Comparative Evaluation of Statistical and Mechanistic Models of Escherichia coli at Beaches in Southern Lake Michigan

Statistical and mechanistic models are popular tools for predicting the levels of indicator bacteria at recreational beaches. Researchers tend to use one class of model or the other, and it is difficult to generalize statements about their relative performance due to differences in how the models ar...

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Bibliographic Details
Published in:Environmental science & technology 2016-03, Vol.50 (5), p.2442-2449
Main Authors: Safaie, Ammar, Wendzel, Aaron, Ge, Zhongfu, Nevers, Meredith B, Whitman, Richard L, Corsi, Steven R, Phanikumar, Mantha S
Format: Article
Language:English
Subjects:
Bathing Beaches
Beaches
Comparative analysis
Conductivity
E coli
Escherichia coli - physiology
Geography
Lakes - microbiology
Michigan
Models, Statistical
Models, Theoretical
Time series
Water Microbiology
Water quality
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Summary:Statistical and mechanistic models are popular tools for predicting the levels of indicator bacteria at recreational beaches. Researchers tend to use one class of model or the other, and it is difficult to generalize statements about their relative performance due to differences in how the models are developed, tested, and used. We describe a cooperative modeling approach for freshwater beaches impacted by point sources in which insights derived from mechanistic modeling were used to further improve the statistical models and vice versa. The statistical models provided a basis for assessing the mechanistic models which were further improved using probability distributions to generate high-resolution time series data at the source, long-term “tracer” transport modeling based on observed electrical conductivity, better assimilation of meteorological data, and the use of unstructured-grids to better resolve nearshore features. This approach resulted in improved models of comparable performance for both classes including a parsimonious statistical model suitable for real-time predictions based on an easily measurable environmental variable (turbidity). The modeling approach outlined here can be used at other sites impacted by point sources and has the potential to improve water quality predictions resulting in more accurate estimates of beach closures.
ISSN:0013-936X
1520-5851
DOI:10.1021/acs.est.5b05378