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Predictive Models for Determination of E. coli Concentrations at Inland Recreational Beaches

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Abstract

Given the 24-h turn-around time before swimming advisories are released, advisories issued to protect public health really only indicates ‘it may be unsafe to swim yesterday’. Predictive modelling for Escherichia coli concentrations at inflow-impacted beaches may be a favourable alternative to the current, routinely criticised monitoring approach. Using a total of 482 sets of meteorological and bacteriological data covering 14 swimming seasons, as well as environmental data of 10 inflow streams, this study developed models that could be used for predicting E. coli concentrations at five Lake Rotorua beaches. The models include predictor variables such as wind speed, antecedent rainfall, suspended solids at Puarenga, Utuhina and Ngongotaha stream inflows and particulate inorganic phosphorus concentration at Puarenga stream inflow. The combined 2011–2012 models had an average-adjusted R 2 of 0.73, root mean square error (RMSE) of 0.33 logCFU/100 mL and captured 38 % of the variance in the validation data when used to predict E. coli concentrations for an additional 2 years (2013–2014). Among the individual beach models, predictive accuracy ranged from 88.89 to 92.31 % for the three beaches considered in the study. The developed models can provide a faster estimation of E. coli condition, potentially assisting local beach managers in the decision process related to swimming advisories issuance.

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Acknowledgments

The corresponding author’s post-doctoral study was supported by a University of Waikato Deputy Vice-Chancellor Freshwater Initiative. Support for this research by the Bay of Plenty Regional Council is gratefully acknowledged. Thanks to Chris McBride and Dr Jonathan Abell for providing the DYCD forcing file for years 2001–2012 and 2007–2014, respectively. Thanks to Dr Jonathan Abell for reading through the manuscript. An abstract of the manuscript was presented at the New Zealand Association Water Conference - Silverstream, Wellington (23–26 November 2015) with travel fund support provided by the University of Waikato.

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  1. Environmental Research Institute, Faculty of Science and Engineering, University of Waikato, Private Bag 3105, Hamilton, 3240, New Zealand

    Ayokunle Christopher Dada & David P. Hamilton

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  1. Ayokunle Christopher Dada
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Dada, A.C., Hamilton, D.P. Predictive Models for Determination of E. coli Concentrations at Inland Recreational Beaches. Water Air Soil Pollut 227, 347 (2016). https://doi.org/10.1007/s11270-016-3033-6

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