APPENDIX D
Model Reviews

WATERSHED MODELS

Although some purely hydrologic and hydraulic models (e.g., those by the U.S. Army Corps of Engineers, Hydrologic Engineering Center) might contribute to analysis of nonpoint source water quality in watersheds, only models with an explicit water quality simulation capability are described herein, and more specifically, the models must be capable of simulating nutrient loadings. Some reviews of models are available, although their usefulness diminishes with time since publication due to the dynamic nature of model changes. Reviews of process models for simulation of nonpoint source water quality include those by Donigian and Huber (1991), DeVries and Hromadka (1993), Novotny and Olem (1994), Donigian et al. (1995), Singh (1995), the Environmental Protection Agency (EPA 1997), and Deliman et al. (1999). The references given in the discussion that follows are unlikely to be the best source of information about the latest model capabilities. The best approach is usually to find the webpage for the agency that distributes the model and obtain the most current information in that manner. URLs as of the time of publication of this document are provided in Appendix E. Discussion groups exist on the Internet for some of the models as well.



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution APPENDIX D Model Reviews WATERSHED MODELS Although some purely hydrologic and hydraulic models (e.g., those by the U.S. Army Corps of Engineers, Hydrologic Engineering Center) might contribute to analysis of nonpoint source water quality in watersheds, only models with an explicit water quality simulation capability are described herein, and more specifically, the models must be capable of simulating nutrient loadings. Some reviews of models are available, although their usefulness diminishes with time since publication due to the dynamic nature of model changes. Reviews of process models for simulation of nonpoint source water quality include those by Donigian and Huber (1991), DeVries and Hromadka (1993), Novotny and Olem (1994), Donigian et al. (1995), Singh (1995), the Environmental Protection Agency (EPA 1997), and Deliman et al. (1999). The references given in the discussion that follows are unlikely to be the best source of information about the latest model capabilities. The best approach is usually to find the webpage for the agency that distributes the model and obtain the most current information in that manner. URLs as of the time of publication of this document are provided in Appendix E. Discussion groups exist on the Internet for some of the models as well.

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution PROCESS MODELS Non-Urban Watersheds With few exceptions, simulation models sponsored by federal government organizations dominate the non-urban watershed environment. AGNPS−Agricultural Nonpoint Source Pollution Model (Young et al. 1994) The model was developed by the U.S. Department of Agriculture’s (USDA) Agricultural Research Service. The primary emphasis of the model is on nutrients, soil erosion, and sediment yield for comparing the effects of various best management practices on agricultural pollutant loadings. The AGNPS model can simulate sediment and nutrient loads from agricultural watersheds for a single storm event or for a continuous simulation. The watershed must be divided into a uniform grid (square cells). The cells are grouped by dividing the basin into subwatersheds. However, water flow and pollutant routing is accomplished by a function of the unit hydrograph type, which is a lumped parameter approach. The model does not simulate pesticides. AGNPS is also capable of simulating point inputs such as feedlots, wastewater discharges, and stream bank and gully erosion. In the model, pollutants are routed from the top of the watershed to the watershed outlet in a series of steps. The modified universal soil erosion equation is used for predicting soil loss in five different particle sizes (clay, silt, sand, small aggregates, and large aggregates). The pollutant transport portion is subdivided into one part handling soluble pollutants and another part handling sediment absorbed pollutants. The input data requirements are extensive, but most of the data can be retrieved from topographic and soil maps, local meteorological information, field observations, and various publications, tables, and graphs provided in the user manual or references. ANSWERS−Areal, Nonpoint Source Watershed Environment Response Simulation (Beasley and Huggins 1981) The model was developed by the Agricultural Engineering Department of Purdue University. It is a distributed parameter model designed to simulate rainfall-runoff events. Currently the model is maintained and distributed by the Agricultural Engineering Department, University of Georgia, Tifton, Georgia. To use the ANSWERS model, the watershed is divided into a uniform grid (square elements). The element may range from one to four hectares. Within each element the model simulates the

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution processes of interception, infiltration, surface storage, surface flow, subsurface drainage, sediment detachment, and movement across the element. The output from one element then becomes a source of input to an adjacent element. Nutrients (nitrogen and phosphorus) are simulated using correlation relationships between chemical concentrations, sediment yield, and runoff volume. Snowmelt or pesticides movement cannot be simulated. A single storm rainfall hyetograph drives the model. BASINS−Better Assessment Science Integrating Point and Nonpoint Sources (Lahlou et al. 1998) This model is a multipurpose environmental analysis system for use by regional, state, and local agencies in performing watershed and water quality based studies. It was developed by EPA to address three objectives: To facilitate examination of environmental information To support analysis of environmental systems To provide a framework for examining management alternatives A geographic information system (GIS) based on ArcView provides the integrating framework for BASINS. GIS organizes spatial information so it can be displayed as maps, tables, or graphics. Through the use of GIS, BASINS has the ability to display and integrate a wide range of information (e.g., land use, point source discharges, water supply with-drawals) at a scale selected by the user. For example, some users may need to examine data at a state scale to determine problem areas, compare watersheds, or investigate gaps in data. Others may want to work at a much smaller scale, such as investigating a particular river segment. These features makes BASINS a unique environmental analysis tool. The analytical tools in BASINS are organized into two modules. The assessment and planning module, working within GIS, allow users to quickly evaluate selected areas, organize information, and display results. The modeling module allows users to examine the impacts of pollutant loadings from point and nonpoint sources. The modeling module includes the following: QUAL2E, Version 3.2, a water quality and eutrophication model; TOXIROUTE, a model for routing pollutants through a stream system; NPSM-HSPF, version 10, a nonpoint source model for estimating loadings. The latest versions of both QUAL2E and Hydrologic Simulation Program-FORTRAN (HSPF) are included in the BASINS package.

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution CREAMS−Chemicals, Runoff, and Erosion from Agricultural Management Systems (Knisel 1980) and GLEAMS−Groundwater Loading Effects of Agricultural Management Systems (Knisel 1993) CREAMS is a field-scale model for evaluation of agricultural best management practices (BMPs) for pollution control. Daily erosion, sediment yield, and associated nutrient and pollutant loads are estimated at the boundary of the agricultural area. Runoff estimates are based on the Soil Conservation Service (SCS) method. The vertical flux of nutrients and pesticides in the root zone may be simulated using GLEAMS in order to provide a groundwater component to off-site loadings. Both CREAMS and GLEAMS are maintained by USDA Agricultural Research Service. HSPF−Hydrologic Simulation Program-FORTRAN (Bicknell et al. 1993) HSPF is a simulation model developed under EPA sponsorship to simulate hydrologic and water quality processes in natural and man-made water systems. It is an analytical tool that has application in planning, design, and operation of water resources systems. The model enables the use of probabilistic analysis in the fields of hydrology and water quality management through its continuous simulation capability. It uses such information as time history of rainfall, temperature, evaporation, and parameters related to land use patterns, soil characteristics, and agricultural practices to simulate the processes that occur in a watershed. The initial result of an HSPF simulation is a time history of the quantity of water transported over the land surface and through various soil zones down to the groundwater aquifer. Runoff flow rate, sediment loads, nutrients, pesticides, toxic chemicals, and other water quality constituent concentrations can be predicted. The model can simulate continuous, dynamic, or steady state behavior of both hydrologic/hydraulic and water quality processes in a watershed. HSPF also may be applied to urban watersheds through its impervious land module. SWRRB−Simulator for Water Resources in Rural Basins (Arnold and Williams 1994) and SWAT−Soil and Water Assessment Tool (Arnold et al. 1995) The SWRRB model was developed for large, complex, rural basins through modifications to the CREAMS model for simulation of daily-time-step hydrology, nutrient and other loads. Similarly, SWAT is an extension of SWRRB from small watershed scale to basin scale. SCS hydrology techniques are modified to allow for agricultural return flow and flow through the root zone. Nitrogen and phosphorus computations are based on regression relationships between chemical concentration,

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution sediment yield and runoff volume. Both nitrate and organic nitrogen may be simulated for different soil layers. Both models are maintained by USDA’s Agricultural Research Service. WARMF−Watershed Analysis Risk Management Framework (EPRI 1998) The Electric Power Research Institute (EPRI) has sponsored model development specifically for the purpose of developing Total Maximum Daily Loads (TMDLs) in accordance with EPA water quality regulations. The models embedded in WARMF draw upon other simulation models described herein, including ANSWERS and SWMM. Nonpoint loads are generated on the basis of land use and other data in a GIS format, coupled with simplified hydrologic techniques, but with complete coverage of the hydrologic cycle. Erosion processes are included in land runoff modules, as are integrated water quality fate and transport processes in riverine segments. Because point source loads are also included, the model may be executed in an iterative fashion to determine TMDL allocations. Urban Watersheds Perhaps more so than for non-urban watersheds, process-type simulation models for urban watersheds include a number of non-proprietary, mostly governmentally-sponsored models, plus a few frequently used proprietary private models (Table D-1). However, the discussion that follows describes only models sponsored by a federal agency, since these represent the bulk of the models used in practice. Information on other models may be found from their websites (Appendix E). DR3M-QUAL−Distributed Routing, Rainfall, Runoff Model-Quality (Alley and Smith 1982) This model developed by the U.S. Geological Survey (USGS) includes a quality simulation routine coupled to its earlier DR3M model. Runoff generation and subsequent routing is based on the kinematic wave method. Quality generation is based on buildup and washoff functions. The model may be used for single-event or long-term (continuous) simulation of hydrographs and quality constituents. STORM−Storage, Treatment, Overflow Runoff Model (HEC 1977) This model was developed by the U.S. Army Corps of Engineers, Hydrologic Engineering Center (HEC) for simplified long-term analysis (continuous simulation) of runoff from urban areas. The model addresses

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution TABLE D-1 Model Agency/Source Primarily Hydrology/Hydraulics Continuous Simulation or Storm Event Complete Dynamic Flow Routing? Graphical User Interface DR3M-QUAL USGS Hydrology CS/SE No ANNIE HSPF EPA Hydrology CS/SE No ANNIE, 3rd party Hydroworks HR Wallingford in the United Kingdom, Montgom. Watson in the United States. Hydrology/ Hydraulics CS/SE Yes Yes MOUSE Danish Hydraulic Institute Hydrology/ Hydraulics CS/SE Yes Yes P8 Wiiliam Walker, Jr. Hydrology CS/SE No Menu STORM HEC/Vendors Hydrology CS No 3rd party SWMM EPA/OSU Hydrology/ Hydraulics CS/SE Yes 3rd party TABLE D-1 Nonpoint source water quality simulation models commonly applied to urban watersheds in the United States.

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution combined sewer overflows (CSOs) in particular, although it may also be used to simulate stormwater runoff quantity and quality. Hydrologic methods utilize a simple runoff coefficient and depression storage for hourly time steps. Water quality loads are estimated on the basis of buildup and washoff functions. The trade-off between treatment and storage options at the catchment outlet may be evaluated for economic optimization of control strategies. The model is no longer supported by HEC, but is available from private vendors with an enhanced graphic user interface. SWMM−Storm Water Management Model (Huber and Dickinson 1988; Roesner et al. 1988) The SWMM model was originally developed by EPA as a simulation model for the quantity and quality of CSOs. However, it has been widely used for hydrologic, hydraulic and water quality analysis for urban stormwater and some non-urban applications as well. Runoff is generated on a single-event or continuous basis using nonlinear reservoir methods and Horton or Green-Ampt loss functions. Flow routing options range from simple to complete solution of the Saint-Venant equations in the Extran Block. Simulation of nonpoint source runoff quality may be performed by several options, including constant concentrations, regression methods and buildup and washoff functions. Quality routing and treatment processes may also be performed. SPREADSHEET MODELS A “spreadsheet model” is basically a generic category in which water quality predictions are based on unit loads (e.g., kg ha day−1) or event mean concentrations, as a function primarily of land use, although other factors such as delivery ratios and effects of best management practices may be incorporated. Numerous ad hoc models have been generated in this category for application to both urban and non-urban settings. STATISTICAL APPROACHES Non-Urban Watersheds SPARROW−USGS’s Spatially Referenced Regressions on Watershed Attributes Model (Smith et al. 1997; Preston et al. 1998) A highly sophisticated regression procedure based on spatially-referenced land use and stream channel characteristics has been devel-

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution oped by the USGS for prediction of total nitrogen and total phosphorus loads (kg day−1) at the outlet of major U.S. watersheds. Independent variables for nitrogen prediction include load-related parameters such as point source loads, fertilizer application, livestock waste production, and atmospheric deposition, plus factors such as temperature, soil permeability, and stream density. Coefficients of determination are 0.87 and 0.81 for TN and TP load prediction for the conterminous United States, respectively, based on data from 414 National Stream Quality Accounting Network stream monitoring stations. The regression is based on land use data from 78,000 soil geographic units. An application for the determination of total nitrogen in the Chesapeake Bay watershed (Preston et al. 1998) indicated areas that are most important to the delivery of nutrients to the bay, mainly those that drain directly to large streams or those that are near the bay. Urban Watersheds EPA’s Statistical Method (EPA 1983; Driscoll et al. 1989) This method was adopted for the EPA’s Nationwide Urban Runoff Program (NURP) and later refined in an investigation of highway runoff quality for the Federal Highway Administration. A derived-distribution technique is used to derive the lognormal distribution of event mean concentrations from urban sites. This is a considerable improvement over the simpler, constant concentration approach using a constant event mean concentration (EMC) because the frequency distribution is provided, which in turn may be used to simulate receiving water loadings. USGS’s Regression Models (Driver and Tasker 1990) All of the EPA’s NURP data were combined with some other urban stormwater quality data by the USGS to develop a set of regression equations for estimation of EMC and loads. The equations were developed for three different hydrologic zones of the United States and utilize commonly available watershed characteristics as independent variables. If a single EMC or loading value is needed, this work remains the only comprehensive synthesis of thousands of samples of stormwater runoff from urban watersheds. In the more than 16 years since NURP studies ended, thousands of urban runoff sites have been sampled as part of EPA’s NPDES requirements. The USGS study should be updated to reflect these abundant newer and more spatially diverse data. Once again, printed summaries of receiving water models tend to rapidly become outdated. However, useful background information may

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution be obtained from: Ambrose et al. (1988, 1996), Bouchard et al. (1994), Barnwell et al. (1995), EPA (1997), Rauch et al. (1998), Shanahan et al. (1998), and Somlyody et al. (1998). Much more current information may often be gleaned from Oregon State University (1999) and USGS (1999b). ESTUARINE AND COASTAL EUTROPHICATION MODELS As with the preceding watershed models, eutrophication models for receiving waters, both estuaries and the coastal ocean, come in a variety of forms. These include desktop screening models, steady state and tidally averaged models, and dynamic simulation models. The degree of complexity and the computer and personnel resources necessary to use each effectively are highly variable. Much of the following information follows from the earlier work of the EPA (1990). Desktop Screening Models Desktop screening methodologies may be utilized with a hand-held calculator or computer spreadsheet and are based on steady state conditions, first order decay coefficients, simplified estimates of flushing time, and seasonal pollutant concentrations. The Water Quality Assessment Methodology (WQAM) provides a series of such analyses. WQAM−Water Quality Assessment Methodology (Mills et al. 1985) WQAM is a set of steady state desktop models that includes both one-dimensional and two-dimensional box model calculations. Specific techniques contained in WQAM are the Fraction of Freshwater Method, the Modified Tidal Prism Method, Advection-Dispersion equations, and Pritchard’s two-dimensional box model. Steady State and Tidally Averaged Steady state and tidally averaged simulation models generally use a box or compartment-type network and are difficult to calibrate in situations where hydrodynamics and pollutant releases are rapidly varying. Consequently, they are less appropriate when waste load, river inflow, or tidal range vary appreciably with a period close to the flushing time of the waterbody. These are the simplest models available that are capable of describing the relationship between nutrient loads and some of the endpoints of concern of the eutrophication process (i.e., chlorophyll, minimum dissolved oxygen).

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution QUAL2E (EPA 1995) QUAL2E is a steady state, one-dimensional model designed for simulating conventional pollutants in streams and well-mixed lakes. It has been applied to tidal rivers with minor adaptations to the hydraulic geometry and dispersion functions. Water quality variables simulated include conservative substances, temperature, biochemical oxygen demand (BOD), dissolved oxygen (DO), ammonia, nitrite, nitrate, organic nitrogen, phosphate and organic phosphorus, and algae. It simulates the major reactions of nutrient cycles, algal production, benthic and carbonaceous demand, atmospheric reaeration and their effects on the DO balance. It is applicable to well mixed, dendritic streams. It also has the capability to compute required dilution flows for flow augmentation to meet any prescribed DO level. QUAL2E is widely used for stream waste load allocations and discharge permit determinations in the United States and other countries. WASP5 (Ambrose et al. 1993) WASP5 is a general, multi-dimensional model that utilizes box modeling techniques. The equations solved by WASP5 are based on the principle of conservation of mass. Operated in the quasi-dynamic mode, WASP5 requires the user to supply initial box volumes, network flow fields, and inflow time functions. The user also must calibrate dispersion coefficients between boxes. WASP5 has the capability of simulating nutrient-related water quality issues at a wide range of complexity. EUTRO5 is the submodel in the WASP5 system that is designed to simulate conventional pollutants. It predicts DO, carbonaceous BOD, phytoplankton carbon and chlorophyll a, ammonia, nitrate, organic nitrogen, organic phosphorus, and orthophosphate in the water column and, if specified, the underlying bed. Dynamic Simulation Models of One or More Dimensions Numerical one-dimensional and two-dimensional models that simulate variations in tidal height and velocity throughout each tidal cycle enable the characterization of phenomena varying rapidly within each tidal cycle, such as pollutant spills, stormwater runoff, and batch discharges. They also are deemed appropriate for systems where the tidal boundary impact is important to the modeled system within a tidal period. The application of tidally varying (intratidal) models has found most use in the analysis of short-term events, in which the model simulates a period of time from one tidal cycle to a month. Some seasonal simulations have also been conducted.

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution WASP5 (Ambrose et al. 1993) WASP5 may be operated in the tidal dynamic mode through linkage with the associated hydrodynamic model DYNHYD5, which is a link-node model that may be driven by either constantly repetitive or variable tides. Unsteady inflows may be specified, as well as wind that varies in speed and direction. DYNHYD5 is best suited for one-dimensional longitudinal simulations, but has also been applied in two-dimensional mode to evaluate lateral variations in estuarine water quality. DYNHYD5 is not suited for systems with significant vertical stratification. There is, though, no reason to prevent the WASP5 eutrophication sub-model, EUTRO5, from being linked to a more complex hydrodynamic model than is supplied with WASP5 (see below). In numerical two-dimensional and three-dimensional dynamic simulation models, dispersive mixing and seaward boundary exchanges are treated more realistically than in one-dimensional models. While not routinely used in nutrient analyses, they are now finding use by experts in special studies. CE-QUAL-W2 (Environmental and Hydraulics Laboratories 1986) CE-QUAL-W2 is a dynamic two-dimensional (x-z) model developed for stratified waterbodies. This is a Corps of Engineers modification of the Laterally Averaged Reservoir Model (Edinger and Buchak 1983; Buchak and Edinger 1984a, b). CE-QUAL-W2 consists of directly coupled hydrodynamic and water quality transport models. Hydrodynamic computations are influenced by variable water density caused by temperature, salinity, and dissolved and suspended solids. CE-QUAL-W2 simulates as many as 20 other water quality variables. Primary physical processes included are surface heat transfer, shortwave and longwave radiation and penetration, convective mixing, wind and flow induced mixing, entrainment of ambient water by pumped-storage inflows, inflow density current placement, selective withdrawal, and density stratification as impacted by temperature and dissolved and suspended solids. Major chemical and biological processes in CE-QUAL-W2 include: effects on DO of atmospheric exchange, photosynthesis, respiration, organic matter decomposition, nitrification, and chemical oxidation of reduced substances; uptake, excretion, and regeneration of phosphorus and nitrogen and nitrification-denitrification under aerobic and anaerobic conditions; carbon cycling and alkalinity-pH-CO2 interactions; trophic relationships for total phytoplankton; accumulation and decomposition of detritus and organic sediment; and coliform bacteria mortality.

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution MIKE3 MIKE3 is a three-dimensional, time-dependent, free surface model with wetting and drying of shoals. It is maintained and marketed by the Danish Hydraulic Institute. It offers two different hydrodynamic engines. The first of these assumes a hydrostatic pressure distribution and solves the equations of motion on a sigma-coordinate grid. The second involves a non-hydrostatic formulation and solution on a z-level coordinate grid. Nested grids are allowed. Numerous turbulence closure schemes may be selected. The hydrodynamic model can be coupled to a water quality module, which focuses on dissolved oxygen, organic matter, ammonia, nitrate, phosphorus, bacteria, and chlorophyll a. It can also be coupled to a eutrophication model that includes carbon and nutrient cycling, phytoplankton and zooplankton growth, oxygen balance, and benthic vegetation. The Danish Hydraulic Institute also markets one and two-dimensional coupled hydrodynamic and water quality models, MIKE11 and MIKE21 (Warren and Bach 1992). ECOM/*EM Hydroqual, Inc. has produced a series of similar models based on ECOMsi, a three-dimensional, free surface, finite difference, hydrodynamic code based on the community Princeton Ocean Model (Blumberg and Mellor 1987), and eutrophication code based on the EUTRO code contained within WASP5 (Hydroqual, Inc. 1998). These models include, among others, Bays Eutrophication Model (applied to Massachusetts and Cape Cod Bays), and System-Wide Eutrophication Model (applied to the New York Apex and adjacent estuaries). The models allow for wetting and drying during a tidal cycle and contain various options for the turbulence closure in both the vertical and horizontal dimensions. The eutrophication code involves 25 state variables. These include different classes of phytoplankton, as well as both refractive and labile particulate and dissolved organic matter. CH3D-ICM CH3D-ICM is a linkage of CH3D, a hydrodynamic model, and CE-QUAL-ICM, a water quality model. CH3D is a three-dimensional, finite difference hydrodynamic model developed by Peter Sheng, recently modified for the Chesapeake Bay Program (Johnson et al. 1993), and maintained by the U.S. Army Corps of Engineers’ Waterways Experiment Station in Vicksburg, Mississippi. The model can be used to predict system response to water levels, flow velocities, salinities, temperatures, and the three-dimensional velocity field. CH3D makes hydrodynamic

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution computations on a curvilinear or boundary-fitted planform grid. Deep navigation channels and irregular shorelines can be modeled because of the boundary-fitted coordinates feature. Vertical turbulence is predicted by the model, and is crucial to a successful simulation of stratification, destratification, and anoxia. A second-order model based upon the assumption of local equilibrium of turbulence is employed. ICM is an unstructured finite volume water quality model that may be applied to most waterbodies in one, two, or three dimensions (Cerco and Cole 1995) by readily linking it to any type of hydrodynamic model. The model predicts time-varying concentrations of water quality constituents and includes advective and dispersive transport. The model contains detailed eutrophication kinetics, modeling the carbon, nitrogen, phosphorus, silica, and dissolved oxygen cycles. The model also considers sediment diagenesis and benthic exchange interactions among state variables are described in 80 partial-differential equations that employ over 140 parameters. EFDC−Environmental Fluid Dynamics Code (Hamrick 1996) EFDC is a linked three-dimensional, finite difference hydrodynamic and water quality model developed at the Virginia Institute of Marine Sciences. EFDC contains extensive water quality capabilities, including a eutrophication framework based upon the ICM model. EFDC is a general-purpose hydrodynamic and transport model that simulates tidal, density, and wind-driven flow; salinity; temperature; and sediment transport. Two built-in, full-coupled water quality/eutrophication sub-models are included in the code. EFDC solves the vertically hydrostatic, free-surface, variable-density, turbulent-averaged equations of motion and transport; and transport equations for turbulence intensity and length scale, salinity, and temperature in a stretched, vertical coordinate system; and in horizontal coordinate systems that may be Cartesian or curvilinear-orthogonal. Equations describing the transport of suspended sediment, toxic contaminants, and water quality state variables are also solved. Further information is available for some models at websites (Appendix E). The important features of these models are summarized in Tables D-2 and D-3. The information provided in these tables is primarily qualitative and sufficient to determine whether a model may be suitable for a particular application. For complete information, the potential user must consult the appropriate user’s manuals, the supporting agency, and other experienced users.

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution TABLE D-2 Model Time Scales Spatial Dimensions Hydro-dynamics Data Expertise Requirements Supporting Agency Scale of Effort Fraction of Freshwater SS 1D 0 Minimal EPA Days Modified Tidal Prism SS 1D 0 Minimal EPA Days Advection-Dispersion Equations SS 1D 0 Minimal EPA Days Pritchard’s 2-D Box Model SS 2D (xz) 0 Minimal EPA Days QUAL2E SS 1D I Moderate EPA Few months WASP5 Q/D 1D, 2D (xy), or 3D I, S Moderate to substantial EPA Few months CE-QUAL-W2 D 2D (xz) S Substantial U.S. Army Corps of Engineers Several months MIKE 3 D 3D S Extreme Danish Hydraulic Institute Several months ECOMsi/*EM D 3D S Extreme Hydoqual, Inc. Several months CH3D-ICM D 3D S Extreme U.S. Army Corps of Engineers Several months EFDC D 3D S Extreme None Several months D = dynamic Q = quasi-dynamic (tidal-averaged) SS = steady state xy = two-dimensional, longitudinal-lateral xz = two-dimensional, longitudinal-vertical 0 = no hydraulics specified, inferred from salinity data I = hydrodynamics input S = hydrodynamics simulated TABLE D-2 Summary of selected estuarine water quality model characteristics.

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution TABLE D-3 Model Key Features Advantages Disadvantages/ Limitations WQAM Simplified equations to simulate dilution, advection, dispersion, first-order decay, empirical relationships between nutrient loading, and total nutrientconcentration. Few data requirements; can be easily applied with a hand calculator or computer spreadsheet. Limited to screening-and mid-level applications. QUAL2E Steady-state model provides detailed simulation of water quality processes, including dissolved oxygen, biological oxygen demand, and algal growth cycles. User-friendly Windows interface, which is widely used and accepted. Able to simulate all of the conventional pollutants of concern. Limited to simulation of time periods during which stream flow and input loads are essentially constant. WASP5 Based on flexible compartment modeling approach; can be applied in one, two, or three dimensions. Has been widely applied to estuarine situations. Considers comprehensive dissolved oxygen and algal processes. Can be used in three-dimensional simulations by linking with hydrodynamic models. Coupling with multi-dimensional hydrodynamic models requires extensive site-specific linkage efforts. CE-QUAL-W2 Uses an implicit approach to solve equations of continuity and momentum. Simulates variations in water quality in the longitudinal and lateral directions. Able to simulate the onset and breakdown of vertical stratification. Most appropriate model for cases where vertical variations are an important water quality consideration. Application requires extensive modeling experience.

OCR for page 376
Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution MIKE 3 Finite difference model for use in three dimensions. Predicts time-varying concentrations of constituents, including advective and dispersive transport. Pre-and post-processing software that is user-friendly. Multiple turbulence closure schemes. Computationally intensive. Requires extensive data for calibration and verification. Restricted set of state variables in water quality code. No access to source code. ECOMsi/*EM Finite difference model for use in three dimensions. Predicts time-varying concentrations of constituents, including advective and dispersive transport. State-of-the-science eutrophication kinetics. Multiple turbulence closure schemes. Computationally intensive. Requires extensive data for calibration and verification. Requires a high level of technical expertise to apply effectively. Limited access to sourcecode. CH3D-ICM Finite difference model can be applied to most water bodies in one to three dimensions. Predicts time-varying concentrations of constituents, including advective and dispersive transport. State-of- the- science eutrophication kinetics. Computationally intensive. Requires extensive data for calibration and verification and a high level of technical expertise to apply effectively. EFDC Linked three-dimensional, finite difference hydro-dynamic, and water quality model contains extensive water quality capabilities. Water quality concentrations can be predicted in a variety of formats suitable for analysis and plotting. Able to provide three-dimensional description of water quality parameters of concern. The entire range of hydrodynamic, sediment, eutrophication, and toxic chemical constituents can be considered. Computationally intensive. Requires extensive data for calibration and verification and a high level of technical expertise to apply effectively. TABLE D-3 Key features of selected estuarine water quality models.