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



                                                                                Final Product
                                                                            V-

                                                                                    3/31/93











                          WATER QUALITY MONITORING PROGRAM DESIGN

                                          to be implemented by

                        CHESAPEAKE BAY LOCAL ASSISTANCE DEPARTMENT


                                            in Polecat Creek






                                 Project Designed and Report Prepared By:

                                            Jean N. Tingler

                                            Adam A. Frisch





                             VIRGINIA COUNCIL ON THE ENVIRONMENT
                                          EcoMAP SECTION
                                       North 9th Street, Suite 900
                                       Richmond, Virginia 23219





                                             February 1993





                 This project was funded, in part, by the Virginia Council on the Environment's Coastal
           Resources Management Program through Grant #NA170ZO359-01 of the National Oceanic and
           Atmospheric Administration, Office of Ocean and Coastal Resource Management, under the
           Coastal Zone Management Act of 1972 as amended.









                            CHIESAPEAKE BAY LOCAL ASSISTANCE DEPARTMENT
                                  WATER QUALITY MONITORING PROGRAM
                                VOLUME 1 - MONITORING PROGRAM DESIGN


                                               TABLE OF CONTENTS


                                                                                        PAGE


             List of Figures                                                            ii

             List of Tables                                                             iii

             Acknowledgements,                                                          iv

             Executive Summary                                                          1

             Chapter 1. Water Quality Monitoring Program Design                         5

             Chapter 2. The Polecat Creek Project Design                                10

                    Section 1. The "Axle"                                               10


                            Trend Monitoring - Surface Water                            10
                            Information Expectations                                    14
                            Parameters to be Monitored                                  15
                            Parameter Justification                                     17


                            Biological Monitoring
                                   Benthic Macroinvertebrates
                                   Information Expectations                             21

                                   IBI
                                   Information Expectations                             22

                            Rainfall Gage Network
                            Information Expectations                                    23
                            Parameters to be Monitored                                  24
                            Parameter Justification                                     25


                    Section 2.The "Wheels"                                              26
    SO
             Chapter 3. Description of the Polecat Creek                                28

             Chapter 4. Glossary                                                        34

             Chapter 5. Literature Cited                                                43












                                               LIST OF FIGURES




            Figure                                                                       Page

            Figure 2.1 "Wheel and Axle" Concept of WQ Monitoring Program. Design         11

            Figure 2.2 Polecat Creek Trend Network Stations                              12

            Figure 3. 1 Polecat Creek, Caroline County, Virginia                         30

            Figure 3.2  Polecat Creek, Primary and Secondary Roads                       31

            Figure 3.3  Polecat Creek, Streams and Wetlands                              32

            Figure 3.4  Polecat Creek, Resource Protection Areas (RMA)                   33















                      I


                                                    LIST OF TABLES



            Table                                                                                        Page


            Table 1. 1      Information Flow in a Monitoring System                                      6

            Table 1. 2      Steps in the Design Process                                                  7

































                                                             iii












                                                ACKNOWLEDGENIENTS



                     The authors would like  'to thank the members of the Polecat Creek Technical Advisory
              Committee for their time and technical expertise. These individuals are Scott Crafton and Darryl
              Glover from the Chesapeake Bay Local Assistance Department, Adam Frisch and Alfredo
              Freuenfelder from the Virginia Council on the Environment, Ronald A. Gregory, Rick Hoffman,
              Al Pollock, and Charlie Morgan from the Virginia Water Control Board, and Mike Flagg from
              the Virginia Department of Conservation and Recreation.

                     The EcoMAPS staff of the Council on the Environment was instrumental in the
              completion of this project. Leigh Tetrault and Carol Reynolds digitized data and provided
              clerical services, respectively. Leigh Medford provided technical assistance as well as artistic
              insight during the production of graphics for several presentations and the final project report.
              Finally, Alfredo Freuenfelder, Melanie Seigler, Sylvia Tertziotti, and George Muelbach provided
              technical assistance, support, and almost unlimited patience acquiring and developing
              applications with the geographic information system hardware and software.

                     Ted Polk and his staff at the Virginia State Library spent many hours locating and
              ordering literature references for this project. We greatly appreciate their efforts on our behalf.























                                                              iv












                                              EXECUTIVE SUAIMARY



                    In 1991 the Chesapeake Bay Local Assistance Department (CBLAD), the Virginia Water
            Control Board (VWCB), and the Virginia Council on the Environment (COE) submitted a joint
            grant proposal to the National Oceanographic and Atmospheric Administration (NOAA), Coastal
            Zone Management (CZM) Program. This grant requested monies to design a water quality
            monitoring program for CBLAD. COE was the lead agency on this project. The EcoMAP
            section of COE was given primary responsibility for the scope of work outlined in the grant
            proposal, and unless otherwise stated all aspects of the plan development were performed by
            EcoMAPS staff. The design criteria provided by CBLAD to COE were:

                    1)     the program would be funded for ten years,

                    2)     the project would be located in a small watershed in Chesapeake Bay drainage,
                           currently rural but in which urban development would likely occur in the next
                           three to five years,

                    3)     CBLAD would select the study drainage, and

                    3)     the primary goal of the monitoring program would be to describe the efficacy of
                           emerging land use regulations and policies in protecting adjacent water quality
                           during urban development activities.

            Of course, the land use regulations and policies being tested are those developed by the CBLAD
            and the county governments in response to the Chesapeake Bay Preservation Act.

                    After the main goal of the program was set, it was determined from that goal what kinds
            of data were required to address the information needs. The project was divided into three main
            components and a list of objectives for each component was developed. The components were:

                    1)     design a system of water quality monitoring networks that would provide
                           quantitative information about chemical, physical, and biological parameters from
                           a watershed in the Chesapeake Bay drainage;

                    2)     develop a data base of land use activities and land cover characteristics in the
                           watershed and monitor changes in each over the life span of the project; and

                    3)     use a geographical information system (GIS) to develop a link between the water
                           quality data, the land use and land cover data and, digital geographic base map
                           data. This component will be used to assess these data at the end of the project
                           as well as to develop a nonpoint source pollution model for the watershed.








                     The Polecat Creek watershed which is in south-central Caroline County was determined
             to be the most appropriate watershed for this study. It was selected for several reasons:

                     1)     Polecat Creek has diverse physiographic features. The headwaters rise in the
                            piedmont, flow through the fall zone, and converge with the Mattaponi river in
                            the coastal plain.

                     2)     The drainage area is about 30,000 acres which is the size recommended for
                            watershed projects by the EPA and the USDA.

                     3)     Although the watershed is currently rural, it will likely undergo urban
                            development in the next ten years. Currently, the predominant land cover in the
                            watershed is forest, followed by open fields and pastureland, but about two thirds
                            of the watershed is designated a primary growth area in the Caroline County
                            comprehensive plan. Also, it is located on the Interstate 95 corridor between
                            Richmond, Virginia and Washington, D.C.

                     To begin this project an extensive literature review on design of water quality monitoring
             systems was performed (these references are listed by subject later in this document). During
             the literature review process, a glossary was developed and is included in this document. The
             following statements were written by some of the foremost authors and researchers in water
             quality monitoring system design, and they were used to drive the design phase of the Polecat
             Creek Monitoring Program.

                     "Water quality monitoring is an effort to obtain an understanding of the chemical,
                     physical, and biological characteristics of water via statistical sampling. To achieve an
                     understanding of chemical, physical, and biological characteristics of water, samples are
                     collected; analyzed; data from the sample analysis are stored; the data are retrieved and
                     analyzed statistically; reports are written describing the behavior of water quality
                     variables; and the reports must then be read and understood (Sanders et al. 1983)."

                     "If a management agency wants answers to water quality questions then the questions will
                     have to be quantified and a monitoring system, including its statistical methods, designed
                     before the data are collected (Loftis and Ward 1987).

                     "The exact procedures to be used in the day-to-day operation of the monitoring system
                     need to be documented throughout the entire system. From preparation of sampling
                     routes and specification of sampling protocols through identification of' standard
                     laboratory analysis methods to definition of data handling and storage procedures, the
                     operating procedures need to be documented in detail. To leave portions of the
                     monitoring system undefined or poorly defined, is to leave open the opportunity for
                     inconsistent operation of the monitoring system. This permits introduction of variability
                     into the data that comes from the operation of the monitoring system and not from the
                     behavior of the water quality variables" (Ward 1989).


                                                             2









                    As stated above, all activities undertaken in a monitoring program must be documented.
             The Polecat Creek Water Quality Monitoring Program standard operating procedures (SOP's)
             are presented in several volumes and record the monitoring program design as well as SOP's
             used in the project.

                    Chesapeake Bay Local Assistance Department, Polecat Creek Water Quality Monitoring
             Program, Volume 1: Introduction and Monitoring Program Design is the first volume of
             documentation and includes a review of water quality monitoring program design, the method
             used to design the Polecat Creek project, and a description of Polecat Creek watershed. Also,
             a glossary of important terms used in monitoring and a literature review of program design,
             project reports, statistical analysis methods, chemical analysis methods, field methods, and
             biological monitoring are included in this volume.

                    The second volume, Chesapeake Bay Local Assistance Department, Polecat Creek Water
             Quality Monitoring Program, Volume 2: Standard Operating Procedures - Sample Collection,
             contains detailed methodologies for collecting water, sediment and fish tissue samples as well
             as methodologies for performing the EPA's Rapid Bioassessment Protocol III and the Index of
             Biotic Integrity. Of course, this includes all pertinent information concerning type, size and
             preparation of sampling containers, preservation, holding times, and quality assurance/quality
             control procedures. When sampling equipment is purchased, a schedule of maintenance,
             calibration, routine repair and replacement will be added to this document.

                    Chesapeake Bay Local Assistance Department, Polecat Creek Water Quality @Vonitoring
             Program, Volume 3: Standard Operating Procedures - Chemical Analysis will document all
             chemical protocols, bench methodologies, calculations and calibrations performed by the selected
             analytical laboratory. These will adhere to the EPA's requirements outlined in Methods for
             Organic Chemical Analysis of Municipal and Industrial Wastewater and the American Public
             Health Association's Standard Methods for the &amination of Water and       'Wastewater. This
             document will be produced when CBLAD selects an analytical laboratory.

                    The fourth volume, Chesapeake Bay Local Assistance Department, Polecat Creek Water
             Quality Monitoring Program, Volume 4: Data Handling, Analysis, and Reporting describes the
             software and data base management system, provides documentation for WQSTAT 11 and the
             EPA STORET data base, and documents the statistical methods used for reporting.             Also
             included are methods of data interpretation and evaluation.

                    The GIS for the project is described in Chesapeake Bay Local Assistance Department,
             Polecat Creek Water Quality Monitoring Program, Volume 5: Geographic Information System.
             So far this document contains a description of all GIS hardware and software, a digitizing
             protocol, and a dictionary of all data in the system.





                                                            3









                    Chesapeake Boy Local Assistance Department, Polecat Creek Water Quality Monitoring
            Program, Volume 6: Land UselLand Cover Data Base will be developed during the first year
            of the monitoring program. This volume will contain a dictionary (definition and description)
            of individual land uses and land covers, methodologies for delineating each, and a methodology
            for annually updating the data sets.

                    Chesapeake Bay Local Assistance Department, Polecat Creek Water Quality Monitoring
            Program, Volume 7: Special Studies will provide guidelines for development of special studies,
            including quality assurance project reports. It will also be a repository for special study project
            reports.








































                                                           4











                                                        CHAPTER I
                                        Water Quality Monitoring System Design

                     "Water quality monitoring is an effort to obtain an accurate understanding of the
             chemical, physical, and biological characteristics of water through statistical sampling" (Sanders
             et al. 1983). To understand water quality conditions a number of tasks must be performed.
             Table 1. 1 provides a schematic representation of these tasks and the information flow in a water
             quality monitoring system (Sanders et al., 1983).

                     For many years when a monitoring program was being designed, the focus of the design
             was on "what, where, and how". In other words, what water quality constituents or parameters
             to monitor, at what physical location in the stream, and how to collect those particular samples
             (Item 1, Table 1. 1). During that time tremendous quantities of data were collected with little
             thought given to how those data would be used by management or how they would be
             statistically analyzed and interpreted. The focus on data collection led. to a situation that Ward,
             Loffis and McBride (1986) referred to as the "data rich but information poor syndrome" in water
             quality monitoring.

                     Of course, collection activities are important to data quality of a monitoring program, but
             these activities alone do not constitute a viable monitoring program. During the last ten years
             a number of researchers have investigated and evaluated design of water quality monitoring
             programs (Brown, 1991; Loftis and Ward, 1987; McBride, 1987; Sanders et al., 1983; Ward,
             1988; Ward, 1989; Ward et al., 1990; Ward and Loftis, 1989). As a result of this work, a new
             method of designing water quality monitoring programs has emerged. This method entails
             viewing the design process in an entirely new manner. The following is a brief description of
             the steps in the design of a water quality monitoring system. Table 1.2 provides an outline of
             this process and this is the template that was used to design the Polecat Creek Water Quality
             Monitoring Program.

                     In this format, Step I provides a list of tasks that must be addressed to define and
             describe the information expectations of the water quality monitoring program. Unfortunately,
             to some individuals defining goals and objectives sounds like a waste of time, that goals and
             objectives should be "understood" by anyone routinely involved in the monitoring program.
             Today, most researchers and program designers recognize this step as essential to the success
             of their monitoring programs. A concise and clear statement of goals and objectives will drive
             and direct all activities undertaken during the monitoring program. The goals and objectives
             dictate the statistical methods used, the location of monitoring stations, the parameters
             monitored, and the frequency of sampling, as well as the type of chemical analyses used and
             minimum acceptable analytical detection limits. Having a written statement of goals and
             objectives will allow each component of the monitoring program to be reviewed in a logical
             manner with subsequent decisions based on how each component fits into the overall
             management objective for the water quality monitoring program.



                                                              5











           Table 1.1    Schematic Representation of the Information Flow in a Water Quality
                        Monitoring Information System.




                        Sample Collection
                               *Sample Techniques
                               *Field Measurements
                               *Sample Preservation
                               *Sample Transport

                        Laboratory Analysis
                               *Scheduling and Operational Procedures
                               *Laboratory Analysis Procedures
                               *Laboratory Quality Control
                               *Data Recording

                        Data Handling
                               *Screening and Verification
                               *Computer Hardware
                               *Data Base Management System
                               *Storage and Retrieval

                        Data Analysis
                               *Statistical Procedures
                               *Statistical Software
                               *Deterministic Modeling

                        Reporting
                               *Formats
                               *Frequency
                               *Distribution


                        Information Utilization
                               *Public
                               *Policy Making
                               *Administration
                               *Technical








                                                      6











           TABLE 1.2   Steps in the Design of a Water Quality Monitoring Information System
                       (Ward et al. 1990).

           STEP 1.     Define Information ELcMtAons
                       ODetermine management and corresponding monitoring goals
                       ODefine water quality for monitoring system design purposes
                       OIdentify statistical methodology to be used by monitoring system
                       *State statistical conclusion to be drawn from data and discuss how these
                       conclusions relate to management goals
                       *Describe means of reporting conclusions

           STEP 2.     Confirm Statistical Desi2n Criteria
                       *Statistically characterize water quality "population" to be sampled
                             *plot concentration and flow (and load, if appropriate) versus time
                             0 normality testing
                             *variance homogeneity testing
                             0 independence testing
                       OState that assumptions of chosen statistical methodology are met

           STEP 3.     Design Monitoring Network
                       *Where to sample (from management/monitoring goals)
                       OWhat to measure (from water quality definition and management/monitoring
                       goals)
                       OHow frequently to sample (from needs of selected statistical methodologies)

           STEP 4.     Develo Qperating Plans and Procedures
                       GSampling routes, equipment, and employee training
                       OField sampling and analysis procedures
                       *Sample preservation and transportation
                       *Laboratory analysis and quality control procedures
                       *Data verification protocols
                       *Data storage and retrieval hardware and software
                       *Data analysis software for chosen statistical methodology

           STEP 5.     Develo Information R=rting Procedures
                       *Type, format, and frequency of reporting
                       *Distribution of reports
                       *Automation of reporting
                       OEvaluation of information relative to expectations defined in Step I





                                                  7








                    Step 2 of the design outline describes statistical design criteria. Again, this step should
             be addressed early in the monitoring program design. The first point in this procedure is to
             "statistically characterize the water quality population to be sampled", and includes a list of
             graphical and statistical tests which might be used to accomplish this. Each of these tests centers
             around understanding and describing the t3W of statistical analysis (parametric or nonparametric)
             that will be appropriate for use.

                    Robustness is a term used by statisticians to describe the resistance of a parti        cular
             statistical test to giving "false positives". The robustness of parametric and nonparametric tests
             is dependent on different assumptions about the "water quality population" being tested. For
             parametric tests these assumptions are:

                    a)      the underlying distribution should be normal,

                    b)      the data should be independent (no serial or temporal correlation), and

                    c)      the data should exhibit homogeneity of variance.

             If any of these assumptions is violated, then the results of parametric tests can be very
             misleading.    For nonparametric statistical tests, the only assumption is that the data are
             independent, since nonparametric tests are performed on ranks of data and therefore do not rely
             on any underlying distribution or homogeneity of variance. Water quality data rarely display
             a normal distribution pattern or homogeneity of variance, and it takes skill to ensure that data
             are independent. For these reasons nonparametric statistical tests provide the best available
             method of supplying information about many water quality parameters.

                    Also, knowing what statistical test will be used to analyze the resulting data will provide
             the information required to select an appropriate sampling frequency. Sample collection and
             analysis is very expensive and time consuming. Too few samples can waste years of effort,
             while too many samples can waste time and money that could be spent on more useful activities.


                    After the goals and objectives have been defined and the statistical methodology selected,
             Step 3 can be addressed. This is the time to decide "where, what, and how often". There are
             a number of factors to consider in determining where to monitor. First, the macrolocation
             should be selected. Macrolocations are river reaches which will be sampled within the river
             basin, and are a function of the specific objective of the sampling agency. Secondly, the
             microlocation will be selected. Microlocation is an actual station location which is located
             relative to unique or pertinent features within a rivei reach. The microlocation is a function of
             the hydraulics and mixing characteristics of the stream. The most important aspect of station
             selection is that each station be representative. That is each station must provide samples which
             will provide data relative to the management goals. For example, if the agency goal is to
             determine trends over time, then the stations should be placed to yield information characteristic
             of reaches of the river and, in composite with other stations, provide information characteristic


                                                              8








             of the condition of the river system in general (Keith 1991).

                    Secondly, during this step, each parameter must be defined and reasons for its selection
             documented. Also, a description of how each parameter will be used to reflect water quality
             must be provided (in essence, a justification for monitoring each constituent).

                    Finally, the frequency of sampling must be determined. Of course, if the protocol is
             followed, the frequency of sampling will have already been determined by the statistical test
             which was selected in Step 2.

                    As stated earlier "the exact procedures to be used in the day-to-day operation of the
             monitoring system need to be documented throughout the entire system. From preparation of
             sampling routes and specification of sampling protocols through identification of standard
             laboratory analysis methods to definition of data handling and storage procedures, the operating
             procedures need to be documented in detail. -To leave portions of the monitoring system
             undefined or poorly defined is to leave open the opportunity for inconsistent operation of the
             monitoring system. This permits introduction of variability into the data that comes from the
             operation of the monitoring system and not from the behavior of the water quality variables"
             (Ward 1989). These activities are undertaken in Step 4 of the program design.

                    Developing standard operating procedures for collection of water quality samples and
             chemical analysis is typically the least difficult phase of designing a water quality monitoring
             program. Collection methodologies for surface water, sediment, fish, fish tissue, benthic
             macroinvertebrates, fecal coliform bacteria, rain water and ground water are well documented
             in the literature (see Literature Review - Collection Methodologies and Biological Monitoring).
             Also, private industry, wishing to make their equipment "user friendly", has developed SOP's
             for most of the commonly used monitoring equipment. As for chemical analysis and laboratory
             QA/QC, both the EPA and USGS have developed manuals and/or issued directives concerning
             both (see Literature Review - QA/QC and Laboratory Analysis).

                    Developing data handling and storage procedures is also a relatively simple, but time
             consuming task. Data handling, storage and retrieval methods are documented in several
             government publications. There are many commercial software packages available as well as
             several government-sponsored data base systems available for data storage and retrieval. This
             step simply involves selecting the software that is most useful, cost effective and usable by
             individuals in the monitoring program and subsequently acquiring the appropriate documentation
             manuals and training for monitoring personnel.









                                                            9












                                                       CHAPTER 2
                                NETWORK DESIGN - POLECAT CREEK PROJECT



                     The Polecat Creek water quality monitoring program networks are designed after the
             "wheel and axle" concept of water quality monitoring network design (Ward et al., 1990). What
             this actually means is that the monitoring program is comprised of two different types of station
             networks: network(s) of stations referred to as the "axle" network(s) and a series of special
             study networks referred to as "wheel" networks (Figure 2. 1).

                     In this monitoring program design, the "axle" is a network(s) of stations that makes up
             the "back bone" of the monitoring program. It is data collected from these stations that are used
             to perform statistical trend analyses. These are fixed stations (station location does not change)
             at which samples are taken using standard operating procedures describing collection techniques
             at specific time intervals, using specific collection, preservation, and analytical techniques.
             These methodologies will not change over the life of the project (with the possible exception of
             chemical analytical methodologies).

                     "Wheels" are networks of stations that are actually special studies or intensive stream
             surveys. Typically, a special study network is an intensive sampling effort with a limited time
             frame and a specific information purpose related to a particular water quality problem that needs
             further definition. In other words, there are a relatively large number of stations over a fairly
             small area. These stations are monitored to observe a particular event or practice.

             Section 1. The "Axle" or backbone of the Polecat Creek Project

                     The "axle" of the Polecat Creek Water Quality Monitoring Program consists of two
             networks of eight stations each (Figure 2.2). The first network, referred to as "Trend Network -
              Surface Water" will be comprised of an in-stream network of stations monitoring surface water
             conditions. Chemical, physical, and biological parameters will be monitored. The second
             network, "Trend Network - Rain Fall", will consist of an off-stream network monitoring
             quantity, quality, and intensity of rain fall. Each of these types of monitoring is essential in
             obtaining an accurate understanding of water quality conditions in the Polecat Creek watershed.



             "Trend Network - Surface Water"


                     This network will monitor chemical, physical and biological parameters. Data from these
             stations will be used to identify long-term changes or trends in water quality.

                     In order to monitor physical and chemical parameters, each station will have a stream
             gage (weir), automatic sampler, and an automatic data logger. Flow data are essential in


                                                             to







                                                     ANALYSIS & INTERPRETATION




        LT







                                                                           BIOMONITORING NETWORK:


                                                                              Fixed sites
                                                                              (trend detection)
                                                                              Floating sites
     ',,--Water Quality Monitoring Program                                    (pop. characterization)

        Chesapeake Bay Local Assistance
                  Department                                            TREND DETECTION NETWORK:
                                                                           Fixed sites (monthly sampling)
                                                                           Fixed sites (seasonal sampling)


                                                    T I M E

               The conceptual "Wheel and Axle" design frame to be used for monitoring streams as
               part of the proposed long-term monitoring program designed to assess the efficacy of
               state and local landuse regulations in protecting water quality during urban development.

       Prepared by: Virginia EcoHAP System, Council on the Environment                     Figure 2.1




                                  POLEC AT                                CREEK




                             Jill



                                 tp
                                                                                                     !!441






                                         TREND MONITORING STATIONS
                                                                                                             FIGURE 2.2









            identifying long term trends in water quality data because they allow concentration data to be
            converted to loading data normalized for season.

                    Biomonitoring efforts will include monitoring benthic macroinvertebrate community
            structure (EPA's Rapid Bioassessment Protocol III) and fish community structure (Index of
            Biotic Integrity - IBI). These monitoring efforts will in the short-term describe biological
            community structures and in the long-term record any changes in the community structures.
            Biomonitoring is integral to any water quality monitoring program, but is particularly important
            to the Polecat Creek project since this project will assess the effectiveness of best management
            practices and land use regulations in the watershed. It has long been recognized that "assessing
            the integrated response of biological communities to highly variable pollutant inputs offers a
            particularly useful approach for monitoring nonpoint source impacts and the effectiveness of
            certain BMP's" (Plafkin, 1989).

            "Trend Network - Rain Fall"


                    An off-stream network of rainfall gages in close proximity to the in-stream stations will
            record quality, quantity and intensity of rainfall. These data are required in an effective
            nonpoint source monitoring program for two reasons. Rain water is a potential source of
            nutrients as well as pH and temperature changes to surface water. Secondly, quantity and
            intensity of rain fall will describe how much and in what time frame water moves through the
            system. For example, two inches of rain falling over a time frame of two days has a
            tremendously different implication to surface water quality than does two inches of rain falling
            over a time frame of two hours.





























                                                            13










                              information Expectations for the "Axle" or Backbone Networks
                                               Trend Network - Surface Water



              Management Goal:Determine the efficacy of state and local land use regulations in protecting
              water quality during and after urban development

              Monitoring Objective:                  Detect and measure temporal trends in water quality

              Definition of Water Quality:           Nutrients, sediments, temperature, pH, flow, oxygen, and
                                                     bacteria


              Statistical Methodology:               Seasonal Kendall Test

              Statistical Hypothesis:                H,,: No trend exists
                                                     H,,: Trend exists

              Monitoring System Product:             Description of appearance or absence of a trend over time.

              Reporting:                             If there is a trend toward improved water quality or there
                                                     is no discernible trend in water quality over time, then state
                                                     and local land use regulations will remain unchanged. If
                                                     there is a trend toward degraded water quality for those
                                                     parameters associated with state and local land use
                                                     regulations, then recommendations will be made to modify
                                                     regulations to better protect water quality.




















                                                               14











                                      Trend Network - Surface Water
                                        Parameters to be Monitored


           STORET Parameter Code          Description

           -----------------------------------------------------------------
           00010                          Temperature (degree Q

           00061                          Flow, (ft3/sec)

           00076                          Turbidity (NTU)

           00094                          Conductivity, (micro-seimans/cm)

           00300                          Oxygen, dissolved (mg/L)

           00301                          Oxygen, dissolved (% saturated)

           00310                          BOD5


           00400                          pH, field (Standard Units)

           00403                          pH, lab (Standard Units)

           00410                          Alkalinity, lab (mg/L as CaC03)

           00453                          Bicarbonate, water dissolved, IT field (mg/L as HC03)

           00940                          Chloride


           00500                          Solids, total (mg/L)

           00505                          Solids, total volatile (mg/L)

           00510                          Solids, total fixed (mg/L)

           00515                          Solids, dissolved (mg/L)

           00530                          Residue, total at 105 degree C,
                                          suspended (mg/L)

           00535                          Residue, volatile, suspended (ing/L)

           00540                          Residue, fixed, nonfilterable (mglL)


                                                  15









          00545                           Solids, settleable (mg/L)

          00610                           Nitrogen, Ammonia total (mg/L as N)

          00613                           Nitrogen, Nitrite dissolved (mg/L as N)

          00615                           Nitrogen, nitrite total (mg/L as N)

          00618                           Nitrogen, nitrate dissolved (mg/L as N)

          00620                           Nitrogen, nitrate, total (mg/L as N)

          00625                           Nitrogen, total Kjeldahl
                                          Ammonia + organic total (mg/L as N)

          00665                           Phosphorus, total (mg/L as P)

          00666                           Phosphorus, dissolved (mg/L as P)

          00671                           Phosphorus-ortho, (P04), dissolved (mg/L as P)

          70507                           Phosphorus-ortho (P04), total (mg/L as P)

          00680                           Carbon, total organic (mg/L as C)

          00900                           Hardness, total (mg/l as CaC03)

          00945                           Sulfate, dissolved (mg/L as S04)

          80154                           Sediment, suspended (mg/L)

          31506                           Bacteria, total coliform/100ml MPN

          31616                           Bacteria, fecal coliform/100ml MFM, M-FC broth, 44.5
                                          deg C

          31614                           Bacteria, fecal coliform/100ml MPN, tube configuration

          31618                           Bacteria, fecal streptococci/100ml







                                                   16













                                               Trend Network - Surface Water
                                               Justification for each Parameter



              Dissolved Oxygen

                      Dissolved oxygen is essential to aquatic life as well as to the breakdown of organic waste
                      materials that may be present in a stream. The US EPA (      1986) "Gold Book" established
                      a concentration of 5.0 milligrams of oxygen per liter of water to be the minimum level
                      for adequate maintenance of a varied fish population.

              Temperature

                      Temperature has a significant effect on chemical reactions in water. It can effect the
                      solubility of chemicals, the rate of reactions, and the metabolic rate of biota. Besides
                      the obvious seasonal variations there are other factors that can effect water temperature.
                      These include, but are not limited to the removal of riparian vegetation and the input of
                      heated waste water.


              Flow


                      Flow data are essential in performing statistical tests for trend analysis. Having this data
                      available allows for seasonal variations to be accounted for during data analysis.

              Biochemical Oxygen Demand

                      "The use of dissolved oxygen during the metabolism of organisms and the oxidation of
                      biologically oxidizable organic material in water can be measured by a 5-day biological
                      oxygen demand test (BOD5). The BOD5 is useful to evaluate the amount of oxidizable
                      organic material in the water. BOD5 values of I to 8 are common for streams
                      moderately contaminated with domestic waste water.

              pH

                      of The pH of water is fundamental to the nature of the chemical reactions that occur in the
                      water. In general, aquatic life requires pH to be within a range of 6.5 to 9 units (US
                      EPA 1986). Low pH values can increase the solubility of materials toxic to aquatic life
                      and cause detrimental effects. Consumption of carbon dioxide by algae causes a
                      decreased acidity, causing pH to rise."





                                                                17









              Alkalinity

                      "Alkalinity buffers acidity of water reducing changes in pH that may occur, for example,
                      in response to algae activity, acid precipitation, and waste water discharges. The
                      bicarbonate ion can be a major contributor to the alkalinity of water.               Because
                      bicarbonate can reduce the toxicity of certain metals to aquatic life, the US EPA
                      recommends a minimum of 20 mg/L of alkalinity as CaC03 (1986).

              Bicarbonate


                      The US Forest Service recommends monitoring bicarbonate (HC03) when assessing
                      impacts from the use of fertilizers.

              Hardness


                      "Hardness in the water is caused by polyvalent cations, primarily calcium and
                      magnesium, and to a lesser extent, strontium, ferrous iron, and the manganous ion.
                      Hardness is generally dependent on contact of the water with certain chemicals and
                      minerals in soils and local rock formations. In addition, calcium and magnesium are
                      abundant in seawater, so hardness generally increases with increased mixing of
                      freshwater with seawater. Many of the aquatic life criteria (US EPA 1986)'vary
                      depending on the water hardness because toxicity of metals and other constituents to
                      aquatic life increase as water hardness decreases."

              Suspended Sediment

                      "Sediment is the solid material transported by stream discharge, either in suspension or
                      along the stream bottom, and consists primarily of fragmental material that originates
                      from weathering of rocks and includes soils and organic debris. Many nutrients, metals,
                      and synthetic organic materials, such as pesticides are readily sorbed and transported by
                      sediment particles.

              Turbidity

                      "Turbidity is caused by suspended material in water. High turbidity reduces sunlight
                      penetration and may limit algal growth capacity.,,

              Solids, (Total, Suspended, and Dissolved)

                      "The matter that remains as residue after a water sample is evaporated is generally
                      referred to as total solids. This residue can be further defined by measurements to
                      determine (1) dissolved solids, which is primarily inorganic salts, and (2) suspended
                      solids, which is undissolved constituent generally comparable to suspended sediment.
                      Solids can be further subdivided into volatile and nonvolatile fractions. The volatile


                                                               18









                    fraction is primarily the organic material in the sample; the nonvolatile fraction of the
                    residue is primarily the inorganic material in the sample. Dissolved solids, reported in
                    milligrams per liter, is mostly used in reference to freshwater quality. The amount of
                    dissolved material in water is environmentally important because it helps managers
                    determine the ultimate use or treatment of water and plays a critical role in the types of
                    aquatic life that populate the waters.

             Chloride


                    "Chloride is one of the major constituents of dissolved solids in seawater. Locally,
                    trends detected in chloride are expected to be similar to those seen for dissolved solids
                    and salinity. The US Forest Service recommends monitoring chloride (CI) when
                    assessing impacts from the use of fertilizers.

             Sulfate (S04)

                    The US Forest Service recommends monitoring sulfate when assessing impacts from the
                    use of fertilizers.


             Specific conductance

                    "Specific conductance is a measure of the ability of water to conduct electric current and
                    is measured in uS/crn (microsiemens per centimeter at 25 degrees Q.                Specific
                    conductance is dependent upon the number and types of ions dissolved in the water and
                    is, therefore, useful as an indirect measure of the relative amounts of chemical ions in
                    solution.


             Macronutrients (Carbon, Nitrogen, and Phosphorus)

                    Carbon, nitrogen, and phosphorus are primary chemical elements required by plants for
                    growth. Eutrophication, the enrichment of a body of water with nutrients, is normally
                    associated with increases in algal populations. The accumulation of organic matter
                    caused by growth and decomposition of algae in turn provides habitats and ample food
                    supplies for bacteria and other aquatic organisms. These effects are usually most
                    pronounced in lakes and estuaries where accumulation of nutrients may result in
                    particularly high concentrations of algae.

                    Carbon - A range of 5 to 15 mg/L total organic carbon (TOC) is characteristic of the
                    upstream edge of the tidal zone of river and estuary waters of Chespeake Bay. However,
                    TOC concentrations in swamps and bogs, which can be relatively high generally range
                    from 30 to 40 mg/L. Because carbon is readily available in the environment as carbon
                    dioxide or bicarbonate, it is unusual that carbon would limit the growth of algae.




                                                             19








                     Nitrogen - "Nitrogen is critical in the growth of algae. Total nitrogen concentrations
                     larger than 0.3 mg/L indicate potential for nuisance growth of algae. The oxidation of
                     reduced forms of nitrogen (ammonia and organic nitrogen) in surface waters is readily
                     accomplished by aerobic aquatic biota that produce nitrite and nitrate nitrogen. Because
                     natural processes oxidize reduced nitrogen, concentrations of reduced nitrogen are
                     transient in surface water" (USGS, 1990).

                     Phosphorus - "Phosphorus is the third major nutrient essential to algal growth. The
                     National Technical Advisory Committee (1968) recommends 0.05 mg/L total phosphorus
                     (as P) as the maximum limit for waters entering impoundments. Other sources note that
                     total phosphorus concentrations in lakes above 0.01 mg/L promote nuisance algal growth.
                     A concentration below 0. 1 mg/L is recommended to prevent algal blooms in streams
                     (USGS 1990). Phosphorus undergoes seasonal and other cycles in the abundance of its
                     organic and inorganic forms due to biological activity and physical cycles. Thus, total
                     phosphorus (which represents all forms: dissolved, particulate, organic and inorganic) is
                     believed to better indicate phosphorus enrichment or reduction in ecological assessments
                     rather than its soluble nutrient forms. Orthophosphate is the form of phosphorus which
                     is most available for plant growth.

                     Carbon: nitrogen: phosphorus ratios - Ratios of carbon to nitrogen to phosphorus can be
                     used to evaluate which nutrient is limiting algal growth. A comparison of the measured
                     ratios to an average plant tissue composition carbon: nitrogen:phosphorus ratio of 47:7: 1
                     can show which nutrient is in relatively limited supply. It is important to note that
                     nutrient ratios based strictly on observed water column concentrations of nutrients do not
                     always clearly indicate the limiting nutrient. In particular, seasonal variation in nutrient
                     limitation and limits of nutrient chemical forms available to phytoplankton are not
                     reflected in a simple nutrient ratio comparison.

             Biological Characteristics

                     "Bacteria - Fecal coliform bacteria commonly live in the gut and feces of warmblooded
                     animals. Although all species of this group are not human pathogens, the occurrence of
                     fecal coliform bacteria indicates probable fecal contamination and possible presence of
                     pathogenic species. The US EPA raw-water criteria for body contact is a geometric
                     mean of 200 fecal coliform colonies per 100 milliliters of water. Fecal streptococci
                     bacteria also indicate fecal contamination from warmblooded animals. The ratio of fecal
                     coliforms to fecal streptococci is sometimes used to identify the origin of bacterial
                     contamination. Ratios greater than 4.0:1 indicate contamination primarily'of human
                     origin, whereas ratios less than 0.6:1 indicate animal origin."







                                                              20











                              Information Expectations for the "Axle" or Backbone Networks
                                             Benthic Macroinvertebrate Network



              Management Goal:Determine the efficacy of state and local land use regulations in protecting
              water quality during and after urban development

              Monitoring Goal:                      Characterize the biotic component of the watershed and
                                                    subsequently describe existence and severity of any
                                                    identified impairment.

              Definition of Water Quality:          Benthic macroinvertebrate community structure.

              Statistical Methodology:              Rapid Bioassessment Protocol 111, Plafkin, 1989.

              Statistical Hypothesis:               HO: the community is not impacted by land use activities
                                                    H.: the community is impacted by land use activities

              Monitoring System Product:            Description of status and trends in the benthic
                                                    macroinvertebrate community structure.

              Reporting:                            Identification of use impairment through biological
                                                    monitoring will initiate special studies to identify the
                                                    specific agents causing the impact. These special studies
                                                    might include intensive surveys of water chemistry, fish
                                                    tissue, sediment, and/or toxicity testing. Results of special
                                                    studies will be used to determine and limit (or eliminate)
                                                    specific sources.

















                                                              21











                             Information Expectations for the "Axle" or Backbone Networks
                                         IBI (Fish Community Structure) Network


             Management Goal:Determine the efficacy of state and local land use regulations in protecting
             water quality during and after urban development

             Monitoring Goal:                      Description of status and identification of changes in fish
                                                   community structures.

             Definition of Water Quality:          Fish community structure as defined by the Index of Biotic
                                                   Integrity (IBI).

             Statistical Methodology:              IBI Metrics (Karr 1981; Angermeier and Karr 1986;
                                                   Angermeier and Schlosser, 1987)

             Statistical Hypothesis:               H,,: the fish community structure is not impacted by land
                                                   use activities.
                                                   H.: the fish community structure is impacted by land use
                                                   activities.


             Monitoring System Product;            Description of status and trends in the fish community
                                                   structure.


             Reporting:                            Identification of use impairment through biological
                                                   monitoring will initiate special studies to identify the
                                                   specific agents causing the impact. These special studies
                                                   might include intensive surveys of water chemistry, fish
                                                   tissue, sediment, and/or toxicity testing. Results of special
                                                   studies will be used to determine and limit (or eliminate)
                                                   specific sources.













                                                             22











                              Information Expectations for the "Axle" or Backbone Networks
                                                  Trend Network - Rain Fall




             Management Goal:                        Determine the efficacy of state and local land use
                                                     regulations in protecting water quality during and after
                                                     home construction activities.


             Monitoring Goal:                        Characterize rain fall patterns, rain water quantity, quality,
                                                     and intensity.

             Definition of Water Quality:            pH, nitrogen, phosphorus, sulfate

             Statistical Methodology:                Seasonal Kendall Test

             Statistical Hypothesis:                 H,,: there is no trend in rain water quality.
                                                     H,,: there is a trend in rain water quality

             Monitoring System Product:              Description of status and trends in rain water quality.

             Reporting:                              These data will be used in conjunction with data from the
                                                     trend network - surface water. They will be used primarily
                                                     to eliminate or identify rain water as a source of pH or
                                                     nutrient trends in surface water and to identify times of
                                                     high surface runoff. These data will be reported to the
                                                     Chesapeake Bay Local Assistance Board and to the EPA
                                                     Chesapeake Bay Program.
















                                                               23













                                       Trend Network - Rain Fall
                                       Parameters to be Monitored



          STORET CodeDescription

          004OOpH (field), standard units

          00610                           Nitrogen, Ammonia total (mg/L as N)

          00613                           Nitrogen, Nitrite dissolved (mg/L as N)

          00615                           Nitrogen, nitrite total (mg/L as N)

          00618                           Nitrogen, nitrate dissolved (mg/L as N)

          00620                           Nitrogen, nitrate, total (mg/L as N)

          00625                           Nitrogen, total Kjeldahl
                                          Ammonia + organic total (mg/L as N)

          00665                           Phosphorus, total (mg/L as P)

          00666                           Phosphorus, dissolved (mg/L as P)

          00671                           Phosphorus-ortho (PO4), dissolved (mg/L as P)

          70507                           Phosphorus-ortho (P04), total (mg/L as P)

          00945                           Sulfate, dissolved (mg/L as S04)














                                                  24













                                                Trend Network - Rain Fall
                                        Justification for Monitoring each Parameter


             pH

                    There is ample evidence in the scientific literature to support the contention that some
                    areas of the country are impacted by "acid rain". It is essential to the Polecat Creek
                    project to eliminate or identify rain water as a source of pH changes in surface water.

             Nitrogen

                    There is evidence to indicate that rain water can be a source of nutrients to surface
                    water. This phenomenon has been reported in the Chesapeake Bay drainage. It is
                    essential to the Polecat Creek project to eliminate or identify rain water as a source of
                    nitrogen to surface water.

             Phosphorus

                    There is evidence to indicate that rain water can be a source of.nutrients to surface
                    water. This phenomenon has been reported in the Chesapeake Bay drainage. It is
                    essential to the Polecat Creek project to eliminate or identify rain water as a source of
                    phosphorus to surface water. Total phosphorus (which represents all forms: dissolved,
                    particulate, organic and inorganic) is believed to better indicate phosphorus enrichment
                    or reduction in ecological assessments rather than its soluble nutrient forms.

             Sulfate


                    There is evidence to indicate that rain water can be a source of sulfate to surface water.
                    It is essential to the Polecat Creek project to eliminate or identify rain water as a source
                    of sulfate to surface water.
















                                                             25











             Section 2.      The "Wheels"; Special Studies and Intensive Stream Surveys.


                     As noted before, "wheels" are networks of stations that are actually special studies or
             intensive stream surveys. The "wheels" or special studies of the Polecat Creek program will
             be used to determine the potential sources or reasons for the changes in water quality.

                     An outline of the requirements for a special study design follows, with each special study
             having a sampling plan and quality assurance work plan which will provide the following:

                     1.      Describe the environmental problems and concerns that led to the initiation of the
                             monitoring project. This should include information on specific environmental
                             concerns, general history and project background, the current situation, and the
                             projected impacts to the environment if no action is taken.

                     2.      Define what the environmental goals (management and monitoring) are, and how
                             the goals can be achieved.

                     3.      Define acceptable confidence (including confidence interval) and power, and state
                             a statistical methodology and hypothesis.

                     4.      Describe information expectations.

                     5.      Describe any regulatory requirements.

                     6.      Define data quality objectives (these are qualitative and quantitative statements of
                             the quality of data which is needed to support specific decisions or actions). The
                             quality of the data must be compatible with the decision malcing requirement.
                             This should include specific standard operating procedures used to assess data
                             precision, accuracy, representativeness, completeness, and comparability.

                     7.      Provide a list of parameters which will be monitored and a written justification
                             for each parameter.

                     8.      Describe how the data will be used and a reporting format.

                     9.      Provide standard operating procedures for collection and chemically analyzing
                             data.


                     10.     Describe data reduction, validation and reporting procedures.




                                                              26








                     11.    Describe Quality Assurance/Quality Control procedures including: internal
                            quality control checks, performance and system audits, and preventive
                            maintenance with a description of the required corrective action and QA reporting
                            procedures for problem situations.

                     Examples of some special study networks might include:

                     1)     pre-construction or pre-logging monitoring (development of "base-line" data set)
                            which will require monitoring during base-flow and high-flow events,

                     2)     monitoring a high flow event after logging or construction activities,

                     3)     monitoring high flow events near potential agricultural, commercial, or industrial
                            nonpoint sources, and

                     4)     monitoring the influence of nearby septic systems on stream water quality.

             All special study project plans and reports will be kept in Chesapeake Bay Local Assistance
             Department, Water Quality Monitoring Program, Volume 7, Special Studies.





























                                                            27













                                                      CHAPTER 3
                             DESCRIPTION OF THE POLECAT CREEK DRAINAGE


                     The Polecat Creek watershed which is in south-central Caroline County (Figure 3. 1) was
             determined to be the most appropriate watershed for this study. It is in the headwaters of the
             Mattaponit River which is in the York River system. Polecat Creek was selected as the study
             area for several reasons:


                     1)     Polecat Creek has diverse physiographic. features. The headwaters rise in the
                            piedmont, flow through the fall zone, and converge with the Mattaponi river in
                            the coastal plain.

                     2)     The drainage area is about 30,000 acres which is the size recommended for
                            watershed projects by the EPA and the USDA.

                     3)     Although the watershed is currently rural, it will likely undergo urban
                            development in the next ten years. Currently, the predominant land cover in the
                            watershed is forest, followed by open fields and pastureland, but about two thirds
                            of the watershed is designated a primary growth area in the Caroline County
                            comprehensive plan. Also, it is located on the Interstate 95 corridor between
                            Richmond, Virginia and Washington, D.C.

                     The 1990 US Census reported 5,569 individuals living in the Polecat Creek watershed.
             Most of these individuals live in the Lake Caroline or the Lake Heritage developments. Both
             these impoundments are located on the Stevens Mill Run tributary to the Polecat Creek. There
             are about 144 miles of paved roads in the drainage including a section of Interstate 95 which
             bisects the drainage in the fall zone (Fig 3.2).

                     Some of the environmentally sensitive areas in the drainage include wetlands and potential
             habitat for endangered species. Approximately 2,433 acres of wetlands and waterbodies, occur
             in the drainage (Fig 3.3). There are about 5,234 acres of Chesapeake Bay Preservation Areas
             (Resource Protection Areas) buffering these wetlands and waterbodies (Fig 3.4). The Polecat
             Creek watershed presents the habitat requirements for three plant species listed as federal
             endangered or threatened species. A list of these species with a short description of habitat
             requirements and threats to the species follows (DGIF 1992).

                     "Small whirled pogonia, Isottia medeoloides (Pursch) Raftesque, is extremely rare in
                     Virginia ... It occurs in third-growth upland forests with open understories.         The
                     population is threatened by urban development and by deer grazing."

                     "Swamp pink, Helonia@ bullata, is extremely rare in Virginia. It occurs along small
                     watercourses, in springy ground, or in other areas where water conditions are stable and


                                                            28








                      rarely subject to flooding. The swamp pink is vulnerable to damage from logging,
                      roadbuilding, trampling, or drainage at the few unprotected sites."

                      "New Jersey Rush, Juncus caesafiensis, is extremely rare in Virginia. It has been
                      reported from five Coastal Plain counties, where it occurs in very acidic usually
                      sphagnous, hardwood swamps, seeps, swales, or pond margins. Ditching, ponding, or
                      clearcutting of the overstory will result in the elimination of this species."

                      The following describes the current water quality conditions of the Polecat Creek and was
              taken from the Virginia Water Control Board's 1990 Section 305(b) Report: "The Polecat Creek
              waterbody encompasses an area of approximately 50 square miles in Caroline County. It
              includes the mainstem and tributaries, from its confluence with the Mattaponi River to the
              headwaters. The Polecat Creek station (8-PCT002.29) near Rt. 601 is monitored monthly for
              state water quality standards. Sediment and water column samples were analyzed for metals,
              but less frequently than for the state standards. There were no violations of the standards or
              exceedences, of criteria for metals. This station serves as a biological monitoring station as well
              as an ambient water quality monitoring station. The benthic macroinvertebrate community at
              this station was. rated fair, showing no improvement from the last 305(b) reporting period. The
              fair rating is similar to the current bioassessment rating of moderately impaired. The habitat and
              substrate limitations at this station may restrict the sensitive portions of the benthic community.

                      Several municipal facilities, including the Caroline County Regional STP and one
              industrial facility, Pilot Oil Corp. #291, discharge into this waterbody. A stream survey was
              conducted in February 1988 to determine the impacts of the sewage treatment facilities and low
              stream flows. Results indicated that there was nutrient overload in this stream.


                      Based on the results of the stream survey, six miles of this segment partially support the
              Clean Water Act (CWA) goal for swimmable waters. Polecat Creek partially supports the CWA
              goal for fishable waters in 5.50 miles due to the moderately impaired rating of the benthic
              community. The remainder of the waterbody fully supports the CWA goal for fishable and
              swimmable waters."



















                                                              29





                                                                                                                                                                  POLECAT CREEK




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                                                                                                  VIRGINIA DEPARTMENT OF CONSERVATION AND RECREATION

                                                                                                  PREPARED BY VIRGINIA ECOMAP PROGRAM









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                                                        GLOSSARY



             Absolute Method - a method in which characterization is based entirely on physically
                     (absolute) defined standards (Taylor, 1987).

             Accuracy - "is a measure of the degree of agreement of a measured value with an accepted
                     reference or true value. It is usually expressed in terms of percent recovery of the true
                     value and is an expression of the amount of bias in the data" (Dillaha et al. 1988).

             Aliquant - A divisor that does not divide a sample into a number of equal parts without
                     leaving a remainder; a sample resulting from such a divisor (Taylor, 1987).

             Aliquot - A divisor that does divide a sample into a number of equal parts without leaving a
                     remainder; a sample resulting from such a divisor (Taylor, 1987).

             Analyte - the specific component measured in a chemical analysis (Taylor, 1987).

             Autocorrelation - is a measure of how data points are related in time.              Values of the
                     autocorrelation range from - I to + 1. Plus (+) I = a perfect relationship, while 0 =
                     independent distribution. Autocorrelation may result from seasonality, trend, or serial
                     correlation. Seasonality will appear as a cyclic pattern.

             Benthos - the community of organisms living in or on the bottom or other substrate in an
                     aquatic environment.

             Bias -  A systematic error inherent in a method or caused by some artifact or idiosyncrasy of
                     the measurement system. Temperature effects and extraction inefficiencies are examples
                     of this first kind of bias. Blanks, contamination, mechanical losses and calibration errors
                     are examples of the latter kinds. Bias may be both positive and negative, and several
                     kinds can exist concurrently, so net bias is all that can be evaluated except under special
                     conditions (Taylor, 1987).

             BLANKS - matrices that have negligible or unmeasurable amounts of the substance of
                     interest.  Wherever a possibility exists for introducing extraneous material into a
                     collection, treatment, or analytical procedure, a blank should be devised to detect and
                     measure the extraneous material.


                     Field blanks - samples of analyte free media similar to the sample matrix. They are
                     transferred from one vessel to another or exposed to the sampling environment at the
                     sampling site.



                                                             34








                    Trip blanks - are test samples of analyte-free media taken from the laboratory to the
                    sampling site and returned to the laboratory unopened.

                    Background samples (matrix blanks or control samples) - are samples of the media
                    similar to the test sample matrix and are taken near to the time and place where the
                    analytes of interest may exist at background levels.

                    Equipment blanks - are samples of analyte-free media that have been used to rinse the
                    sampling equipment.      They document adequate decontamination of the sampling
                    equipment after its use.

                    Field Spike Samples - selected field samples to which a known amount of the analytes
                    of interest are added during their collection in the field. In the event that background
                    samples are not practical to collect, field spiked samples can provide a reasonable
                    substitute that will help to estimate matrix effects; however, field spiked samples may
                    have higher extraction efficiencies than unspiked test samples.

                    Material blanks - are samples of construction materials such as those used in groundwater
                    wells, pump and flow testing, etc. They document the decontamination (or measure
                    artifacts from use of the materials.


             Blind Sample - a sample submitted for analysis whose composition is known to the submitter
                    but unknown to the analyst. A blind sample is one way to test proficiency of a
                    measurement process (Taylor, 1987).

             Calibrant - a substance used to calibrate or establish the analytical response of a measurement
                    system (Taylor, 1987).

             Calibration - comparison of a measurement standard or instrument with another standard or
                    instrument to report or eliminate by adjustment any variation (deviation) in the accuracy
                    of the item being compared (Taylor, 1987).

             Central Limit Theorem - For large sample sizes the sample means will tend to be normally
                    distributed, regardless of the underlying distribution of the random variable, X.

             Chance cause - a cause for variability of a measurement process that occurs unpredictably,
                    for unknown reasons, and believed to happen by chance (Taylor, 1987).

             Check  standard - in physical calibration, an artifact measured periodically, the results of
                    which typically are plotted on a control chart to evaluate the measurement process
                    (Taylor, 1987).





                                                            35








             Coefficient of Variability - the standard deviation divided by the mean multiplied by 100
                    QN) 100. This is a measure of relative dispersion about the mean and is applicable only
                    when the mean is not equal to zero.

             Coefficient of Variation - the standard deviation divided by the value of the parameter
                    measured (Taylor, 1987).

             Comparability - "expresses the confidence with which one data set, measuring system, or
                    piece of equipment can be compared with another. Data can be considered comparable
                    if they are similar to those reported by others in the literature or if the analysis
                    procedures produce results similar to those of other laboratories from split samples"
                    (Dillaha et al. 1988).

             Completeness - "is a measure of the amount of valid data obtained from a measurement
                    system compared to the amount expected to be obtained under correct normal conditions.
                    For example, analysis of a water sample for total phosphorus will not be complete unless
                    the sample is totally digested. Completeness is usually expressed as a percent of the true
                    value" (Dillaha- et al. 1988).

             Confidence Interval - That range of values, calculated from an estimate of the mean and the
                    standard deviation, which is expected to include the population mean with a stated level
                    of confidence. Confidence intervals in the same context may also be calculated for
                    standard deviations, lines, slopes, and points (Taylor, 1987).

             Confidence Level - "There is a certain probability (1 - ot) that the population mean of a
                    random variable will lie within a certain interval (the confidence interval) about the
                    sample mean." A small confidence interval width indicates a small degree of uncertainty
                    in the estimate of the mean. Similarly, a small confidence interval width indicates that
                    a large amount of information is contained in the estimate of the mean.

             Control Sample - a material of known composition that is analyzed concurrently with test
                    samples to evaluatea measurement process (Taylor, 1987).

             Composite Sample - a sample composed of two or more increments selected to represent a
                    population of interest (Taylor, 1987).

             Data Quality Objectives - data quality is a measure or description of the type and amount of
                    the error associated with a set-of data.


             Detection Limit - the smallest concentration/amount of some component of interest that can
                    be measured by a single measurement with a stated level of confidence (Taylor, 1987).





                                                            36








             Double Blind Sample - a sample known by the submitter but submitted to an analyst in such
                     a way that neither its composition nor its identification as a check sample are known to
                     the latter (Taylor, 1987).

             Duplicate Measurement - a second measurement made on the same (or identical) sample of
                     material to assist in the evaluation of measurement variance (Taylor, 1987).

             Duplicate Sample - a second sample randomly selected from a population of interest to assist
                     in the evaluation of sample variance (Taylor, 1987).

             Error - the difference between the true or expected value and the measured value of a
                     quantity or parameter (Taylor, 1987).

             Frequency distribution - a plot of the number of observations occurring within each of
                     several specified class intervals.

             Holding Time - the length of time a sample can be stored, after collection and preservation
                    . and before preparation and analysis, without significantly affecting the analytical results.

             Homogeneity - the degree to which a property or substance is randomly distributed
                     throughout a material. Homogeneity depends on the size of the subsample under
                     consideration. Thus a mixture of two minerals may be nonhomogeneous at the
                     molecular or atomic level but homogeneous at the particulate level (Taylor, 1987).

             Intercalibration - the process, procedures, and activities used to ensure that the several
                     laboratories engaged in a monitoring program can produce compatible data. When
                     compatible data outputs are achieved and this situation is maintained, the laboratories can
                     be said to be intercalibrated (Taylor, 1987).

             Limiting Mean - the value approached by the average asthe number of measurements made
                     by a stable measurement process increases indefinitely (Taylor, 1987).

             Limit of Linearity (LOL) - the upper limit of concentration or amount of substance for which
                     incremental additions produce constant increments of response (Taylor, 1987).

             Limit of Quantitation (LOQ) - the lower limit of concentration or amount of substance that
                     must be present before a method is considered to provide quantitative results. By
                     convention, LOQ = I Oso, where so is the estimate of the standard deviation at the lowest
                     level of measurement (Taylor, 1987).

             Macroinvertebrates - invertebrates which are large enough to be seen by the unaided eye and
                     which can be retained by a U.S. Standard No. 30 sieve (28 meshes per inch, 0.595 mm
                     openings) and live at least part of their life cycles within or upon available substrates in
                     a body of water or water transport system.


                                                               37








             Map Content Accuracy - determination of whether a map accurately depicts the true situation
                     on the ground. This is determined by ground checking and relating this to a specific
                     statistical reliability (e.g. 95% +/- 3%).

             Map Projection - used to portray all or part of the round earth on a flat surface. This cannot
                     be done without some distortion. It is important to note the map projection when making
                     a map.

             Map Scale - a ratio of distance on the map to the corresponding distance on the ground. For
                     example, a USGS 1:24000 scale map indicates that one unit of measurement on the map
                     is equal to 24000 units of measurement on the ground. So long as the both the
                     numerator and the denominator of the ratio represent the same unit (inches, feet,
                     centimeters) the scale is valid. If different units of measurement are to be used, the
                     appropriate conversion must be made. For example, a map scale 1:24000 measured in
                     inches can be converted to 1 inch on the map is equal to 2,000 feet on the ground.

             Map resolution - this is the smallest unit shown on a map (ie. 1 acre).

             Monotonic - regression (either increasing or decreasing) which goes in one direction, but not
                     in a straight line.

             Outlier - "an observation which deviates so much from other observations as to arouse
                     suspicions that it was generated by a different mechanism" (Magnien et al. 1991).

             Phi Grade Scale - a logarithmic transformation of the Wentworth grade scale for size
                     classifications of sediment grains based on their negative logarithm to the base 2 of the
                     particle diameter. 0=log' d

             Population - a generic term denoting any finite or infinite collection of individual things,
                     objects or events; in the broadest concept, an aggregate determined by some property that
                     distinguishes things that do and do not belong.

             Positional Accuracy - the extent to which the location of features shown on a map accurately
                     reflects their true location. This is determined by field checking against National Map
                     Standards.


             Power - The ability of a statistical test to determine whether the null hypothesis is false Q -
                     fi). The power of a test is the probability of not committing a Type 11 error (p). The
                     more powerful the test, the more likely it is to show, statistically an effect that exists.
                     A Type II error (p) means that we have accepted an invalid null hypothesis. Also, this
                     is called "sensitivity";   the ability of a test to find differences in the data when
                     differences are actually present, the greater the power, the smaller the changes that can
                     be discerned; power is dependent on 1) the variability within the data set, 2) the length
                     of the data set, and 3) the statistical test used (Magnien et al. 1991).


                                                             38








              Precision - "is a measure of the degree of agreement between independent measurements of
                     some property. It is concerned with the closeness of the results and is best expressed in
                     terms of standard deviation" (Dillaha et al. 1988).

              Probability - the likelihood of the occurrence of any particular form of an event, estimated as
                     the ratio of the number of ways or times that the event may occur in that form to the
                     total number of ways that it could occur in any form (Taylor, 1987).

              Probability Function - this is a function that assigns probabilities to the various events in the
                     sample space. This mathematically expresses how probabilities of occurrence are
                     distributed over the possible range of values and can be utilized to estimate the
                     probability that a specified event will or will not occur. Probability density function
                     describe continuous random variables. Probability Mass Function describe discrete
                     random variables.


              Quality - an estimation of acceptability or suitability for a given purpose of an object, item,
                     or tangible or intangible thing.

              Quality Assessment - the overall system of activities whose purpose is to provide assurance
                     that the quality control activities are done effectively. It involves a continuing evaluation
                     of performance of the production system and the quality of the products produced
                     (Taylor, 1987).

              Quality Assurance (QA) - "can be defined as a system of activities designed to assure
                     sponsors, researchers, and other data users that quality control activities are being
                     accomplished and that data of known quality are being generated. Quality assurance is
                     primarily a process of documenting the quality control activities that are being followed.
                     The documentation should be verifiable and defensible" (Dillaha et al. 1988). "The term
                     quality assurance refers to the quality control functions and involves totally integrated
                     program for ensuring the reliability of monitoring data." EPA 1990.

              Quality Control (QC) - "activities include data collection operations which are undertaken in
                     the field and laboratory and in the processing of data to ensure that quality data are being
                     collected which meet the needs of data users. The quality of data can be expressed in
                     terms of its precision, accuracy, representativeness, comparability, and completeness
                     (PARCC)" (Dillaha et al. 1988). "refers to the routine application and procedures for
                     obtaining prescribed standards of performance and for controlling the measurement
                     process (EPA 1990).

              Random sampling - simple      random sampling is a method of selecting n units out of a total
                     population in such a    way that each unit of the population has an equal probability of
                     being selected.

              Reduction - the process of preparing one or more subsamples from a sample (Taylor, 1987).


                                                               39










             Reference material (RM) - a material or substance, one or more properties of which are
                     sufficiently well established to be used for the calibration of an apparatus, the assessment
                     of a measurement method, or for the assignment of values to materials (Taylor, 1987).


             Relative standard deviation - the coefficient of variation expressed as a percentage
                     (coefficient of variation is the standard deviation divided by the value of the parameter
                     measured).

             Replicate Sample - a counterpart of another, usually referring to an analytical sample or a
                     measurement. It is the general case for which duplicate is the special case consisting of
                     two samples or measurements.

             Representativeness - "is a measure of the degree to which data accurately and precisely
                     represent the characteristic of the population which is being monitored. For example,
                     collection and analysis of a single grab sample collected from the surface of a stream will
                     not be representative of the mean sediment concentration of the stream because sediment
                     concentrations in the stream will vary at different places in the cross-section" (Dillaha
                     et al. 1988).

             Robustness - This is a term used by statisticians which means that some of the assumptions
                     about a population can be violated somewhat and the technique can still be used. The
                     assumptions being: 1) independence between observations or groups, 2) the sample
                     means have a normal distribution, (3) and the groups should have nearly equal variances,
                     called homogeneity of variance (Cody and Smith, 1991). "Degree of susceptibility to
                     "false alarms"; the resistance of a test to giving "false" positives, that is saying there
                     is a difference when there is not; robustness is dependent on the statistical test used
                     (Magnien, et al. 199 1).

             Sample - a portion of a population or lot. It may consist of an individual or groups of
                     individuals. It may refer to objects, materials, or measurements, conceivable as part of
                     a larger group that could have been considered (Taylor, 1987).

             Selectivity - the ability of methodology or instrumentation to respond to a desired substance
                     or constituent and not to others.


             Sensitivity - capability of methodology or instrumentation to discriminate between samples
                     having differing concentrations or containing differing amounts of an analyte.

             Serial Correlation - the tendency of an observation to be closely related to those around it.
                     Serial correlation is significant autocorrelation remaining after seasonality and trend are
                     removed.




                                                              40








             Significance level - ct (alpha).

             Skewness - the third statistical moment. The mean divided by the cube of the standard
                    deviation. Skewness is a dimensionless parameter which measures asymmetry of the
                    probability density function.

             Special studies (surveys) - monitoring efforts which have a designated termination data.

             Spiked sample - using a simi   lar analyte (surrogate) or the same analyte (standard addition)
                    are, used to estimate interference bias when expected confidence limits of percent
                    recovery are exceeded.

             Split Sample - a replicate portion or subsample of a total sample obtained in such a manner
                    that it is not believed to differ significantly from other portions of the same sample
                    (Taylor, 1987).

             Standard Deviation - is the square root of the variance.         Describes the distribution of
                    individuals. This is a description of the "spread" of the individuals. The variance or
                    mean square (e or s) is defined in terms of squared deviations.

             Standard Error - is the standard deviation of a mean.


             Stratified Random Sampling - In stratified random sampling the total population is divided
                    into subpopulations referred to a strata. Then, a simple random sample is taken
                    independently from each strata.

             Suspended load sampler - is a sampler which attempts to secure a sample of the water with
                    its sediment load without separating the sediment from the water.

             Systematic Sampling - consists of selecting a unit at random from I to k and then selecting
                    every k" unit thereafter.

             Tolerance Interval - the range of values, calculated from an estimate of the mean and
                    standard deviation, within which a specified percentage of individual values of a
                    population (measurements of sample) are expected to lie with a stated level of confidence
                    (Taylor, 1987).

             Trend - a monotonic change in time, occurring as either an abrupt or a gradual change in
                    concentration.


             Type I Error - the probability of declaring a valid null hypothesis false, referred to as the ce
                    (alpha) level.




                                                           41








            Type II Error - the probability of accepting an invalid null hypothesis, referred to as the
                    (beta) level.

            Uncertainty - the range of values within which the true value is estimated to lie. it is a best
                    estimate of possible inaccuracy due to both random and systematic error.

            Validation - the process by which.a sample, measurement method, or a piece of data is
                    deemed useful for a specified purpose (Taylor, 1987).

            Variance - the value approached by the average of the sum       of the squares of deviations of
                    individual measurements from the limiting mean. The second statistical moment about
                    the mean. A measure of the amount of dispersion about the mean of a population of
                    data. var(x) = s'ln (the population variance is equal to the sample variance divided by
                    the number of observations).



































                                                           42













                                              LITERATURE CITED
                                                DATA ANALYSIS



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                                                        43








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                                                        44








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                                                        45








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                                                         46








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                                                      47













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                                                           48








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                                                        49













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                                                          50











                                                                            I

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                                                          51








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            Ward, R.C., J.C. Loftis, and G.B. McBride. 1990. Design of Water Quality Monitoring
                I  Systems. Van Nostrand Reinhold. New York, New York. 231 pp.

            Ward,  R.C. and J.C. Loftis. 1989. Monitoring systems for water qu,*ity. Critical Reviews
                   in Environmental Control. 19(2):101-118.

            Ward,  R.C., J.C. Loftis, K.S. Nielsen, R.D. Anderson. 1979. Statistical evaluation of
                   sampling frequencies in monitoring networks. Journal of the Water Pollution Control
                   Federation. 51(9):2292-2300.

            Whitfield, P.H. 1988. Goals and data collection designs for water quality monitoring.
                   Water Resources Bulletin. 24(4):775-780.
































                                                        52













                                               LITERATURE CITED
                                  ANALYTICAL METHODS AND PROTOCOLS



             Currie, L. A.    1968.    Limits for qualitative detection and quantitative determination:
                    application to radiochemistry. 40(3):586-593.

             D'Elia, C.F., J.G. Sanders, and       D.G.. Capone..     1989.    Analytical chemistry for
                    environmental scientists:   a question of confidence. Environmental Science and
                    Technology. 23(7):768-774.

             D'Elia, C.F., K.L. Webb, D.V.         Shaw, and C.W. Keefe.         1986.     Methodological
                    Comparisons for Nitrogen and Chlorophyll Determinations in Fstuarine Water Samples.
                    United States Environmental Protection Agency, Chesapeake Bay Program. Annapolis,
                    Maryland.

             Franson, M.A. (ed).       1989.   Standard Methods for the aamination of Water and
                    Wastewater. 17th edition. American Public Health Association, American Water Works
                    Association, and Water Pollution Control Federation. Washington, D.C.

             Hites, R.A. and W.L. Budde.        1991. EPA.'s analytical methods for water: the next
                    generation. Environmental Science and Technology. 25(6):998-1006.

             Horwitz, W.     1982. Evaluation of analytical methods used for regulation of foods and
                    drugs. Analytical Chemistry. 54(l):67-76.

             Keith, L.H. and W.A. Telliard.       1979. Priority Pollutants: I - a perspective view.
                    Environmental Science and Technology. .13(4): 416-423.

             Keith, L.H., W. Crummett, J. Deegan, R.A. Libby, J.K. Taylor, and G. Wender. 1983.
                    Principles of environmental analysis. Analytical Chemistry. 55:2210-2218.

             Magnien, R. 1986. A Comparison of Estuarine Water Chemistry Analysis on the Filtrate
                    ftom two 7ypes of Filters. Maryland Office of Environmental Programs, Ecological
                    Modeling and Analysis Division. Baltimore, Maryland. 12 pp.

             Oppenheimer, L., T.P. Capizzi, R.M. Weppelman, and Hina Mehta. 1983. Determining
                    the lowest limit of reliable assay measurement. Analytical Chemistry. 55:638-643.

             Porter, P.S., R.C. Ward, and H.F. Bell. 1988. The detection limit. Environmental Science
                    and Technology. 22(8):856-861.



                                                          53








            Rogers, L.B. 1986. The inexact imprecise science of trace analysis. Journal of Chemical
                  Education. 63(l):3-6.

            Siegfried, R.C. 1987. Comparison of Preservation Techniques for Organic Carbon Analysis
                  in Estuarine Water Samples. US Environmental Protection Agency, Chesapeake Bay
                  Program. Annapolis, Maryland. CBP/TRS 5/87.

            US EPA. 1982. Methods for Organic Chemical Analysis of Municipal and Industrial
                  Wastewater. United States Environmental Protection Agency. Cincinnati, Ohio. EPA
                  600/4-82-057. NTIS No. PB83-201798.
















































                                                      54













                                               LITERATURE CITED
                                  QUALITY ASSURANCE/QUALITY CONTROL


            Dillaha, T.A., S. Mostaghimi, C.D. Eddleton, and P.W. McClellan. 1988. Quality
                    control/quality assurance for water quality monitoring. A paper presented at the winter
                    meeting of the American Society of Agricultural Engineers. December 13-16, 1988
                    Chicago, Illinois.

            Horowitz, W., L.R. Kamps, and K.W. Boyer. 1980. Quality assurance in the analysis of
                    foods for trace constituents.   Journal of the Association of Analytical Chemists.
                    63(6):1344-1354.

            Taylor, J.K. 1987. Quality Assurance of Chemical Measurements. Lewis Publishers,
                    Chelsea, Michigan. 328pp.

            US EPA. 1980. Interim Guidelines and Specocations' for Preparing Quality Assurance
                    Project Plans. Office of Monitoring Systems and Quality Assurance, Office of Research
                    and Development. Washington, D.C. QAMS-005/80.

            US EPA.       1982. Handbook for Analytical Quality Control in Water and Wastewater
                    Laboratories. United States Environmental Protection Agency. Cincinnati, Ohio. EPA
                    600/4-79-015. NTIS No. PB-297-451.


            US EPA. 1984. Guidance for Preparation of Combined WorklQuality Assurance Project
                    Plans for Environmental Monitoring. United States Environmental Protection Agency,
                    Office of Water Regulations and Standards. Washington, D.C. EPA-OWRS/QA-1.

            US EPA. 1990. Chesapeake Bay Coordinated Split Sample Program Annual Report, 1989.
                    United States Environmental Protection Agency, Chesapeake Bay Program. Annapolis,
                    Maryland. CBP/TRS 51/90.

            US EPA.       1991. Chesapeake Bay Coordinated Split Sample Program Implementation
                    Guidelines - Revision 3. United States Environmental Protection Agency, Chesapeake
                    Bay Program. Annapolis, Maryland. CBP/TRS 58/91.









                                                          55













                                                LITERATURE CITED
                                     FIELD COLLECTION METHODOLOGIES



             Bros, W.E. and B.C. Cowell. 1987. A technique for optimizing sample size (replication).
                    Journal of Experimental Marine Biology and Ecology. 114:63-71.

             Brydon, G.W. and L.R. Smith. 1989. Sampling for environmental analysis: part 1:
                    planning and preparation. American Laboratory. July:30-39.

             Brydon, G.W. and L.R. Smith. 1989. Sampling for environmental analysis: part 2:
                    sampling methodology. American Laboratory. September: 19-24.

             Casey, D., P.N. Nemetz, and D.H. Uyeno. 1983. Sampling frequency for water quality
                    monitoring: measures of effectiveness. Water Resources Research. 19(5): 1107-1110.


             Cowan, C. E. and R. G. Riley. 1987. Guidance for Sampling of and Analyzing for Organic
                    Contaminants in Sediments. Prepared for United States Environmental Protection
                    Agency, Criteria and Standards Division, Washington, D.C.

             Keith, L.H. 1990. Environmental sampling: a summary. Environmental Science and
                    Technology. 24(5):610-617.

             Keith, L.H. 1991. Environmental Sampling and Analysis: A Practical Guide. Lewis
                    Publishers. Chelsea, Michigan.

             Rutherford, J.E. and R.J. Mackay. 1985. The vertical distribution of hydropsychid larvae
                    and pupae (Tricoptera: Hydropsychidae) in stream substrates. Canadian Journal of
                    Zoology. 63:1306-1315.

             Schmitt, C.J. J.L. Zajicek, and M.A. Ribick.           1985.    National pesticide monitoring
                    program: residues of organochlorine chemicals in freshwater fish, 1980-81. Archives
                    of Environmental Contamination and Toxicology. 14:225-260.

             US EPA 1980. Interim Methods for the Swnpling and Analysis of Priority Pollutants in
                    Ssediments and Fish Tissue. Second Edition. Environmental Analysis Section, US
                    Environmental Protection Agency. Washington, D.C.

             US EPA.       1982.    Handbook for Sampling and Sample Preservation of Water and
                    Wastewater. United States Environmental Protection Agency. Cincinnati, Ohio. EPA
                    600/4-82-029. NTIS No. PB83-124503.


                                                           56








           US EPA. 1985. EPA Region III Guidance on Sampling Aquatic Organisms for Tissue
                  Analyses During FY 1986. Environmental Services Division, US Environmental
                  Protection Agency. Washington, D.C.

           VWCB. 1984. Procedures for Collecting and Preserving Samples for Toxic Pollutant
                  Analysis in Water, Sediment, and Fish. Toxics Monitoring Program, Office of
                  Environmental Research and Standards, Virginia Water Control Board. Richmond,
                  Virginia.

           VWCB. 1988. Water Quality Assessment Operating Procedures Manual. Office of Water
                  Resource Management, Virginia Water Control Board. Richmond, Virginia. Revised
                  June, 199 1.

           Welton, J.S. and M. Ladle. 1979. Two sediment trap designs for use in small rivers and
                  streams. Limnol. Oceanogr. 24(3):588-592.































                                                     57













                                               LITERATURE CITED
                                           BIOLOGICAL MONITORING



            Angermeier, P.L. and J.R. Karr. 1986. Applying an index of biotic integrity based on
                    stream-fish communities: considerations in sampling and interpretation. North American
                    Journal of Fisheries Management. 6:418-429.

            Angermeier, P.L. and R.J. Neves. 1987. Project Report:           Virginia Warmwater Strewn
                    Classification and Survey. Project Number: F-47-R. Virginia Polytechnic and State
                    University, Blacksburg, Virginia.

            Angermeier, P.L. and I.J. Schlosser. 1987. Assessing biotic integrity of the fish community
                    in a small Illinois stream. North American Journal of Fisheries Management. 7:331-
                    338.


            Berkman, H.E., C.F. Rabeni, and T.P. Boyle. 1986. Biomonitors of stream quality in
                    agricultural areas: fish versus invertebrates. Environmental Management. 10(3):413-
                    419.


            DGIF.     1991. Endangered Species of Wrginia. (ed. Karen Terwilliger). Virginia
                    Department of Game and Inland Fisheries, Endangered Species Program. Richmond,
                    Virginia.

            Fausch, K.D.,   J. Lyons, J.R. Karr, and P.L Angermeier. 1990. Fish communities as
                    indicators of environmental degradation. American Fisheries Society Symposium.
                    8:123-144.


            Hilsenhoff, W.L. 1987. An improved biotic index of organic stream pollution. The Great
                    Lakes Entomologist. 20(l):31-39.

            Hughes, R. M.      1985.   Use of watershed characteristics to select control streams for
                    estimating effects of metal mining wastes on extensively disturbed streams.
                    Environmental Management. 9(3):253-262.

            Hughes, R.M., D.P. Larsen, and J.M. Omernik. 1986. Regional reference sites: a method
                    for assessing stream potentials. Environmental Management. 10(5):629-635.

            Karr, J. R.   1981.   Assessment of biotic integrity using fish communities.       Fisheries.
                    6(6):21-27.




                                                          58








             Miller, D.L. et seq. 1988. Regional applications of an index of biotic integrity for use in
                    water resource management. Fisheries. 13(5): 12-20.

             Scott, J.B., C.R. Steward, and Q.J. Stober. 1986. Effects of urban development on fish
                    population dynamics in Kelsey Creek, Washington. Transactions of the American
                    Fisheries Society. 115:555-567.

             Steedman, R.J.     1988. Modification and assessment of an index of biotic integrity to
                    quantify stream quality in southern Ontario. Canadian Journal of Fisheries and Aquatic
                    Science. 45:492-501.


             US EPA. 1989. Rapid Bioassessment Protocols for Use in Streams and Rivers. United
                    States Environmental Protection Agency, Assessment and Watershed Protection Division.
                    Washington, D.C. EPA-440-4-89/001.

             US EPA. 1990. Biological Ctiteria: National Program Guidance for Sur ace Waters.
                                                                                            .f
                    United States Environmental Protection Agency, Regulations and Standards Division.
                    Washington, D.C. EPA-440/5-90-004.

             US EPA.      1990. Macroinvertebrate Field and Laboratory Methods for Evaluating the
                    Biological Integrity of Surface Waters. United States Environmental Protection Agency,
                    Office of Research and Development. Washington, D.C. EPA/600/4-90-030.

             Walsh, J.B.S.      1992.    Effects of Timber Harvesting on Benthic Macroinvertebrate
                    Populations in Southwestern Virginia. Virginia Department of Forestry, Charlottesville,
                    Virginia.





















                                                           59












                                               LITERATURE CITED
                       COMPUTER SOFTWARE DOCUMENTATION AND MODELING



            Cody, R.P. and J.K. Smith. 1991. Applied Statistics and the SAS Progrwwning Language.
                    Elsevier Science Publishing Company, New York, New York. 403pp.

            Dortch, M.S., C.F. Cerco, D.L. Robey, H.L. Butler, and B.H. Johnson. 1988. Work plan
                    for three-dimensional time-varying, hydrodynamic and water quality model of
                    Chesapeake Bay. U.S. Army Corps of Engineers. Baltimore, Maryland.

            Engman, E.T. and A.S. Rogowski. 1974. A partial area model for storm flow synthesis.
                    Water Resources Research. 10(3):464-472.

            Freeze, R. A.    1980.   A stochastic-conceptual analysis of rainfall-runoff processes on a
                    hillslope. Water Resources Research. 16(2):391-408.

            Haddad, K.D. and G.A. McGarry. 1989. Basin-wide management: A remote sensing/GlS
                    approach. Coastal Zone 1989. 1822-1836.

            Hession, C. 1989. Geographic information system technology and water quality modeling:
                    an interface. Virginia Department of Conservation and Recreation, Division of Soil and
                    Water Conservation. Richmond, Virginia.

            Hession, C., K.L. Huber, S. Mostaghimi, V.0. Shanholtz, and P.W. McClellan. 1989.
                    BMP effectiveness evaluation using AGNPS and a GIS.             American Society of
                    Agricultural Engineers. Paper Number 89-2566. St. Joseph, Mi.

            Johnson, L.E.     1989. MAPHYD - a digital map-based hydrologic modeling system.
                    Photogrammetric Engineering and Remote Sensing. 55(6):911-917.

            Loftis, J.C., R.D. Phillips, R.C. Ward, and C.H. Taylor. 1989. WQSTAT II: a water
                    quality statistics package. Groundwater. 27(6):866-873.

            Reardon, J.C., L.D.Hanson, and J. Randolph. 1982. Using EPA's computerized data base
                    (STORET) to analyze for agricultural water pollution. Journal of Environmental Quality.
                    11(3):427-432.

            Shanholtz, V.0. and N. Zhang. 1989. GIS/hydrologic model interface for local planning
                    jurisdictions. American Society of Agricultural Engineers. Paper Number 89-2562. St.
                    Joseph, Mi.



                                                          60








            Shanholtz, V.0. and N. Zhang. 1989. Hydrologic modeling system for Northern Neck
                    Planning District. ISSL Report No. 100. Virginia Tech, Department of Agriculture
                    Engineering. Blacksburg, Virginia.

            Shanholtz, V.0. N. Zhang, E.R. Yagow, C.J. Desai, and J.M. Flagg. 1988. The use of a
                    GIS to track the impact of Virginia Chesapeake Bay Agricultural Nonpoint Source
                    Program. American Society of Agricultural Engineers. Paper Number 88-2535. St.
                    Joseph, Mi.

            Shanholtz, V.0., C.J. Desai, N. Zhang, J.W. Kleene, C.D. Metz, and J.M. Flagg. 1990.
                    Hydrologic/water quality modeling in a GIS environment.         American Society of
                    Agricultural'Engineers. Paper Number 90-3033. St. Joseph, Mi.

            USDA-SCS. 1986. Urban Hydrology for Small Watersheds, Technical Release 55, User's
                    Guide. United States Department.of Agriculture, Soil Conservation Service, Engineering
                    Division. Washington, D.C. 210-VI-TR-55, 2nd Edition.

            USDA-SEA. 1978. Predicting rainfall erosion losses: a guide to conservation planning.
                    United States Department of Agriculture, Science and Education Administration.
                    Washington, D. C.

            US EPA. 1991. Nonpoint Source Management System, NPSMS Version 3, User's Guide.
                    United States Environmental Protection Agency, Assessment and Watershed Protection
                    Division, Office of Wetlands, Oceans, and Watersheds, Nonpoint Source Management
                    Branch. Washington, D.C. Prepared under EPA Contract 68-C9-0013.

            US EPA. STORET - Basic Seminar Documentation. United States Environmental Protection
                    Agency. Washington, D.C.

            US EPA. STORET - Advanced Seminar Documentation. United States Environmental
                    Protection Agency. Washington, D.C.















                                                          61












                                               LITERATURE CITED
                                       BEST MANAGEMENT PRACTICE'S



            Barton, D.R., W.D. Taylor, and R.M. Biette. 1985. Dimensions of riparian buffer strips
                    required to maintain trout habitat in southern Ontario streams. North American Journal
                    of Fisheries Management. 5:364-378.

            CBLAD. 1989. Local Assistance Manual: A Guide for the Development of Local Programs
                    in Order to Comply with the Chesapeake Bay Preservation Act. Chesapeake Bay Local
                    Assistance Department. Richmond, Virginia.

            VADCR. 1990. Virginia Stormwater Management Regulations. Virginia Department of
                    Conservation and Recreation, Division of Soil and Water Conservation. Richmond,
                    Virginia.

            VADCR.     '1991. Virginia Erosion and Sediment Control Regulations. Virginia Department
                    of Conservation and Recreation, Division of Soil and Water Conservation. Richmond,
                    Virginia.

            VADCR. 1992. Virginia Erosion and Sediment Control Law. Virginia Department of
                    Conservation and Recreation, Division of Soil and Water Conservation. Richmond,
                    Virginia.

            VDOF. 1988. Loggers Guide: Save Money, Time, and Improve Water Quality. Virginia
                    Department of Forestry. Charlottesville, Virginia.

            VDOF. 1989. Forestry Best Management Practices for Water Quality in Virginia.
                    Virginia Department of Forestry. Charlottesville, Virginia. 76 pp.















                                                          62













                                        LITERATURE CITED
                                          CARTOGRAPHY



           Monmonier, M.S. 1977. Maps, Distortion, and Meaning. Association of American
                 Geographers. Resource Paper No. 75-4. Washington, D.C. 51 pp.

           Muehrcke, P.C. 1978. Map Use: Reading, Analysis, and Interpretation. JP Publications,
                 Madison, Wisconsin. 474 pp.



































                                                 63









                                                                                                                                     NOAA COASTAL SERVICES CTR LIBRARY



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