Browsing by Author "Soupir, M. L."

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    Die-off of E. coli and enterococci in dairy cowpats
    Soupir, M. L.; Mostaghimi, Saied; Lou, J. (American Society of Agricultural and Biological Engineers, 2008)
    E. coli and enterococci re-growth and decay patterns in cowpats applied to pasturelands were monitored during the spring, summer fall, and winter First-order approximations were used to determine die-off rate coefficients and decimal reduction times (D-values). Higher-order approximations and weather parameters were evaluated by multiple regression analysis to identify environmental parameters impacting in-field E. coli and enterococci decay. First-order kinetics approximated E. coli and enterococci decay rates with regression coefficients ranging from 0.70 to 0.90. Die-off rate constants were greatest in cowpats applied to pasture during late winter and monitored into summer months for E. coli (k = 0.0995 d(-1)) and applied to the field during the summer and monitored until December for enterococci (k = 0.0978 d(-1)). Decay rates were lowest in cowpats applied to the pasture during the fall and monitored over the winter (k = 0.0581 d(-1) for E. coli, and k = 0.0557 d(-1) for enterococci). Higher-order approximations and the addition of weather variables improved regression coefficients to values ranging from 0.82 to 0.96. Statistically significant variables used in the models for predicting bacterial decay included temperature, solar radiation, rainfall, and relative humidity. Die-off rate coefficients previously reported in the literature are usually the result of laboratory-based studies and are generally higher than the field-based seasonal die-off rate coefficients presented here. To improve predictions of in-field E. coli and enterococci concentrations, this study recommends that higher-order approximations and additional parameters such as weather variables are necessary to better capture re-growth and die-off trends over extended periods of time.
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    Modeling bacteria fate and transport in watersheds to support TMDLs
    Benham, Brian L.; Baffaut, C.; Zeckoski, Rebecca Winfrey; Mankin, K. R.; Pachepsky, Y. A.; Sadeghi, A. A.; Brannan, Kevin M.; Soupir, M. L.; Habersack, M. J. (American Society of Agricultural and Biological Engineers, 2006)
    Fecal contamination of surface waters is a critical water-quality issue, leading to human illnesses and deaths. Total Maximum Daily Loads (TMDLs), which set pollutant limits, are being developed to address fecal bacteria impairments. Watershed models are widely used to support TMDLs, although their use for simulating in-stream fecal bacteria concentrations is somewhat rudimentary. This article provides an overview of fecal microorganism fate and transport within watersheds, describes current watershed models used to simulate microbial transport, and presents case studies demonstrating model use. Bacterial modeling capabilities and limitations for setting TMDL limits are described for two widely used watershed models (HSPF and SWAT) and for the load-duration method. Both HSPF and SWAT permit the user to discretize a watershed spatially and bacteria loads temporally. However, the options and flexibilities are limited. The models are also limited in their ability to describe bacterial life cycles and in their ability to adequately simulate bacteria concentrations during extreme climatic conditions. The load-duration method for developing TMDLs provides a good representation of overall water quality and needed water quality improvement, but intra-watershed contributions must be determined through supplemental sampling or through subsequent modeling that relates land use and hydrologic response to bacterial concentrations. Identified research needs include improved bacteria source characterization procedures, data to support such procedures, and modeling advances including better representation of bacteria life cycles, inclusion of more appropriate fate and transport processes, improved simulation of catastrophic conditions, and creation of a decision support tool to aid users in selecting an appropriate model or method for TMDL development.