Analytical and Sampling Tools
The Water Quality Analysis Simulation Program (WASP6), an enhancement of the original WASP (Di Toro et al., 1983; Connolly and Winfield,1984; Ambrose, R.B. et al.,1988). This model helps users interpret and predict water quality responses to natural phenomena and man-made pollution for various pollution management decisions. WASP6 is a dynamic compartment-modeling program for aquatic systems, including both the water column and the underlying benthos. WASP allows the user to investigate 1, 2, and 3 dimensional systems, and a variety of pollutant types. The time-varying processes of advection, dispersion, point and diffuse mass loading and boundary exchange are represented in the model. WASP also can be linked with hydrodynamic and sediment transport models that can provide flows, depths, velocities, and temperature, salinity and sediment fluxes.
WASP has been used to examine eutrophication of reservoirs, bays, estuaries, and rivers across the country; phosphorus loadings in lakes; and PCB pollution in the Great Lakes. Specifically, researchers have used WASP to investigate kepone pollution and volatile organic pollution in Mid-Atlantic estuaries, as well as heavy metal pollution and mercury in rivers. WASP is also routinely used for TMDL determinations and waste load allocations.
Model Contact Information: |
Tim Wool |
Model Homepage: |
http://www.epa.gov/athens/wwqtsc |
The Soil and Water Assessment Tool (SWAT), is a river basin, or watershed, scale model developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use and management conditions over long periods of time. It is a continuous time model (i.e., a long-term yield model and is not designed to simulate detailed, single-event flood routing). To satisfy these objectives, the model is physically based. Rather than incorporating regression equations to describe the relationship between input and output variables, SWAT requires specific information about weather, soil properties, topography, vegetation, and land management practices occurring in the watershed. The physical processes associated with water movement, sediment movement, crop growth, nutrient cycling, etc. are directly modeled by SWAT using this input data. Benefits of this approach are:
- Watersheds with no monitoring data (e.g. stream gage data) can be modeled
- The relative impact of alternative input data (e.g., changes in management practices, climate, vegetation, etc.) on water quality or other variables of interest can be quantified.
Some additional attributes of SWAT are that it:
- Uses readily available inputs. While SWAT can be used to study more specialized processes such as bacteria transport, the minimum data required to make a run are commonly available from government agencies.
- Is computationally efficient. Simulation of very large basins or a variety of management strategies can be performed without excessive investment of time or money.
- Enables users to study long-term impacts. Many of the problems currently addressed by users involve the gradual buildup of pollutants and the impact on downstream water bodies. To study these types of problems, results are needed from runs with output spanning several decades.
Model Contact Information: |
SWAT2000 was developed by the USDA, ARS, and the Texas A&M Spatial Sciences Laboratory with funding from EPA and is incorporated into EPA’s BASINS 3.0 water quality modeling system. |
Model Homepage: |
The EPA Storm Water Management Model (SWMM) is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and generate runoff and pollutant loads. The routing portion of SWMM transports this runoff through a system of pipes, channels, storage/treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff generated within each subcatchment, and the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period comprised of multiple time steps. It continues to be widely used for planning, analysis and design related to stormwater runoff, combined sewers, sanitary sewers, and other drainage systems in urban areas, with many applications in non-urban areas as well.
SWMM accounts for various hydrologic processes that produce runoff from urban areas. These include:
- time-varying rainfall
- evaporation of standing surface water
- snow accumulation and melting
- rainfall interception from depression storage
- infiltration of rainfall into unsaturated soil layers
- percolation of infiltrated water into groundwater layers
- interflow between groundwater and the drainage system
- nonlinear reservoir routing of overland flow.
Spatial variability in all of these processes is achieved by dividing a study area into a collection of smaller, homogeneous subcatchment areas, each containing its own fraction of pervious and impervious sub-areas. Overland flow can be routed between sub-areas, between subcatchments, or between entry points of a drainage system.
SWMM also contains a flexible set of hydraulic modeling capabilities used to route runoff and external inflows through the drainage system network of pipes, channels, storage/treatment units and diversion structures. These include the ability to:
- handle drainage networks of unlimited size
- use a wide variety of standard closed and open conduit shapes as well as natural channels
- model special elements such as storage/treatment units, flow dividers, pumps, weirs, and orifices
- apply external flows and water quality inputs from surface runoff, groundwater interflow, rainfall-dependent infiltration/inflow, dry weather sanitary flow, and user-defined inflows
- utilize either kinematic wave or full dynamic wave flow routing methods
- model various flow regimes, such as backwater, surcharging, reverse flow, and surface ponding
- apply user-defined dynamic control rules to simulate the operation of pumps, orifice openings, and weir crest levels
In addition to modeling the generation and transport of runoff flows, SWMM can also estimate the production of pollutant loads associated with this runoff. The following processes can be modeled for any number of user-defined water quality constituents:
- dry-weather pollutant buildup over different land uses
- pollutant washoff from specific land uses during storm events
- direct contribution of rainfall deposition
- reduction in dry-weather buildup due to street cleaning
- reduction in washoff load due to BMPs
- entry of dry weather sanitary flows and user-specified external inflows at any point in the drainage system
- routing of water quality constituents through the drainage system
- reduction in constituent concentration through treatment in storage units or by natural processes in pipes and channels
Since its inception, SWMM has been used in multiple sewer and stormwater studies. Typical applications include:
- design and sizing of drainage system components for flood control
- sizing of detention facilities and their accessories for flood control and water quality protection
- flood plain mapping of natural channel systems (SWMM 5 is a FEMA-approved model for NFPI studies)
- designing control strategies for minimizing combined sewer overflows
- evaluating the impact of inflow and infiltration on sanitary sewer overflows
- generating non-point source pollutant loadings for waste load allocation studies
- evaluating the effectiveness of BMPs for reducing wet weather pollutant loadings.
Model Contact Information: |
Lewis Rossman |
Model Homepage: |
The SPARROW method uses spatially referenced regressions of contaminant transport on watershed attributes to support regional water-quality assessment goals, including descriptions of spatial and temporal patterns in water quality and identification of the factors and processes that influence those conditions. The method is designed to reduce the problems of data interpretation caused by sparse sampling, network bias, and basin heterogeneity.
The regression equation relates measured transport rates in streams to spatially referenced descriptors of pollution sources and land-surface and stream-channel characteristics. Spatial referencing of land-based and water-based variables is accomplished via superposition of a set of contiguous land-surface polygons on a digitzed network of stream reaches that define surface-water flow paths for the region of interest.
Water-quality measurements are obtained from monitoring stations located in a subset of the stream reaches. Water-quality predictors in the model are developed as a function of both reach and land-surface attributes and include quantities describing contaminant sources (point and nonpoint) as well as factors associated with rates of material transport through the watershed (such as soil permeability and stream velocity).
Predictor formulae describe the transport of contaminant mass from specific sources to the downstream end of a specific reach. Loss of contaminant mass occurs during both overland and in-stream transport.
In calibrating the model, measured rates of contaminant transport are regressed on predicted transport rates at the locations of the monitoring stations, giving rise to a set of estimated linear and nonlinear coefficients from the predictor formulae.
Once calibrated, the model is used to estimate contaminant transport and concentration in all stream reaches. A variety of regional characterizations of water-quality conditions are then possible based on statistical summarization of reach-level estimates. The application of bootstrap techniques allows estimation of the uncertainty of model coefficients and predictions.
Model Contact Information: |
Richard A. Smith Gregory E. Schwarz Richard B. Alexander |
Model Homepage: |
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Useful Links: |
QUAL2Kw is a river and stream water quality model that is intended to represent a modernized version of the QUAL2E model (Brown and Barnwell, 1987). QUAL2Kw is related to the QUAL2K model that was developed by Dr. Steven Chapra (Chapra and Pelletier, 2003). It is similar to QUAL2E in the same ways that QUAL2K are similar to QUAL2E (see above).
The QUAL2Kw (Q2K) framework includes the following new elements:
- Software environment and interface. Q2K is implemented within the Microsoft Excel/VBA environment. It is programmed in the Windows macro language: Visual Basic for Applications (VBA). Excel is used as the graphical user interface.
- Model segmentation. QUAL2E segments the system into river reaches comprised of equally spaced elements. In contrast, Q2K can use unequally-spaced reaches. In addition, multiple loadings and abstractions can be input to any reach.
- Carbon speciation. Q2K uses two forms of carbon, rather than BOD, to represent organic carbon. These forms are a slowly oxidizing form (slow dissolved organic carbon) and a rapidly oxidizing form (fast dissolved organic carbon). In addition, non-living particulate organic matter (detritus) is simulated. This detrital material includes particulate organic carbon, nitrogen, and phosphorus.
- Anoxia. Q2K accommodates anoxia by reducing oxidation reactions to zero at low oxygen levels. In addition, denitrification is modeled.
- Bottom algae. The model explicitly simulates attached bottom algae using either zero-order or first-order growth kinetics.
- Luxury uptake. Variable stoichiometry of nitrogen and phosphorus in bottom algae and phytoplankton.
- Light extinction. Light extinction is calculated as a function of algae, detritus and inorganic solids.
- pH. Both alkalinity and total inorganic carbon are simulated. These are used to determine pH.
- Pathogen indicator. A generic pathogen indicator is simulated (e.g. fecal coliform or Enterococci). Pathogen indicator removal is determined as a function of temperature, light, and settling.
- Sediment-water interactions. Sediment-water fluxes of dissolved oxygen and nutrients are simulated internally rather than being prescribed. Oxygen (SOD) and nutrient fluxes are simulated as a function of settling particulate organic matter, diagenesis reactions within the sediments, and the concentrations of soluble forms in the overlying waters.
- Sediment heat flux. Sediment-water heat flux and sediment temperature is simulated using a Fick's law formulation to account for conduction between the water and sediment and hyporheic flow and heat exchange.
- Hyporheic respiration. Exchange of water between the surface water column and the hyporheic zone, and simulation of sediment pore water quality, including optional simulation of growth and respiration of heterotrophic bacteria biofilm in the hyporheic zone.
- Total dissolved gas. Dissolved nitrogen and argon gases are included in addition to oxygen and carbon dioxide for the calculation of total dissolved gas. Optional calculation of the super-saturation of dissolved gases in spillways of large dams is also included.
Model Contact Information: |
Greg Pelletier |
Model Homepage: |
QUAL2K (or Q2K) is a river and stream water quality model that is intended to represent a modernized version of the QUAL2E (or Q2E) model (Brown and Barnwell 1987). Q2K is similar to Q2E in the following respects:
- One dimensional. The channel is well-mixed vertically and laterally.
- Steady state hydraulics. Non-uniform, steady flow is simulated.
- Diurnal heat budget. The heat budget and temperature are simulated as a function of meteorology on a diurnal time scale.
- Diurnal water-quality kinetics. All water quality variables are simulated on a diurnal time scale.
- Heat and mass inputs. Point and non-point loads and abstractions are simulated.
The QUAL2K framework includes the following new elements:
- Software Environment and Interface. Q2K is implemented within the Microsoft Windows environment. It is programmed in the Windows macro language: Visual Basic for Applications (VBA). Excel is used as the graphical user interface.
- Q2E segments the system into river reaches comprised of equally spaced elements. In contrast, Q2K uses unequally-spaced reaches. In addition, multiple loadings and abstractions can be input to any reach.
- Carbonaceous BOD speciation.Q2K uses two forms of carbonaceous BOD to represent organic carbon. These forms are a slowly oxidizing form (slow CBOD) and a rapidly oxidizing form (fast CBOD). In addition, non-living particulate organic matter (detritus) is simulated. This detrital material is composed of particulate carbon, nitrogen and phosphorus in a fixed stoichiometry.
- Anoxia.Q2K accommodates anoxia by reducing oxidation reactions to zero at low oxygen levels. In addition, denitrification is modeled as a first-order reaction that becomes pronounced at low oxygen concentrations.
- Sediment-water interactions. Sediment-water fluxes of dissolved oxygen and nutrients are simulated internally rather than being prescribed. That is, oxygen (SOD) and nutrient fluxes are simulated as a function of settling particulate organic matter, reactions within the sediments, and the concentrations of soluble forms in the overlying waters.Bottom algae. The model explicitly simulates attached bottom algae.
- Light extinction. Light extinction is calculated as a function of algae, detritus and inorganic solids.
- pH. Both alkalinity and total inorganic carbon are simulated. The river ?s pH is then simulated based on these two quantities.
- Pathogens. A generic pathogen is simulated. Pathogen removal is determined as a function of temperature, light, and settling.
Model Contact Information: |
Tim Wool |
Model Homepage: |
QUAL2E is a steady state and quasi-dynamic water quality model for the simulation of point source impact on water quality including nitrogen and phosphorus cycling, dissolved oxygen and BOD, algae, fecal coliform, other conservative and non-conservative substances, and temperature and fecal coliform for steady mean or 7Q10 flow. In the BASINS system, reach flow, reach network, and point source data are extracted for user selected reach segments and automatically populated in the QUAL2E Windows interface. As the QUAL2E water quality model is steady state flow and pollutant load model, the output it produces is pollutant concentration or flow as a function of distance downstream.
QUAL2E, which can be operated either as a steady-state or as a dynamic model, is intended for use as a water quality planning tool. The model can be used, for example, to study the impact of waste loads on instream water quality or to identify the magnitude and quality characteristics of nonpoint waste loads as part of a field sampling program. The user also can model effects of diurnal variations in meteorological data on water quality (primarily dissolved oxygen and temperature) or examine diurnal dissolved oxygen variations caused by algal growth and respiration. QUAL2E can be used to calculate Waste Load Allocations (WLAs) and/or Total Maximum Daily Loads (TMDLs), ultimately resulting in permit limits.
Model Contact Information: |
Paul Cocca QUAL2E was developed by Linfield Brown and Thomas Barnwell of Tufts University, Medford, MA, Department of Civil Engineering with funding from EPA Office of Research and Development Environmental Research Lab in Athens, GA. It is maintained by Russell Kinerson (U.S. EPA, Office of Water (OW), Office of Science and Technology (OST)). |
Model Homepage: |
http://smig.usgs.gov/cgi-bin/SMIC/model_home_pages/model_home?selection=qual2e |
HSPF can be used to model both watersheds and receiving waterbodies including rivers, streams, and well-mixed lakes and reservoirs. It can be applied to watersheds of any size, and for both predominantly rural, as well as rural/urban land use mixtures. It does not simulate stormwater flow through sewer networks. HSPF v.12, finalized this year, was developed in the early 80's as HSPF v.5 based on the Stanford Watershed Model (SWM) and four other models.
HSPF is a continuous simulation model, driven by meteorological data, typically at a one-hour time step.
The model simulates the complete hydrology of a watershed and simulates the fate and transport of a wide variety of pollutants, from land surface processes, to overland runoff, to fate and transport in river reach networks.
It simulates both the fate and transport of pollutants from both point and non-point sources. Organized in modules defined largely by pollutant categories, HSPF simulates conservative tracers, sediments, pesticides, nutrients, and general quality constituents.
· Conservative tracers are modeled according to simple transport with no on-land or in-stream reactions;
· Sediment simulation processes include scour and gully erosion on the land surface, and sediment deposition and resuspension in stream and river reaches;
· Pesticide fate and transport includes a number of degradation processes and adsorption/desorption;
· Phosphorous and nitrogen are modeled with complete on-land and in-stream nutrient cycle reactions involving oxygen, heat balance, and phytoplankton;
General quality constituents are any user-specified pollutant that can be reasonably represented by a build-up/washoff phenomenon on land segments and by first order degradation in reaches and/or reservoirs.
Model Contact Information: |
Paul Cocca Model was developed and is maintained by Brian R. Bicknell, John C. Imhoff, John L. Kittle, Jr., Thomas H. Jobes, and Anthony S. Donigian, Jr. at AQUA TERRA Consultants, Mountain View, California (in cooperation with the Office of Surface Water, Water Resources Division, U.S. Geological Survey). |
Model Homepage: |
http://water.usgs.gov/software/hspf.html
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HSPF can be used to model both watersheds and receiving waterbodies including rivers, streams, and well-mixed lakes and reservoirs. It can be applied to watersheds of any size, and for both predominantly rural, as well as rural/urban land use mixtures. It does not simulate stormwater flow through sewer networks. HSPF v.12, finalized this year, was developed in the early 80's as HSPF v.5 based on the Stanford Watershed Model (SWM) and four other models.
HSPF is a continuous simulation model, driven by meteorological data, typically at a one-hour time step.
The model simulates the complete hydrology of a watershed and simulates the fate and transport of a wide variety of pollutants, from land surface processes, to overland runoff, to fate and transport in river reach networks.
It simulates both the fate and transport of pollutants from both point and non-point sources. Organized in modules defined largely by pollutant categories, HSPF simulates conservative tracers, sediments, pesticides, nutrients, and general quality constituents.
· Conservative tracers are modeled according to simple transport with no on-land or in-stream reactions;
· Sediment simulation processes include scour and gully erosion on the land surface, and sediment deposition and resuspension in stream and river reaches;
· Pesticide fate and transport includes a number of degradation processes and adsorption/desorption;
· Phosphorous and nitrogen are modeled with complete on-land and in-stream nutrient cycle reactions involving oxygen, heat balance, and phytoplankton;
General quality constituents are any user-specified pollutant that can be reasonably represented by a build-up/washoff phenomenon on land segments and by first order degradation in reaches and/or reservoirs.
Model Contact Information: |
Paul Cocca Model was developed and is maintained by Brian R. Bicknell, John C. Imhoff, John L. Kittle, Jr., Thomas H. Jobes, and Anthony S. Donigian, Jr. at AQUA TERRA Consultants, Mountain View, California (in cooperation with the Office of Surface Water, Water Resources Division, U.S. Geological Survey). |
Model Homepage: |
http://water.usgs.gov/software/hspf.html
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CE-QUAL-W2 is a two-dimensional (longitudinal/vertical) hydrodynamic and water quality model that has been under development for over 25 years and has been successfully applied to over 400 systems throughout the U.S. and the world. Version 3 can now model entire waterbasins including sloping rivers, reservoirs, and estuaries.
Relevant hydrodynamic/transport capabilities include dynamic adjustment of the timestep to help ensure numerical stability, variable vertical/longitudinal grid spacing, wetting/drying, multiple point/nonpoint sources, and a higher-order numerical transport scheme (QUICKEST/ ULTIMATE) that reduces numerical diffusion and eliminates physically unrealistic over / undershoots.
Relevant water quality capabilities include any number of generic consitutuents that could include a conservative tracer, and/or water age, and/or coliform bacteria groups. These generic constituents are defined by a settling velocity, and/or a 0-order decay rate, and/or a 1st order decay rate, and/or an Arhennius temperature rate multiplier. The model can also simulate any number of phytoplankton groups, any number of CBOD groups, any number of inorganic suspended solids groups, phosphate, ammonium, nitrate/nitrite, dissolved silica, particulate biogenic silica, dissolved iron, dissolved oxygen, total inorganic carbon, and alkalinity. The model also has the capability to internally compute and output derived variables such as pH, TOC, DOC, POC, DOP, TOP, etc. for comparison to measured observed data.
Typical year long simulations to a single river, reservoir, lake, or estuary take less than 10 minutes on a 1Ghz pentium machine although, with V3.1, applications to a waterbasin may take several hours of CPU time. The model has been used routinely for decade long simulations. The model is currently being used extensively for FERC relicensing projects and TMDL's.
The model will continue to be developed in the future including adding sediment transport, sediment diagenesis, macrophytes, periphyton, zooplankton, and contaminants.
Model Contact Information: |
Tom Cole Model was developed and is maintained by Tom Cole and Scott Wells ( Portland State University). |
Model Homepage: |
BASINS system is configured to support environmental and ecological studies in a watershed context. The system is designed to be flexible. It can support analysis at a variety of scales using tools that range from simple to sophisticated. BASINS was also conceived as a system for supporting the development of total maximum daily loads (TMDLs). Section 303(d) of the Clean Water Act requires states to develop TMDLs for water bodies that are not meeting applicable water quality standards by using technology-based controls. Developing TMDLs requires a watershed-based approach that integrates both point and non-point sources. BASINS can support this type of watershed-based point and non-point source analysis for a variety of pollutants. It also lets the user test different management options.
Model Contact Information: |
Russell Kinerson Model was developed by Russell Kinerson, Paul Cocca, Ed Partington, Marjorie Wellman, and David Wells of EPA's |
Model Homepage: |
AQUATOX is a PC-based ecosystem model that simulates the transfer of biomass and chemicals from one compartment of the ecosystem to another. It does this by simultaneously computing important chemical and biological processes over time. AQUATOX can predict not only the fate of chemicals in aquatic ecosystems, but also their direct and indirect effects on the resident organisms. Therefore, it has the potential to help establish the cause and effect relationships between chemical water quality, the physical environment, and aquatic life.
AQUATOX Release 2 has enhanced scientific capabilities and analytical tools to more completely simulate and understand aquatic ecosystems. The updates include:
- Calculation of retention time in lakes and reservoirs
- Refinement of the calculation for light extinction due to blue-green algae and calculation of blue-green algae as a percentage of total algae
- Minor corrections related to the effects of excess temperature in plants and the calculation of initial conditions
- Improved algal parameter set and updated example applications
- Improved graphical user interface for more easily assigning toxicity data, and graphing model results
Model Contact Information: |
Marjorie Wellman |
Model Homepage: |
Follow this link to access more modeling information from EPA’s CREM (Council for Regulatory Modeling) Models Knowledge Base.
Follow this link to access more modeling information from USGS's Surface water-quality and flow Modeling Interest Group.
