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TESTING A BEACH BACTERIA MODEL IN LAKE MICHIGAN AND SOUTHERN CALIFORNIA
Citation:
Frick, W E., A P. Dufour, T. Khangaonkar, AND M Molina. TESTING A BEACH BACTERIA MODEL IN LAKE MICHIGAN AND SOUTHERN CALIFORNIA. Presented at Oceans 2003 Marine Technology and Ocean Science Conference, San Diego, CA, September 22-26, 2003.
Impact/Purpose:
A main objective of this task is to combine empirical and physical mechanisms in a model, known as Visual Beach, that
â— is user-friendly
â— includes point and non-point sources of contamination
â— includes the latest bacterial decay mechanisms
â— incorporates real-time and web-based ambient and atmospheric and aquatic conditions
â— and has a predictive capability of up to three days to help avert potential beach closures.
The suite of predictive capabilities for this software application can enhance the utility of new methodology for analysis of indicator pathogens by identifying times that represent the highest probability of bacterial contamination. Successful use of this model will provide a means to direct timely collection of monitoring samples, strengthening the value of the short turnaround time for sampling. Additionally, in some cases of known point sources of bacteria, such as waste water treatment plant discharges, the model can be applied to help guide operational controls to help prevent resulting beach closures.
Description:
Beach closures due to high bacterial concentrations deprive the public and disrupt the tourist industry. Almost half the Lake Michigan beaches are closed more than 10% of the time. In 1999 the six-mile long beach in Huntington Beach, California was closed in July and August. Due to long growth times, bacteria-related closures are generally based on samples collected 48 hours or more previously, so that many closures may not be justified by current conditions. Monitoring frequency can delay re-openings. Furthermore, bacteria have both human and animal origins, with different inherent risk to humans. Tests using polymerase chain reactions (PCR) that can determine criterion-level concentrations in less than two hours are coming into use and work is ongoing on determining bacterial origins based on DNA fingerprinting. These technologies will help protect the public, however, predictive models promise to help health officials post warnings in advance and, even better, prevent closures by helping sewage treatment plant managers apply optimal preventive disinfection, automatically metering or rerouting releases from combined sewer overflow retention basins, etc.. An existing version of the proposed model has been used to simulate the movement of the Orange County Sanitation District, California outfall plume, a major source. The results suggest the offshore waste field is generally not connected to high beach bacteria concentrations, an issue further addressed by the revised model by the addition of a line source, simulating beaches. In addition to revisiting the Orange County example, the new model is tested in southern Lake Michigan using 2002 West Beach (Indiana Dunes National Seashore) bacteria data, available current meter measurements, wind and other meteorological data, and hydrological and loading records of Burns Ditch, a major stream draining the area. More realistic results portraying near-shore and major source contributions are described. Combined with advances in species differentiation and pathogen identification (that will generally be associated with human sources), modeling may ultimately help to limit beach closures to events posing actual risk to humans.