An international team has developed a new, timelier method to identify harmful bacteria levels on recreational beaches. The team was led by researchers at the University of Miami (UM) Rosenstiel School of Marine and Atmospheric Science.
The tool offers more accurate health risk prediction model to better inform beach closure decisions.
The new model offers beach managers a better prediction tool to identify when closures are required to protect beachgoers from harmful bacteria.
"The development of this new model has allowed us, for the first time, to estimate contamination levels on beaches subject to non-point source pollution, in particular from beach sand and runoff from storms," said the authors of the study published in the journal Marine Pollution Bulletin
The new method provides beach health managers with an easily accessible computer model to predict harmful bacteria levels from all potential pollution sources.
The team optimized and validated their model using a 10-day monitoring data-set from the popular Virginia Beach in Miami, Florida.
The predictive model uses information on waves, tides, rainfall and solar radiation to more accurately predict harmful bacteria concentration and movement along the shore.
Direct sampling methods, currently in use, require a one-day laboratory analysis to access the health risk to humans at a particular beach.
Therefore, a 24 to 48 hour wait period after sampling is required before any beach closure or advisory is issued.