EPA Science Inventory

A Workflow to Model Microbial Loadings in Watersheds

Citation:

Wolfe, K., R. Parmar, G. Whelan, Gerry Laniak, M. Galvin, K. Kim, M. Molina, R. Zepp, P. Duda, AND D. Keiser. A Workflow to Model Microbial Loadings in Watersheds. iEMSs 8th International Congress on Environmental Modelling and Software, Toulouse, FRANCE, July 10 - 14, 2016.

Description:

Many watershed models simulate overland and instream microbial fate and transport, but few actually provide loading rates on land surfaces and point sources to the water body network. This paper describes the underlying general equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is linked within a workflow containing eight models and a set of databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal-impacted catchments. A hypothetical example application – accessing, retrieving, and using real-world data – demonstrates the ability of the infrastructure to automate many of the manual steps associated with a standard watershed assessment, culminating with calibrated flow and microbial densities at the pour point of a watershed.

Purpose/Objective:

Presented at 2016 Biennial Conference, International Environmental Modelling & Software Society.

URLs/Downloads:

http://www.iemss.org/sites/iemss2016/   Exit

Record Details:

Record Type: DOCUMENT (PRESENTATION/SLIDE)
Completion Date: 07/14/2016
Record Last Revised: 08/01/2016
Record Created: 08/01/2016
Record Released: 08/01/2016
OMB Category: Other
Record ID: 322579

Organization:

U.S. ENVIRONMENTAL PROTECTION AGENCY

OFFICE OF RESEARCH AND DEVELOPMENT

NATIONAL EXPOSURE RESEARCH LAB

COMPUTATIONAL EXPOSURE DIVISION