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NOWCASTING AND FORECASTING BEACH BACTERIA CONCENTRATION USING THE EPA VIRTUAL BEACH SOFTWARE
Citation:
FRICK, W. E. AND Z. GE. NOWCASTING AND FORECASTING BEACH BACTERIA CONCENTRATION USING THE EPA VIRTUAL BEACH SOFTWARE. Presented at IAGLR's 50th Annual Conference on Great Lakes Research, University Park, PA, May 28 - June 01, 2007.
Impact/Purpose:
A main objective of this task is to combine empirical and physical mechanisms in a model, known as Visual Beach, that
- is user-friendly
- includes point and non-point sources of contamination
- includes the latest bacterial decay mechanisms
- incorporates real-time and web-based ambient and atmospheric and aquatic conditions
- and has a predictive capability of up to three days to help avert potential beach closures.
Description:
Beaches are subject to closure when bacterial counts exceed water quality criteria. Many authorities base these decisions on sample counts, which typically require a day or more to analyze. Sometimes called the persistence model, because conditions are assumed to persist, experience shows that this approach often leads to poor decisions: beaches are often closed when they could be open and vice versa. Studies show mathematical models can outperform the persistence model. Many use multi-variable linear regression (MLR) that base predictions on explanatory variables, such as turbidity, temperature, rainfall, and other variables. Virtual Beach, software developed at EPA, does too. It has been used successfully to nowcast, the practice for using real-time variables to estimate existing bacteria concentrations. This work addresses the question, can weather and water forecasts be used to forecast beach conditions in advance? The answer is based on an analysis of 2006 Huntington Beach, Lake Erie beach data (by USGS, state, and local agencies), weather forecasts for nearby Cleveland-Hopkins international airport, and NOAA lake condition forecasts. A comparison of static and dynamic MLR models is also given.