USGS

Water-Resources Investigations Report 98-4241

In cooperation with the Ohio Water Development Authority, Northeast Ohio Regional Sewer District, Ohio Lake Erie Office, Cuyahoga County Sanitary Engineers, and Cuyahoga River Community Planing Organization

Factors Affecting Escherichia coli Concentrations at Lake Erie Public Bathing Beaches

By Donna S. Francy and Robert A. Darner


The environmental and water-quality factors that affect concentrations of Escherichia coli (E. coli) in water and sediment were investigated at three public bathing beachesEdgewater Park, Villa Angela, and Sims Parkin the Cleveland, Ohio metropolitan area. This study was done to aid in the determination of safe recreational use and to help water- resource managers assess more quickly and accurately the degradation of recreational water quality.

Water and lake-bottom sediments were collected and ancillary environmental data were compiled for 41 days from May through September 1997. Water samples were analyzed for E. coli concentrations, suspended sediment concentrations, and turbidity. Lake- bottom sediment samples from the beach area were analyzed for E. coli concentrations and percent dry weight. Concentrations of E. coli were higher and more variable at Sims Park than at Villa Angela or Edgewater Park; concentrations were lowest at Edgewater Park. Time-series plots showed that short-term storage (less than one week) of E. coli in lake-bottom sediments may have occurred, although no evidence for long-term storage was found during the sampling period. E. coli concentrations in water were found to increase with increasing wave height, but the resuspension of E. coli from lake-bottom sediments by wave action could not be adequately assessed; higherwave heights were often associated with the discharge of sewage containing E. coli during or after a rainfall and wastewater-treatment plant overflow.

Multiple linear regression (MLR) was used to develop models to predict recreational water quality at the in water. The related variables included turbidity, antecedent rainfall, antecedent weighted rainfall, volumes of wastewater-treatment plant overflows and metered outfalls (composed of storm-water runoff and combined-sewer overflows), a resuspension index, and wave heights. For the beaches in this study, wind speed, wind direction, water temperature, and the prswimmers were not included in the model because they were shown to be statistically unrelated to E. coli concentrations.

From the several models developed, one model was chosen that accounted for 58 percent of the variability in E. coli concentrations. The chosen MLR model contained weighted categorical rainfall, beach-specific turbidity, wave height, and terms to correct for the different magnitudes of E. coli concentrations among the three beaches. For 1997, the MLR model predicted the recreational water quality as well as, and in some cases better than, antecedent E. coli concentrations (the current method). The MLR model improved the sensitivity of the prediction and the percentage of correct predictions over the current method; however, the MLR model predictions still erred to a similar degree as the current method with regard to false negatives. A false negative would allow swimming when, in fact, the bathing water standard was exceeded.

More work needs to be done to validate the MLR model with data collected during other recreational seasons, especially during a season with a greater frequency and intensity of summer rains. Studies could focus on adding to the MLR model other environmental and water-quality variables that improve the predictive ability of the model. These variables might include concentrations of E. coli in deeper sediments outside the bathing area, the direction of lake currents, site-specific-rainfall amounts, time-of-day information on overflows and metered outfalls, concentrations of E. coli in treated wastewater-treatment plant effluents, and occurrences of sewage-line breaks. Rapid biological or chemical methods for determination of recreational water quality could also be used as variables in model refinements. Possible methods include the use of experimental rapid assay methods for determination of E. coli concentrations or other fecal indicators and the use of chemical tracers for fecal contamination, such as coprostanol (a degradation product of cholesterol) or caffeine.


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