Water quality prediction tools As the name states, these are prediction tools They tend to state the worst possible case for water quality Many assumptions are built into their use
Water quality prediction tools Expected mean concentration modeling Fate transport modeling
Assumptions Streams have uniform width, depth, roughness Same ecological rate constants (reareation rates, pollution decay rates and sediment oxygen demand rate) Transport of pollutants is considered to be conservative (values get averaged over changing flow conditions only) -> no loss or decay of pollutants is considered
Limitations Does not consider infiltration, interflow, or ground water flow additions Does not include atmospheric conditions such as temperature or evapotranspiration Uses mean annual runoff and flow measures with one time water quality sampling data (must match sampling to normal flow conditions or calibrate flow to time of sampling)
Advantages Includes surface runoff from point and non-point sources It is a landscape (watershed) model as compared to a receiving water model Easy to analyze visual output and query capability from results A deterministic simulation model type
Expected mean concentration This is a landscape based water quality modeling approach as compared to an instream water quality modeling approach
Expected mean concentrations Difficult to find and have EMC studies done in study area Soils, temperature, rainfall, etc are all different It is best used as a proxy of possible conditions to compare one area vs another based on land cover distribution
EMC loading values references Adamus, C. L. and M. J. Bergman, 1995. Estimating Nonpoint Source Pollution Loads with a GIS Screening Model. Water Resources Bulletin, American Water Resources Association 12(4):647-655. Donigan, A. S., B. R. Bicknell, and L. C. Linker, 1995. Regional Assessment of Nutrient Loadings from Agriculture and Resulting Water Quality in the Chesapeake Bay Area. Proceedings of the International Symposium on Water Quality Modeling, American Society of Agricultural Engineers, Orlando, FL. Evans, B. M., R. A. White, G. W. Petersen, J. M. Hamlett, G. M. Baumer, A. J. McDonnell, 1994. Land Use and Nonpoint Pollution Study of the Delaware River Basin. Prepared for the Delaware River Basin Commission, Report Number ER9406, Environmental Resources Research Institute, The Pennsylvania State University, University Park, PA. Haith, D. A. and L. L. Shoemaker, 1987. Generalized Watershed Loading Functions for Stream Flow Nutrients. Water Resources Bulletin 23(3):471- 478. Nizeyimana, E, B. M. Evans, M. C. Anderson, G. W. Peterson, D. R. DeWalle, W. E. Sharpe, J. M. Hamlett, B. R. Swistock, 1997. Quantification of NPS Pollution Loads Within Pennsylvania Watersheds. Prepared for Pennsylvania Department of Environmental Protection Bureau of Water Quality Protection, Report Number ER9708,Environmental Resources Research Institute, The Pennsylvania State University, University Park, PA. Olivera, F., R. J. Chareneau and D. R. Maidment, 1996. Spatially Distributed Modeling of Storm Runoff and Non-Point Source Pollution Using GIS. Report 96-4, Center for Watershed Research, University of Texas, Austin, TX.
Expected mean concentrations The previous table can be used with different land cover as input but all cover types must be aggregated to fit into one of the six types to be assigned a loading rate
Estimating Annual Loadings Throughout Watershed The pollutant mass contribution that each cell makes to downstream pollutant loading is calculated by taking the product of the expected mean concentration and runoff associated with the cell or Load (mass/time) = EMC (mass/volume) * Q (volume/time) Which becomes….
Estimating Annual Loadings Throughout Watershed L = K * Q * EMC * A Q is units in mm/year EMC is in mg/Liter A is area of one grid cell K is constant to make units consistent ( ie K = 10 -6 kg-m-L/mg-mm-m 3 ) so that L is determined in kg/year