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Pathogen Transport and Fate Modeling in the Upper Salem River Watershed Using SWAT Model
Citation:
Niazi, M. AND C. Obropta. Pathogen Transport and Fate Modeling in the Upper Salem River Watershed Using SWAT Model. Presented at AWRA Conference, Jacksonville, FL, November 12 - 15, 2012.
Impact/Purpose:
This research was part of a comprehensive project to find out potential sources of pathogen pollution (human, wildlife and livestock) in the Upper Salem River Watershed located in NJ. The project was supported by USDA- NIFA, (CSREES) grant # 2007-35-102-18145.
Description:
SWAT (Soil and Water Assessment Tool) is a dynamic watershed model that is applied to simulate the impact of land management practices on water quality over a continuous period. The Upper Salem River, located in Salem County New Jersey, is listed by the New Jersey Department of Environmental Protection as a pathogen impaired surface water. The contributing watershed is 37 km2 and predominantly agricultural. The overall goal of this research is to use SWAT to simulate pathogen fate and transport, as a tool to evaluate different management practices in order to reduce pathogen loading to the river. This effort was the first watershed modeling attempt using SWAT to successfully simulate two pathogen indicators (E. coli and fecal coliform) simultaneously. Hydrologic calibration and validation results at six sampling points show a good (Nash-Sutcliffe Efficiency (0.65 < E < 0.75) to unsatisfactory (E < 0.5) linear relationship between measured and predicted daily flow data (0.32 < E < 0.70) and (0.2 < E < 0.66) respectively. Sensitivity analysis has been performed for flow as well as fecal coliform and E. coli. Monthly calibration and validation of the pathogen transport model was conducted for both fecal (0.07 < E < 0.47) and (-0.94 < E < 0.33) and E. coli (0.03 < E < 0.39) and (-0.81 < E < 0.31) for the six sampling points. Comparing the results of this study with similar pathogen modeling efforts indicates that this study has achieved higher Nash-Sutcliffe Efficiency numbers. The research contributes new knowledge in E. coli and fecal coliform modeling and will help increase the understanding of sensitivity analysis and pathogen modeling with SWAT at the watershed scale.
