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

Abstract

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.

Microbial Water Quality: Monitoring and Modeling

“…Data‐poor environments can still benefit from watershed‐scale modeling. The example given by M. Kim et al (2018) for a watershed in Laos shows how the Soil and Water Assessment Tool (SWAT) model can assess microbial water quality in a watershed experiencing fast‐changing land use. Additional flexibility of SWAT is advocated to improve simulations of microbial water quality in tropical landscapes.…”

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies

“…Given the inherent uncertainty associated with emission, fate and transport, and health effects of emerging contaminants, these considerations are particularly critical for microbial CECs. Ongoing advances in QMRA include integration with molecular biology tools, such as microbial source tracking and whole genome sequencing (Haas, 2020 ; Rantsiou et al., 2018 ; Q. Zhang et al., 2019 ), incorporation of Bayesian network modeling approaches (Beaudequin et al., 2015 ; Greiner et al., 2013 ), and development of software applications for practical implementation (Chhipi‐Shrestha et al., 2017 ; K. Kim et al., 2018 ; Schijven et al., 2015 ). Among microbial CECs, AMR presents unique challenges for QMRA (Ashbolt et al., 2013 ; Pires et al., 2018 ); see Section 1.3.2 .…”