A clear understanding of a model is important for its appropriate use. In this article, eleven watershed scale hydrologic and nonpoint-source pollution models are reviewed: AGNPS, AnnAGNPS, ANSWERS, CASC2D, DWSM, HSPF, KINEROS, MIKE SHE, PRMS, and SWAT. AnnAGNPS, HSPF, and SWAT are continuous simulation models useful for analyzing long-term effects of hydrological changes and watershed management practices, especially agricultural practices. AGNPS, ANSWERS, DWSM, and KINEROS are single rainfall event models useful for analyzing severe actual or design single-event storms and evaluating watershed management practices, especially structural practices. CASC2D, MIKE SHE, and PRMS have both long-term and single-event simulation capabilities. Mathematical bases, the most important and critical elements of these mathematical models, were identified and compiled. In this article, a comprehensive summary of the compilation is presented in tabular form. The flow-governing equations and their solution methods used in each of the eleven models are discussed. The compilation of the mathematical bases of these models would be useful to determine the problems, situations, or conditions for which the models are most suitable, the accuracies and uncertainties expected, their full potential uses and limitations, and directions for their enhancements or new developments. AGNPS, AnnAGNPS, DWSM, HSPF, MIKE SHE, and SWAT were found to have all the three major components (hydrology, sediment, and chemical) applicable to watershed-scale catchments. SWAT is a promising model for continuous simulations in predominantly agricultural watersheds, and HSPF is promising for mixed agricultural and urban watersheds. Among the single-event models, DWSM provides a balance between the simple but approximate and the computationally intensive models and, therefore, is a promising storm event model for agricultural watersheds.

Based on recent reviews of 11 physically based watershed models, the long-term continuous model soil and water assessment tool ͑SWAT͒ and the storm event dynamic watershed simulation model ͑DWSM͒ were selected to examine their hydrologic formulations, calibrate, and validate them on the 620 km 2 watershed of the upper Little Wabash River at Effingham, Ill., and examine their compatibility and benefits of combining them into a more comprehensive and efficient model. Calibration and validation of the SWAT by comparing monthly simulated and observed flows and adjusting the model-assigned resulted in coefficients of determination and Nash-Sutcliffe coefficients for individual years and cumulatively for the calibration period ͑1995-1999͒ and for the entire simulation period ͑1995-2002͒ mostly above or near 0.50 with an exception of 0.05 and −0.27, respectively, in 2001, relatively a dry year. Visual comparisons of the hydrographs showed SWAT's weakness in predicting monthly peak flows ͑mostly underpredictions.͒ Therefore, SWAT needs enhancements in storm event simulations for improving its high and peak flow predictions. Calibration of DWSM was not necessary; its three physically based parameters were taken from SWAT. Validation of DWSM on three intense storms in May 1995, March 1995, and May 2002 resulted 1, −29, and 16% errors in peak flows and 0, −11, and 0% errors in times to peak flows, respectively. Comparisons of DWSM's 15-min flow hydrographs with SWAT's daily flow hydrographs along with the 15-min and daily observed flow hydrographs during the above three storms confirmed that DWSM predicted more accurate high and peak flows and precise arrival times than SWAT. DWSM's robust routing scheme using analytical and approximate shock-fitting solutions of the kinematic wave equations was responsible for the better predictions, the addition of which along with its unique combination with the popular runoff curve number method for rainfall excess computation to SWAT would be a significant enhancement. Parameters and data of both the models are interchangeable and, therefore, are compatible and their combination will result in a more comprehensive and efficient model.

No abstract

The U.S. Geological Survey (USGS), in cooperation with DuPage County Stormwater Management Division, maintains a USGS database of hourly meteorologic and hydrologic data for use in a near real-time streamflow simulation system, which assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek watershed in DuPage County, Illinois. Most of the precipitation data are collected from a tipping-bucket rain-gage network located in and near DuPage County. The other meteorologic data (wind speed, solar radiation, air temperature, and dewpoint temperature) are collected at Argonne National Laboratory in Argonne, Ill. Potential evapotranspiration is computed from the meteorologic data. The hydrologic data (discharge and stage) are collected at USGS streamflow-gaging stations in DuPage County. These data are stored in a Watershed Data Management (WDM) database. An earlier report (Murphy and Ishii, 2006) describes in detail the WDM database development including the processing of data from