Type of Document Master's Thesis Author Jocz, Robert Michael URN etd-07122012-111421 Title Development of a Risk Assessment Model to Assess TMDL Implementation Strategies Degree Master of Science Department Biological Systems Engineering Advisory Committee
Advisor Name Title Krometis, Leigh Anne Committee Chair Benham, Brian L. Committee Member Ziegler, Peter Committee Member Keywords
- Risk Assessment
- Monte Carlo
- Watershed Management
Date of Defense 2012-06-18 Availability unrestricted AbstractHigh levels of fecal indicator bacteria (e.g. E. coli) are the leading cause of identified surface water impairments in the United States. The US Clean Water Act of 1972 requires that jurisdictions establish priority rankings for impaired waterways and develop a Total Maximum Daily Load (TMDL) plan for each. Although past research indicates that the risk of illness to humans varies by source of fecal contamination, current watershed assessments are developed according to total concentration of indicator bacteria, with all sources weighed equally.
A stochastic model using Quantitative Microbial Risk assessment (QMRA) principles to translate source-specific (e.g. human, livestock) daily average concentrations of E.coli into a daily average risk of gastroenteritis infection was developed and applied to Pigg River, an impaired watershed in southern Virginia. Exposure was calculated by multiplying a ratio of source related reference pathogens to predicted concentrations of E.coli and a series of qualifying scalars. Risk of infection was then determined using appropriate dose response relationships.
Overall, human and goose sources resulted in the greatest human health risk, despite larger overall E.coli loading associated with cattle. Bacterial load reductions specified in the Pigg River TMDL were applied using Hydrological Simulation Program- FORTRAN (HSPF) to assess the effect these reductions would have on the risk of infection attributed to each modeled bacterial source. Although individual risk sources (neglecting geese) were reduced below the EPA limit of 8 illnesses per 1000 exposures, the combined risk of illness varied between 0.006 and 64 illnesses per 1000 exposures.
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