Using Integrated Environmental Modeling to Assess Sources of Microbial Contamination in Mixed‐Use Watersheds

Microbial fate and transport in watersheds should include a microbial source apportionment analysis that estimates the importance of each source, relative to each other and in combination, by capturing their impacts spatially and temporally under various scenarios. A loosely configured software infrastructure was used in microbial source‐to‐receptor modeling by focusing on animal‐ and human‐impacted mixed‐use watersheds. Components include data collection software, a microbial source module that determines loading rates from different sources, a watershed model, an inverse model for calibrating flows and microbial densities, tabular and graphical viewers, software to convert output to different formats, and a model for calculating risk from pathogen exposure. The system automates, as much as possible, the manual process of accessing and retrieving data and completes input data files of the models. The workflow considers land‐applied manure from domestic animals on undeveloped areas; direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; pastureland, cropland, forest, and urban or engineered areas; sources that directly release to streams from leaking septic systems; and shedding by domestic animals directly to streams. The infrastructure also considers point sources from regulated discharges. An application is presented on a real‐world watershed and helps answer questions such as: What are the major microbial sources? What practices contribute to contamination at the receptor location? What land‐use types influence contamination at the receptor location? and Under what conditions do these sources manifest themselves? This research aims to improve our understanding of processes related to pathogen and indicator dynamics in mixed‐use watershed systems. CORE IDEAS: We performed a microbial source apportionment and risk assessment on a mixed‐use watershed. Our work links water safety, environmental quality, and human health using integrated modeling. The modeling workflow informs on which microbial sources and land‐use types are of importance. We discuss how microbial criteria can be interpreted by linking modeling and monitoring. Such assessment can help determine the appropriateness of waivers to water quality criteria.