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This study compared the utility and results of four watershed models that include water quality elements: Spreadsheet Tool for Estimating Pollutant Load (STEPL), a GIS-based model to calculate pollutant loads for watersheds (PLOAD), Long-term Hydrologic Impact Assessment (L-THIA), and ArcGIS Soil and Water Assessment Tool (ArcSWAT). These models are different in their levels of complexity, data requirements, time step, and simulation techniques. Therefore, different scenarios were conducted to test some of the standard applications of each model based on data quality and model capabilities. Climatological, land use, and soil datasets as well as flow rates, sediment, nitrate, and total P concentrations were collected for the Pomona Lake watershed in Kansas over 30 years. Stakeholders' information was integrated into the models to the extent possible. Using results obtained from STEPL, L-THIA, PLOAD, and uncalibrated ArcSWAT for estimating long-term (30 years) average pollution loads in a watershed can result in incorrect load estimation. In addition, the STEPL, L-THIA, and PLOAD models may not be the most reliable in identifying pollutant source areas in a watershed. Therefore, in the context of effective resource allocation, use of simple models (such as STEPL, L-THIA, and PLOAD) is not suggested for critical source area targeting for watershed planning if the nature of the problem is complex. However, the simple models can still be used to evaluate relative contribution of different land uses to overall pollution loads. [ABSTRACT FROM AUTHOR]

As climate changes, the uncertainty of water availability, changing magnitudes of nonpoint-source pollution, and uncertainty of best management practice (BMPs) effectiveness are issues that watershed managers and stakeholders must consider and plan for. The objective of this study was to determine how BMP effectiveness will be affected by climate change using the Soil and Water Assessment Tool (SWAT). Using downscaled monthly precipitation and temperature data output from the Community Climate System Model (CCSM), daily precipitation and temperature data were produced based on observed weather station data for the Tuttle Creek Lake watershed in Kansas and Nebraska. The A1B, A2, and B1 SRES emissions scenarios were compared to historical CCSM model output. Eight agricultural BMPs were physically represented within SWAT and compared across climate scenarios. Water yield, surface runoff, baseflow, sediment load, nitrogen load, and phosphorus load increased in all three future climate scenarios. Terraces, contour farming, and native grass were determined to be the most effective in pollution load reduction and percent efficiency at the field and watershed scales in future scenarios. Porous gully plugs and filter strips showed no significant changes in pollution load or percent reduction. Grazing management, no-tillage, conservation tillage, and grazing management percent and load reduction in future scenarios varied at the field and watershed scales. This study demonstrates that BMP performance in terms of sediment, nitrogen, and phosphorus reduction significantly changes in future climate scenarios at the field scale, while performance generally does not change significantly at the watershed scale. [ABSTRACT FROM AUTHOR]