivers, mixes with the ambient
                         "contarninated" water, and is once again removed during ebb tide.

                         The returning ratio or "alpha" is incorporated into the flood tide transport portion of the mass balance
                         equation. This parameter accounts for the volume of water which moves out of a segment during ebb
                         tide and then returns at the same concentration in the following flood tide. Alpha therefore represents
                         the relative mixing which occurs between segments. Low values of alpha signify less water exchange
                         and therefore less mixing and vise versa. Sanfbrd et al. (1992) discuss *in detail the different
                         hydrodynamic properties of a water body which influence the value of this returning ratio at the
                         seaward boundary. In general, it was shown that the differences in current direction and magnitude at
                         the intersection of the embayment with the receiving water will influence the amount of contaminant
                         that is "returned" to the embayment upon flood tide.

                         5.2 Model Format
                         The Tidal Prism Model utilizes a notebook format to enter data and display model results. The first
                         five notebook pages provide screens for 'input data and the last notebook page is used to present tabular
                         and graphical model results. Each page of the notebook can be accessed by clicking on the
                         corresponding tab or pressing <Alt> plus the underlined letter of the tab header. Comprehensive
                         discussions regarding model input and parameter estimation are provided in Section 5.3 to Section 5.6.
                         Each of these sections corresponds to an individual notebook page *in the Tidal Prism Model.
                         Simulation results and model output are discussed in Section 5.7.

                         For each notebook page used to enter data, there is an example data set. This data set can be used as a
                         tutorial for the Tidal Prism Model. To access this data click on the [Example Data] buttons on each
                         notebook page. There is data available to meet all model options. These data can be used to become
                         fluniliar with how to navigate through the model and it provides an example of typical input and model
                         results.


                         The first notebook page, Project Info. serves as the Tidal Prism Model's 'introductory screen. This
                         notebook page can be used for record keeping purposes. There are text boxes available to enter in the
                         project title. date, and the names of the individuals involved with the model run. This notebook page
                         may be omitted if desired.




                                                                                                                                    5 - 3













                                P(N)   R(N)                            n+1                              n-I        MHW         2
                                                                                      r                                        I
                                                                                      I      p(n)         I        MLW

                                                                         F(D) + R(n)                        Op P(n-l)+R(n-1)
                                    V(N)                                 I            I      V(D)                                      V(2)            V(I)
                                                                         P(n) - R(n)  41                        P(B- 1) - FL(n- 1)







                              Figure 5-1. Elevation view of a hypothetical river illustrating the volumes of water excifanges
                              between adjacent segments during a complete tidal cycle.

                              The menu bar on the Tidal Prism Model provides the user with file access, editing capability, and help
                              information. Selecting File Will display a drop-down menu list with the following items: New, Open,
                              Save, Save As, Print, and Exit. New deletes the current dam set. A message box will ask for
                              verification prior to deleting current values. Open calls up the Open File dialog box to select an
                              existing data set. Save will save the current data set using the existing file name. If a file name has not
                              been defined, the Save As File dialog box will appear prompting the user to enter a file name. Save As
                              opens the Save As File dialog box toallow the current data set to be saved with a new file name.
                              Selecting Print will send the current model data and results, including the graph to the default
                              Windows printer. Exit closes the Tidal Prism Model and returns the user to the main CS Model
                              window. If the current data set has not been saved, it will be lost. Selecting Edit will display a drop-
                              down menu fist with Cut, Copy, and Paste. These menu items can be used to edit input data. Cut will
                              remove the selected text and move it to the windows clipboard. Copy will place a duplicate ofthe
                              selected text on the clipboard, but not remove the original text. Paste can be used to put text placed on
                              the clipboard back onto one of the input screens. Help will provide information pertaining to the Tidal
                              Prism Model. .


                              5.3 Parameters
                              The Parameters notebook page prompts the user to enter a series of stream parameters necessary to run
                              the Tidal Prism Model. The screen is divided into two portions: (1) the upper portion, which consists
                              of a series of text boxes that are used for numeric input data entered from the keyboard, and (2) the
                              bottom portion, which consists oftwo radio option buttons that allow the user to choose the duration of
                              time over which stream concentrations will be calculated.


                              The following numeric stream parameters must be entered in the upper text box portion of this
                              notebook page.

                              Number of Stream Divisions: In order to simulate the changing cross-sections of a body of water, the
                              Tidal Prism Model allows the user to divide the water body M*to a number of divisions. Each division
                              will consist of a 2iven len2th of the water body with an approximately constant cross-section and flow










                         volume. This text box prompts the user to enter the number of divisions in the water body being
                         studied.


                         Upstream River Flow: The upstream river flow parameter is considered the flow volume in m/day
                         which enters the UPSErcarn boundary segment of the water body.

                         Ambient River Concentration: The background concentration of the contaminant of interest present
                         in the upstream river flow is considered the ambient river concentration. The user is prompted to enter
                         this concentration in mg/L.

                         Mouth Concentration: The model requires that a mouth boundary concentration be entered at the
                         downstream limit of the water body. For calculation purposes, this concentration will remain constant
                         with time. The user should include stream divisions far enough downstream to allow for this constant
                         boundary condition.

                         Delta X: Ile delta X parameter refers to the calculation interval that is used for segmenting the water
                         body. The model will iterate upstream from the mouth at intervals equal to delta X in this calculation.
                         Small delta X values correspond to a more accurate segmentation of the water body, but also require
                         more computer time for the calculation. A delta X of I meter is recommended.

                         Minimum Segment Length: The minimum segment length is the rruiru*murn distance between segment
                         transects; that is allowed before the segmentation routine ceases. Because the segment lengths decrease
                         as one moves towards the upstream boundary of a water body, the upstrearri limit of the model's
                         segmentation will directly depend upon the minimum segment length in most cases.

                         The bottom portion of the parameters screen consists of the Desired Stream Concentration panel. In
                         this panel the user is given the choice of having the model compute concentrations after a finite number
                         of tidal cycles or at a steady-state condition. A steady-state condition is assumed to be reached when
                         the segment concentrations change less than 0. 000 1 percent between tidal cycles. The steady-state
                         option will usually require slightly more computer time due to the increased number of tidal cycles
                         which must be run through before this condition is reached. If the alternative option is chosen, the user
                         may enter the desired number of tidal cycles with the spin button at the bottom of the screen. The Tidal
                         Prism Model will calculate final concentrations after any number of tidal cycles have passed. This
                         option is useful when the user desires information about the time varying changes which may occur in a
                         stream after a spill or a slug discharge of finite duration has occurred. In this case, the number of tidal
                         cycles can be increased at a set increment between runs and the dispersion of the plume can be
                         visualized over time.

                         5.4 Stream Geometry
                         This screen allows the user to enter the stream geometry cross-section and flow data for each division
                         of the water body. Six variables are required to describe the cross-section of a stream, which is
                         estimated as a trapezoidal polygon. These include the followmig:

                         Slope I and Slope 2: These two slope variables refer to the "run to rise" ratio of the stream bank. In
                         other words, the side slopes are the ratio of the distance traveled horizontally divided by the distance
                         traveled vertically from the water surface to the bottom the channel. These variables are entered as
                         single. decimal values.




                                                                                                                                    5












                   Base Width: The base width is the width across the "bottom" of the channel.

                   High Depth: ne high depth is the mean depth of the stream division at peak high tide.
                   Low Depth: The low depth is the mean depth of the stream division at low tide.
                   Length: The length refers to the length of the individual stream division.

                   In addition to the stream geometry parameters, the user may also enter a value for the additional flow
                   into a division. This additional flow is assumed to begin at the upstream limit of the division and is
                   added to the total upstream flow 'in the river. This variable was incorporated into the model to account
                   for a tributary flow or a significant discharge into the water body. A significant flow is considered to
                   be one in which the river flow is significantly increased downstream of the point. When the river flow
                   is significantly increased, this change in flow must be included in the calculation of the segment
                   transect locations for an accurate representation of the real world condition.

                   5.5 Segmentation
                   Ile segmentation notebook page consists of a noninteractive spreadsheet display of the Tidal Prism
                   Model's segmentation of the water body. The segmentation spreadsheet displays seven parameters
                   associated with each segment. These seven parameters 'include the following:

                    Segment Number:    Numbering begins at the mouth and continues upstream.
                    Location:          This value is the distance from the mouth (considered to be at 0 meters) to the
                                        upstream transect of the segment.
                    Length:            This is the length between the upstream and downstream transects of a segment.
                    Low Volume:        This is the volume of the segment at low tide.
                    High Volume:       This is the volume of the segment at high tide.
                    Prism Volume:      The prism volume of a segment is the total volume of the tidal prism upstream of
                                        a segment.
                    River Flow:        The river flow is the total volume of water entering a segment from upstream.
                   5.6 Loading Data
                   The user may enter all relevant discharge loading parameters in the Loading Data notebook page.
                   Mass and volume data are entered into the Discharge Parameters spreadsheet. A loading source is
                   represented by both the volume per day that is discharged and the mass of the contaminant that is
                   carried within that volume. The user may enter a discharge volume (m'/day) and the mass of
                   contaminant discharged (gra/day) at any given point in the water body. Segment numbers and locations
                   are given in the first two columns to aid the user *in locating the point of discharge.

                   At the bottom of the screen, two panels have been included which define the loading characteristics and
                   the value of the returning ratio to be used in the calculation of final concentrations. The user may
                   define any given type of contaminant discharge. For instarice, a continuous discharge may be chosen
                   for a treatment plant flow or an industrial waste in which discharge is constant over time. For
                   circumstances where flow is not constant over time, such as runoff events or a one time slug discharge,
                   the finite discharge option button may be chosen. With this option. the user may indicate the duration




                                                                                                             5 -6










                         of the discharge using the spin button located at the bottom of the screen. For example, a spill of some
                         contaminant lasting two days would be represented by a finite discharge of a four tidal cycle duration.

                         The returning ratio can be defined as a constant value throughout the water body, or may be varied
                         linearly from the upstream boundary to the mouth. The linear gradient alpha value is represented by
                         the ratio of the total number of segments minus the segment number divided by the total number of
                         segments. This simple linear formula will vary alpha from zero at the upstream boundary segment
                         (total number of segments = segment number), to a value close to one at the first segment (segment
                         number two). For situations where the user desires to define alpha as a constant value, the spin button
                         at the bottom of the panel may be used to increment alpha between zero and one.

                         5.7 Table Results
                         The Table Results notebook page is divided into two halves. On the left hand side of the screen is the
                         noninteractive concentration output spreadsheet. This spreadsheet displays the tabular results of the
                         concentration routine. Concentrations are given in mg/L for each of the water body's segmeiits. On
                         the right half of the screen is the graphical output of the concentration data. This graph consists of a
                         plot of the segment concentrations versus their corresponding distance from the mouth. For each model
                         run, the concentration at half of the total cycles are plotted in addition to the final concentration in each
                         segment. Ile plot of the concentr  'ations at half of the total cycles was included to give the user an idea
                         of the general trend that the concentrations were moving in. For example, in an instantaneous spill one
                         would expect that the contaminant plume would disperse over time due to the dilution effects in the
                         water body. In this case, the concentration at half of the total cycles would be higher dm the final
                         concentration in each segment. Alternatively, for cases where the discharge is continuous, the final
                         concentrations would be higher 'in each segment due to the constant input of the contaminant. This
                         difference would continue until a steady-state condition is reached at which time the two plots would
                         overlap. exactly. The graphical output therefore gives the user information about both the final
                         concentrations in each segment and the general trend of the concentrations in the system.

























                                                                                                                                   5-7









                        6. Finite Section Model
                        The Finite Section Model (FINSEC) is a one-dimensional, steady-state water quality model that can be
                        used to dezerm@ne the concentrations of water quality variables in a river. It is based on dividing the
                        river or estuary into a number of approximately homogeneous regions or sections where the
                        concentration gradient is not significant within each reach. A mass balance is constructed around each
                        section for each water quality variable to be modeled. The model does not consider tidal effects.

                        6.1 Modeling Approach
                        The river is divided into segments of varying lengths, where the segment length is selected based on the
                        principle concentration gradients of the substance being modeled. If segments of equal length are
                        applied, the area of each segment will typically increase as the river be ins to widen near the mouth or
                                                                                                9
                        downstream boundary. The average river depth would also typically increase. An assumption in the
                        FINSEC Model is that velocity gradients and dispersion will provide complete mixing both literally
                        (across the river) and vertically such that the concentrations gradients are only along the axis of the
                        river (T'homann and Mueller, 1987). Figure 3-2 illustrates a possible segmentation of a river reach.
                        Segments are numbered from I to n.

                        The concentration of substance S in any segment i is calculated using a basic mass balance equation.
                        Thomann and Mueller (1987) have outlined the following components of the mass balance equation:
                           1. transport of S due to advective flow
                           2. mass transport due to tidal dispersion and density nuixing
                           3. loss of mass due to decay, and
                           4. any external sources or sinks of S.
                        This concept is graphically displayed in Figure 6-2. The subscript i refers to the value in segment i.
                        The subscripts i- 1, i and i, i+ I refer to the value at the interface between segment i and the upstream
                        and downstream segments, respectively. The FINSEC Model solves for the concentrations of
                        substance S at these interfaces. There are several different methods that can be applied to solve the





                                                                              waste
                                                Tributary                     Loading


                        Upstream
                        Inflow                                                                                        Ocean or
                                 1                 2       1   3                                                      Bay





                                                                             Trib
                                                                                 UP


                                 I          I              f       I        I                  I       I            I

                        Figure 6-1. Finite Section Conceptualization.




                                                                   Segment i


                                    Advective                                                                       Advective
                                    Flow, QI-1, I                        Volume, Vi                                Flow, QI + 1, I
                                                                            [St]
                                                                          Decay, Kt
                              Dispersion, EI-t, I                                                             Dispersion, EI + 1, I



                                                                          Sources or
                                                                          Sinks, Wi
                             Figure 6-2. Components of mass balance equation, adapted from Thomann and Mueller
                             (1987).


                         interface concentration: central, backward, or length dependent differencing options. These options are
                         discussed in greater detail in subsection 6.3.3.

                         Applying a backward differencing option, the numerical approximation of the mass balance equation
                         can be written as
                                  dSi                                                                           +
                               Vi __ = Qi-1,iSi-1 - Qi,i+1Si + Ei-1,i (Si-1 - Si) + Ei+1,i (Si+1 - Si) - KiViSi _ Wi
																		    																			
					    dt	                      
                         The FINSEC Model utilizes the steady-state condition, which assumes that all inputs, flow, exchanges,
                         and reaction rates are constant over time. This reduces the numerical mass balance equation to a
                         simple linear algebraic equation because Vi dSi      There will an algebraic equation for each
                                                                     ___ = 0.

											   dt	
                         defined segment. This set of simultaneous algebraic equations is solved using a matrix inversion.

                         6.2 Model Format
                         The FINSEC Model utilizes a notebook format to enter data and display model results. Ile first three
                         notebook pages provide screens for input data and the last two notebook pages are used to present
                         tabular and graphical model results, respectively. Each page of the notebook can be accessed by
                         clicking on the corresponding tab or pressing <Alt> plus the underlined letter of the tab header.
                         Discussions regarding model input and parameter estimation are provided in Sections 6.3 and 6.4.
                         Both of these sections corresponds to an individual notebook page in the FINSEC Model. Simulation
                         results and model output are discussed in Sections 6.5 and 6.6.

                         The first notebook page, Project Info, serves as the FINSEC Model's introductory screen. This
                         notebook page can be used for record keeping purposes.  There are text boxes available to enter in the
                         project title, date, and the names of the individuals involved With the model run. This notebook page
                         may be omitted if desired.






                                                                                                                                     6-2










                      On the Input Data notebook page, there is an example data set. This data set can be used as a tutorial
                      for the FINSEC Model. To access this data click on the [Example Data] button. This data can be
                      used to become familiar with how to navigate through the model and it provides an example of typical
                      input and model results. There is data available to meet all model options.

                      The menu bar on the Finite Section Model provides the user with file access, editing capability, and
                      help information. Selecting File will display a drop-down menu list with the following items: New,
                      Open, Save, Save As, Print, and Exit. New deletes the current data set. A message box will ask for
                      verification prior to deleting current values. Open calls up the Open File dialog box to select an
                      existing data set. Save will save the current data set us mig the existing file name. If a file name has not
                      been defined, the Save As File dialog box will appear prompting the user to enter a file name. Save As
                      opens the Save As File dialog box to allow the current data set to be saved with a new file name.
                      Selecting Print will send the current model data and results to the default Windows printer. Note that
                      graphs are not printed from this menu item. The graphs are printed directly from the Graph notebook
                      page using the [Print Graph] command button. Exit closes the FINSEC Model and returns the user to
                      the main CS Model window. If the current data set has not been saved, it will be lost. Selecting Edit
                      will display a drop-down menu list with Cut, Copy, and Paste. These menu items can be used to edit
                      input data. Cut will remove the selected text and move it to the windows clipboard. Copy will place a
                      duplicate of the selected text on the clipboard, but not remove the original text. Paste can be used to
                      put text placed on the clipboard back onto one of the input screens. Help will provide information
                      pertaining to the FINSEC Model.

                      6.3 Options
                      The Options notebook page is used to set the basic options for the model. These are the water quality
                      variables, boundary conditions, and differencing options. Each of these options is explained in the
                      following subsections.

                      6.3.1 Water Quality Variables
                      The concentrations of the water quality variables *in the river are what the FINSEC Model is being used
                      to determine. The model will currently estimate concentrations for five water quality variables. A
                      brief description of each variable is provided below, but a more detailed description is available in
                      Subsection 2.3.5 The default variable is salinity. Any or all of these variables may be selected for a
                      model simulation.


                      Carbonaceous Biochemical Oxygen Demand (CBOD): CBOD is an 'indicator of organic pollution
                      measured in terms of the oxygen demand that can develop as the organics are degraded. Units are
                      mg/L.

                      Nitrogenous Oxygen Demand (NBOD): NBOD is the equivalent measure of the organic nitrogen
                      and ammonia that will consume oxygen as they are converted to nitnite and nitrate. Units are mg/L.

                      Dissolved Oxygen (DO): A direct measure of the amount of oxv en dissolved within the water
                                      el                                                 .9
                      column. Units are mg/L.

                      Coliforms: Coliforms are bacten'aL'ri the Enterobacteriaceae family and are commoniv used as an
                      indicator of fecal contamination. Units are organisms/L.




                                                                                                                               6-3









                        Salinity: Salinity is commonly used to calibrate a finite section model for dispersion. It is treated as a
                        conservative material. Usually, the only loads for salinity arise at the mouth of the estuary or river.

                        6.3.2 Boundary Conditions
                        The FINSEC Model simulates a river or a portion of a river reach. The simulated area will have
                        boundaries on both the upstream and downstream ends. As with all models based on differential
                        equations, boundary conditions must be applied to obtain a solution. There are two type of boundary
                        conditions available in the FINSEC Model: fixed or linear gradient.

                        A fixed boundary condition requires a known concentration at the boundary. This concentration does
                        not vary regardless of any changes in loading or kinetics that occur within the modeled reaches. If this
                        option is selected, you will need to specify the boundary concentration for section 0 in the predicted
                        column of the Input Data spreadsheet.

                        A linear gradient boundary condition assumes that the trend in the two adjacent intenior sections, is
                        linear and can be extrapolated out to the boundary section. The boundary concentration is a function
                        of what occurs within the modeled region.

                        Boundary conditions must be applied to both the upstream and downstream sections. However, it is
                        perfectly allowable to mix boundary condition types. For example, a gradient upstream boundary and
                        a fixed downstream boundary is permitted.

                        If fixed boundaries are appropriate, they are generally easier to work with than gradient boundary
                        conditions. Gradient boundaries are more difficult to apply, but are more appropriate where little is
                        known about the boundary concentrations. However, gradient boundaries should not be used when
                        there are significant loadings to sections near the boundary because the trend will no longer be linear
                        and extrapolation to the boundary is not valid.

                        6.3.3 Differencing Options
                        The FINSEC Model solves the mass balance differential equation numerically by applying a finite
                        difference scheme. The concentration of substance S at the interface between segment i and segment i-
                        I must be determined for all segments. Differencing options provide the choice of how to solve for the
                        concentrations at the interfaces. There are thr= options: central, backward, and length dependent.

                        In almost all cases, the central difference option is the most appropriate. This assumes that the
                        concentration of S at the interface is equally influenced by the concentrations in both segment i and
                        segment i-I. This option is applicable when dispersive transport predominates. It is the most accurate
                        numerically, and exhibits the least numerical dispersion, however, it may yield negative predicted
                        concentrations if the section lengths are too large. To ensure that all predicted concentrations will be
                        positive, all segment lengths should be less than or equal to 2EN.

                        The backward difference option is most appropriate when advection predominates dispersion. This
                        option assumes that the concentration of S at the interface is completely dependent on the upstream
                        concentration 'in segment 1-1. It is easier to program and guarantees that the predicted concentrations
                        will be positive regardless of the section lengths. However, it is subject to high numerical dispersion.
                        Numerical dispersion is an increase 'in the dispersion of substance S as a result of the discretization
                        process. The concentration gradient of S is more spread out than the anaiytical solution would predict.



                                                                                                                               6-4










                     The length dependent approach is most appropriate when section lengths differ significantly. This
                     option will interpolate the concentration of S at the interface using similar triangles to compare slopes.
                     It is included for more advanced users.

                     6.4 Input Data
                     The Input Data notebook page is where the necessary hydraulic and chemical properties are entered for
                     the FINSEC Model. The appearance of this notebook page will vary depending on the modeling
                     options selected. The user should first set the number of sections to be modeled, including the two
                     boundary sections. This number can be entered by either clicking on the text box and typing the
                     number from the keyboard or by clicking on the spin buttons until the desired number appears. The
                     data entry spreadsheet itself consists of one row for each section that will be modeled. 'Me boundary
                     sections are highlighted in blue. If the number of sections is increased, blank rows are added to the
                     bottom of the spreadsheet. If the number of rows is decreased, the bottom row is removed from the
                     spreadsheet and any data in that row are lost.

                     The number of columns requiring data input will vary depending on which water quality variables are
                     selected. The length, cross-sectional area, flow, and dispersion coefficient for each segment must
                     always be entered. If the substance being modeled degrades in the natural environment than a decay
                     coefficient should be entered. Any known loadings of the modeled substances should also be entered
                     for each applicable segment.

                     The river reach being modeled can be divided into any number of sections. As the number of sections
                     increase, the number of simultaneous equations to solve increases and simulation time will also
                     increase. Segment length should be based on stream geometry, points of discharge, and the selected
                     differencing option. Thomann and Mueller (1987) state that a section length of 1-2 miles (1.6-3.2 k:m)
                     will generally provide a good representation of the actual river. Segment lengths should be smaller
                     around waste loading (discharge) points. If larger segments are used at discharge points than dilution
                     could produce predicted concentrations that would be less than an observed value. The selected
                     differencing option could affect either the positivity of predicted values or the amount of numerical
                     dispersion generated by the model. If the central differencing option is selected, numerical dispersion in
                     not a problem, but positivity could be. Refer to Subsection 6.3.3. If the backward differencing option
                     is selected dm the effects of numerical dispersion should be considered when selecting segment length.
                     Smaller segments will yield less numerical dispersion.

                     If dissolved oxygen is being modeled, entry boxes for the temperature and salinity are shown. These
                     are used to calculate the dissolved oxygen saturation concentration. For the Coastal Screening Model,
                     sea level is always used for the elevation. If salinity is being modeled, the saturation calculation uses
                     the modeled salinity concentration in each section and ignores the mean value.

                     6.5 Model Results
                     Selecting the Graph or Tables notebook page Will run the FINSEC Model. The mouse pointer will
                     change to an hourglass while the simulation is being processed. Results from the FINSEC Model can
                     be examined as either concentrations plots or in a tabular format. To view tile results 'in a graphical
                     forriiat, click on the Graph notebook tab or press <Alt G>. A complete description of this notebook
                     page is provided in Subsection 6.5. 1. To view the tabular results, click on the Tables notebook tab or
                     press <Alt T>. A compete description of this notebook page is providedmi Subsection 6.5.2.




                                                                                                                         6_5








                        6.5.1 Graph Output
                        The results from the FINSEC Model can be viewed as concentration or loading plots versus distance.
                        To display the model results, select the desired water quality van'ab!e ::nd statistic option. The graphs
                        can be sent to a printer by clicking on the [Print Graph] button or pressing <Alt P>.

                        6.5.2 Table Output
                        Selecting the Tables notebook page displays a nomnteractive spreadsheet containing the model results.
                        Ile row number corresponds to the segment number. The number of columns will vary depending on
                        the number of water quality variables selected. The input values for flow and dispersion in each
                        segment and for the water quality variables are reiterated. The volume of each segment has been
                        calculated from the segment length and cross-sectional area and is displayed in the spreadsheet. The
                        predicted concentrations in each segment for each modeled water quality variable is also displayed in
                        the spreadsheet.







































                                                                                                                          6-6








                        7. Spill Model
                        Fhe Spill Model solves the advective diflusive equation for an instantaneous spill of a material 'into a
                        6ver or a stream. Instantaneous is the name applied to the assumption that the material is completely
                        mixed vertically and axailly immediately following the spill. The model provides an analytical
                        solution. The equation is established for one dimension, and therefore, the concentration of the material
                        is onlv a function of the distance downstream and the time elapsed since the spill occurred. The initial
                        pulse of material will move downstream with time because of advection. As time increases, the pulse
                        will spread out because of dispersion and the total mass of the material will decrease through first order
                        decay.

                        The Spill Model is based on the following mass balance equation:
                                 as            19S     E    as,        k
                                 at            dX          0 2 X

                        where    s  =   solvent concentration
                                 t  =   elapsed time since spill occurred
                                 x  =   distance downstream from spill location
                                 E  =   dispersion coefficient
                                 u  =   average velocity
                                 k  =   first order decay rate

                        7.1 Model Format
                        The Spill Model utilizes a notebook format to enter data and display model results. The first two
                        notebook pages provide screens for input data, the next two notebook pages present tabular and
                        graphical model results, and the final notebook page allows for model calibration. Each page of the
                        notebook can be accessed by clicking on the corresponding tab or pressing <Alt> plus the underlined
                        letter of the tab header. Section 7.2 provides information regarding model input and parameter
                        estimation. Simulation results and model output are discussed in Section 7.3. Model calibration is
                        explained in Section 7.4.

                        An example data set is included with the Spill Model and can be used as a tutorial. To access this data
                        click on the [Example Data] buttons on the Parameter notebook page. These data can be used to
                        become familiar with how to navigate through the model and it provides an example of typical input
                        and model results.


                        The first notebook page, Project Info, serves as the Spill Model's introductory screen. This notebook
                        page can be used for record keeping purposes. There are text boxes available to enter in the project
                        title, date, and the names of the individuals involved with the model run. This notebook page may be
                        on-dtted if desired.


                        The menu bar on the Spill Model provides the user with file access, editing capability, and help
                        information. Selecting File will display a drop-down menu list With the following items: New, Open.
                        Save, Save As, Print, and Exit. New deletes the current data set. A message box will ask for
                        verification prior to deleting current values. Open calls up the Open File dialog box to select an



                                                                                                                                7-1









                        existing data set. Save will save the current data set using the existing file name. If a file name has not
                        been defined, the Save As File dialog box will appear prompting the user to enter a file name. Save As
                        opens the Save As File dialog box to allow the current data set to be saved with a new file name.
                        Selecting Print will send the current model data and results, including the graph to the default
                        Windows printer. Exit closes ttie Spill Model and returns the user to the main CS Model window. If
                        the current data set has not been saved, it will be lost. Selecting Edit will display a drop-down menu
                        list with Cut, Copy, and Paste. These menu items can be used to edit input data. Cut will remove the
                        selected text and move it to the windows clipboard. Copy will place a duplicate of the selected text on
                        the clipboard, but not remove the original text. Paste can be used to put text placed on the clipboard
                        back onto one of the input screens. Help Will provide information pertaining to the Spill Model.


                        7.2 Parameters
                        This notebook page allows the user to enter the required model data and decide how the simulation
                        results will be displayed. The values for these parameters can be entered directly into each text box by
                        clicking on it and then entering the desired value from the keyboard. The text boxes may also be
                        accessed using the <Tab> key. As each text box in the Model Data fi-ame becomes active, its
                        corresponding label will turn blue. Clicking on the label for the various input parameters will display a
                        pop-up message box with help information.

                        Flow: Ile average flow of the river in m'/second.
                        Dispersion: 'Me dispersion coefficient of the river allows for tidal effects and diffusion from
                        concentration gradients. Units are square kilometers per day. A typical dispersion coefficient is
                        0.03 - 0.3 krn2/day.
                        Area: This is the average cross-sectional area of the river in square meters.
                        Spill Mass: The total mass of the contaminant spilled *into the river in kilograms.
                        Decay Rate: 'Me first order decay rate of the contaminant deternunes the rate at which the contaminant
                        disappears. The higher the decay rate, the faster the contaminant will disappear. Units are l/day.

                        The display results fi-ame allows the user to specify how the model will display the simulation results.
                        The beginning and ending distances are from the point of the spill. Negative (upstream) distances are
                        permissible. The upstream concentration values could be important in systems where dispersion
                        predominates flow. The distance interval is entered in the text box beneath the Every header. The
                        beginning and ending time in days must also be specified. Time zero is when the spill occurred.
                        Selection of tirne should reflect the decay rate of the contaminant.

                        The [Clear] button will delete all values frorn the parameter text boxes. If this button is selected, a
                        message box will appear asking for verification prior to removing current values.

                        7.3 Model Results
                        Selecting either the Graph Results or the Table Results notebook page will begin the model simulation.
                        The mouse pointer will change to an hourglass while the simulation is being processed. Results from
                        the Spill Model can be examined as either concentrations plots or ul a tabular format. To view the
                        results 'in a graphical forniat, click on the Graph Results notebook tab or press <Alt G>. A complete
                        description of this notebook page is provided in Subsection 7.3. 1. To view the tabular results, click on









                      the Table Results notebook tab or press <Alt T>. A compete description of this notebook page is
                      provided in Subsection 7.3.2.

                      7.3.1 Graph Results
                      The predicted concentrations can be viewed versus distance or time. The concentration plot versus
                      distance is automatically displayed when the Graph Results notebook page is activated. There will be a
                      concentration plot for each specified time period. Each of these plots is in a different color. To change
                      to the concentration versus time plots, select the time option button below the plot area. The graph will
                      change accordingly. There will be a concentration plot for each specified distance interval.

                      7.3.2 Table Results
                      The model results are presented ii a spreadsheet format. The first column is distance along the river
                      from the point of the contaminant spill. The second column is the time from when the contaminant was
                      spilled. The time series will reflect the values selected on the Parameter notebook page. Tb@ time
                      series will be repeated for each distance interval. Third column contains the contaminant concentration
                      in mg/L at the specified distance and time.

                      7.4 Calibration
                      This notebook page allows the user to calibrate the Spill Model to observed data if it is available. To
                      enter the observed values, click on the [Observed Data] button. A new form will fill the notebook
                      page. Enter the observed concentrations in the spreadsheet and give their appropriate time and distance
                      from the spill. If needed, an entire row can be deleted from the spreadsheet by clicking on the [Delete
                      Row] button. The (Example Data] button will provide a sample data set. The [Clear] button will
                      delete all values from the spreadsheet. If this button is selected, a message box will appear asking for
                      verification prior to removing current values. When you have entered all observed values, select the
                      [Close] button to return to Calibration notebook page.

                      Ile Spill Model Calibration allows the user to change one of the input parameters and quickly assess
                      the results through the concentration plots, residual plots, or the calibration statistics. To change one
                      or more parameters, click on the appropriate spin button or enter the desired value directly into the
                      appropriate text box. To evaluate the effect that the new parameter value has on the predicted
                      concentrations, select the (Run Model] option button. The graphical display and calibration statistics
                      will be automatically updated.

                      If the predictions option is selected in the plot type frame, then the user can view the concentrations
                      plots as either points or curves. There are also option buttons for selecting either distance or time as
                      the x-axis label. The default plot is predicted contaminant concentration versus distance. When the
                      residuals option is selected, the other two option frames disappear. The residual plot of the observed
                      versus the predicted concentrations will appear in the graph window. Viewing the residuals can help
                      improve the calibration effort if the residuals indicate a trend.

                      The calibration statistics are shown in the shaded box to the fight of the parameter text boxes. The
                      Spill Model supplies both the sum of the squared deviations (SSR) and the sum of the absolute
                      deviations (NUD).









                        After a calibration run has been perforined, if the exact predicted values or residuals are desired, select
                        the [Observed Data] button to view the spreadsheet. The predicted values and the residuals will be in
                        the fourth and fifth colunins, respectively.







                     8. Utility Models
                     The utility models option has not been completely developed for this version of the CS Model. Utility
                     models are designed to aid the user with quick, simple calculations. Currently, there is a utility model
                     for estimating dispersion coefficients, for determining DO saturation, and for Manning's open channel
                     flow.
































































                                                                                                                          3-









                      9. References
                      Alhajar, B.J., J.H. Harkin, and G. Chesters. 1989. Detergent formula and characteristics of
                      wastewater in spetic tanks. Journal of the Water l'odurion Control Federation, 61(5): 605-613.

                      Basta, DJ, and Moreau. 1982. Introduction to analyzing natural systems. Analyzing Natural
                      Systems, Chapter 2, D.J. Basta and B.T. Bower, (eds.), Resources for the Future, Washington, D.C.

                      Bosen, J.F. 1960. A formula for approximation of saturated vapor pressure over water. Monthly
                      Weather Reviews, 88(8): 275-276.

                      Browning, G.M. 1979. Development for and of the Universal Soil Loss Equation. Universal Soil
                      Loss Equation: Past, Present, and Future. SSSA Special Publication Number 8. Soil Science Society
                      of America, Madison, Wisconsin.

                      Dombush, J.N., J.R. Anderson, and L.L. Harms. 1974. Quantification ofPollutants in Agricultural
                      Runoff. EPA-660/2-74-005. U.S. Environmental Protection Agency, Washington, D.C.

                      Dyer, K.R., and P.A. Taylor. 1973. A simple, segmented, prism model of tidal mixing in well-mixed
                      estuaries. Estuarine and Coastal Marine Science, 1: 411418.

                      Gottschak L. C. 1964. Sedimentation. In: V. T. Chow (ed.). Handbook ofApplied Hydrolou.
                      MacGraw-Hill, New York, NY.

                      Haan, C.T. 1972. A water yield model for small watersheds. Water Resources Research, 8(l): 58-69.

                      Haith, D.A., R. Mandel, and R. S. Wu. 1992. Generalized Watershed Loading Functions, Version
                      2 0, User's Manual. Department of Agnicultural and Biological Engineering, Cornell University,
                      Ithaca, New York.

                      Hamon, W.R_ 196 1. Estimating potential evapotranspiration. Proceedings of the American Society of
                      Civil Engineers, Journal of the Hydraulics Division, 87(HY3): 107-120.

                      Hamrick, I.M., and B.J. Neilson. 1989. Determination ofMarina Buffer Zones Using Simple Mixing
                      and Transport Models. Virginia Institute of Marine Science.

                      Ketchum, B.H. 195 1. The exchange of fresh and salt waters in tidal estuaries. Journal ofMarine
                      Research, 10(l): 18-37.

                      Kuo, A.Y., and B.J. Neilson. 1988. A modified tidal prism model for water quality in small coastal
                      embayments. Water Science and Technology, 20(6): 133-142.

                      Kuo, C.Y., K.A. Cave, and G.V. Loganathan. 1988. Planning urban best management practices.
                      Water Resources Bulletin, 24(l): 125 - 13 2.

                      Luettinger, J.C. 1995. A Tidal Pr ism Anai.ilsis oj"rhe Soluble Copper Mixing Zone around the
                      Occoquan Water Treatment Plant. Master's thesis submitted to the faculty of Virginia Polytechnic
                      Institute and State Universitv.



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