Understanding Fecal Indicator and Antimicrobial Resistant Organisms in a Mixed-use Watershed: The Role of Precipitation and Hydrological Conditions

Abstract Submission: Authors: Corinne Wiesner-Friedman (EPA-ORD), David Holcomb (CDC WDPB), Audrey Laiveling (ORISE), Daniel Weller (CDC EDEB), Caleb Buahin (EPA-ORD, Jeff Yang (EPA-ORD), Scott Keely (EPA-ORD), Nichole Brinkman (EPA-ORD), Michael Jahne (EPA-ORD), Jay Garland (EPA-ORD), Alison Franklin (EPA-ORD)

Understanding how fecal indicator and antimicrobial resistant organisms differ in their response to precipitation could improve how we assess and manage water quality in rivers and streams. Rainfall and hydrological conditions can greatly impact the spread of fecal contamination in surface water but potential interactions between hydrometerological processes over time and space present challenges to predicting the direction and magnitude of effects on fecal indicator and antimicrobial resistant organisms. The flush effect, in which intense rainfall after a period of drier conditions mobilizes large contaminant loads, can also reduce the impact of subsequent precipitation by diminishing contaminant stocks. However, the flush effect has not been well characterized in the context of environmental antimicrobial resistance, and existing estimation approaches rely on precipitation data aggregated over arbitrary time periods and simple statistical representations of temporal interactions. As part of a National Antimicrobial Resistance Monitoring System (NARMS) surface water pilot study, our work explores hybrid statistical and physically informed modeling approaches to assess the connection between rainfall intensity, duration, and frequency, and how these factors influence the occurrence of traditional and host-associated fecal indicators, extended-spectrum beta-lactamase (ESBL) producing E. coli, vancomycin resistant Enterococcus spp., and culturable Salmonella in a mixed-use Midwest watershed. By comparing analytical approaches, we aim to offer insights into how the flush effect on microbial water quality varies under different conditions, across spatial and temporal scales, and with land use and land cover.

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