|KIM, KEEWOOK - Busan Water Authority|
|WHELAN, GENE - Us Environmental Protection Agency (EPA)|
|MOLINA, MARIROSA - Us Environmental Protection Agency (EPA)|
|PARMER, RAJBIR - Us Environmental Protection Agency (EPA)|
|WOLFE, KURT - Us Environmental Protection Agency (EPA)|
|GALVIN, MICHAEL - Us Environmental Protection Agency (EPA)|
|DUDA, PAUL - Aqua Terra Consultants|
|ZEPP, RICHARD - Us Environmental Protection Agency (EPA)|
|KINZELMAN, JULIE - City Of Racine Public Health Deparment|
|KLEINHEINZ, T. - University Of Wisconsin|
Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/26/2018
Publication Date: 9/1/2018
Citation: Kim, K., Whelan, G., Molina, M., Parmer, R., Wolfe, K., Galvin, M., Duda, P., Zepp, R., Kinzelman, J.L., Kleinheinz, T., Borchardt, M.A. 2018. Using integrated environmental modeling to assess sources of microbial contamination in mixed-use watersheds. Journal of Environmental Quality. 34:1103-1114.
Interpretive Summary: In a watershed consisting of streams, rivers, and lakes there can be many sources of fecal contamination such as human sewage, livestock manure, and wildlife. With the complexity presented by so many possible sources and environmental factors in a watershed it can be difficult to determine which source is the most important contributor to contamination. This study found an appropriately designed computer model can account for this complexity and accurately predict the river concentrations of a microorganism commonly found in fecal material. The model can be used for “what if” scenarios, for example, estimating how much fecal contamination would be reduced if cattle were not allowed to wade in streams. This work is important as it will give watershed managers a tool for making decisions on land use practices, such as locations of septic systems and siting of livestock.
Technical 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.