Water Quality Modeling for the Raccoon River Watershed Using SWAT

The Raccoon River Watershed (RRW) in West-Central Iowa has been recognized as exporting some of the highest nitrate-nitrogen loadings in the United States and is a major source of sediment and other nutrient loadings. An integrated modeling framework has been constructed for the RRW that consists of the Soil and Water Assessment Tool (SWAT) model, the interactive SWAT (i_SWAT) software package, Load Estimator (LOADEST) computer program, and other supporting software and databases. The simulation framework includes detailed land use and management data such as different crop rotations and an array of nutrient and tillage management schemes, derived from the U.S. Department of Agriculture's National Resources Inventory databases and other sources. This paper presents the calibration and validation of SWAT for the streamflow, sediment losses, and nutrient loadings in the watershed and an assessment of land use and management practice shifts in controlling pollution. Streamflow, sediment yield, and nitrate loadings were calibrated for the 1981-1992 period and validated for the 1993-2003 period. Limited field data on organic nitrogen, organic phosphorus, and mineral phosphorus allowed model validation for the 2001-2003 period. Model predictions generally performed very well on both an annual and monthly basis during the calibration and validation periods, as indicated by coefficient of determination (R2) and Nash-Sutcliffe simulation efficiency (E) values that exceeded 0.7 in most cases. A set of land use change scenarios based on taking cropland out of production indicated a significant benefit in reducing sediment yield at the watershed outlet. A second scenario set found that relatively small reductions in nutrient applications resulted in significant reductions in nitrate loadings at the watershed outlet, without affecting crop yields significantly.

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Working or Discussion Paper
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CARD Working Paper 06-WP 428

 Record created 2017-04-01, last modified 2017-08-24

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