Watershed modelling for predicting in-stream pathogen levels

Pramod Pandey, University of California, Davis, USA, Chris Rehmann and Michelle Soupir, Iowa State University, Ames, Iowa, USA


Elevated levels of pathogen pose serious risks to steams and public health. In many of streams in the U.S., elevated levels of pathogen are linked to non-point source pollution (NPS). The NPS pollution of pathogen at watershed scale is mainly controlled by the complex interactions among land cover/land use, soil characteristics, elevation, stream geometry, and climate (i.e., temperature, rainfall, and solar radiation). Improving understanding of how each characteristics of a watershed potentially influences pathogen loads in streams requires watershed modeling, which can help in identifying water quality Best Management Practices (BMPs) and controlling pathogen/pathogen indicator NPS loads. Here, we have developed a model for predicting pathogen loads in stream bed sediment and the water column. Subsequently, the model was integrated with Soil and Water Assessment Tool (SWAT) model for developing a watershed scale hydrological model for estimating E. coli Total Maximum Daily Loads (TMDLs). The model predictions were verified by multiple-years monitoring of in-stream bed sediment and water column E. coli levels. We anticipate the approach of modeling and monitoring proposed here will help improving existing understanding of in-stream pathogen contamination.

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