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Activity Number:
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186
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Type:
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Invited
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Date/Time:
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Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics & the Environment
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| Abstract - #301454 |
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Title:
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Understanding Variation in Escherichia coli Occurrence at a Freshwater Beach Through Spatial Analyses and GIS: Implications for Beach Management and Public Health
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Author(s):
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Sharyl Rabinovici*+ and Richard A. Champion and Richard Whitman
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Companies:
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U.S. Geological Survey and U.S. Geological Survey and U.S. Geological Survey
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Address:
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Western Geological Science Center, Menlo Park, CA, 94205,
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Keywords:
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Escherichia coli ; predictive modeling ; GIS ; beach management ; visualization ; variability
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Abstract:
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The presence of Escherichia coli (E. coli) bacteria in recreational waters is a growing public health concern. U.S. Geological Survey (USGS) studies suggest that E. coli may exhibit spatial and temporal variation that reduces the effectiveness of current beach closure procedures. The USGS is investigating this issue in two projects using water quality data collected at West Beach, Indiana, by the U.S. Environmental Protection Agency in 2000. First, environmental variables are used to predict E. coli levels. The best fit regression model explains about 30 percent of total E. coli variation at the site. Next, maps and animations are used to show how space-time variability in E. coli can lead to either excessive or insufficient swim closures under current sampling practices. The visualizations utilize interpolation techniques such as finite element and neural network algorithms. Programming is done in C++ and S-Plus with graphics display in a geographic information system. Recommendations include increasing the number, frequency and locations of samples taken and expanding the use of predictive models in identifying contamination patterns and alternative management strategies.
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