Science Inventory

NOWCASTING AND FORECASTING BEACH BACTERIA CONCENTRATIONS USING EPA VIRTUAL BEACH SOFTWARE

Citation:

FRICK, W. E. AND Z. GE. NOWCASTING AND FORECASTING BEACH BACTERIA CONCENTRATIONS USING EPA VIRTUAL BEACH SOFTWARE. Presented at ASLO 2007 Aquatic Sciences Meeting, Santa Fe, NM, February 04 - 09, 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.
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:

Evidence shows that traditional persistence-based beach closure decision making is inadequate, beaches are closed when they could be open and kept open when they should be closed. Intense interest is now focused on efforts to nowcast beach conditions using surrogate variables, such as turbidity, temperature, rainfall, and other variables. Contributing to the effort to alert to public, EPA developed the Virtual Beach software program to help users develop beach bacteria concentration models. Similar approaches have been used to develop beach advisories. In tests conducted during the summer of 2006, the authors found that the multi-variable linear regression statistical approach could be extended to forecasting using publicly available weather and water forecasts. Using data from the 2006 Huntington Beach, Lake Erie advisory project, 24 and 48 hour forecasts were found to be about as accurate as nowcasting results. It is hypothesized that the greater precision of some forecasts compensate for the decreasing accuracy of weather and water forecasts. Further forecasting tests of Virtual Beach are planned for the 2007 bathing season.

Record Details:

Record Type:DOCUMENT( PRESENTATION/ ABSTRACT)
Product Published Date:02/04/2007
Record Last Revised:12/04/2006
Record ID: 161505