{"id":1912,"date":"2023-11-01T19:45:15","date_gmt":"2023-11-01T19:45:15","guid":{"rendered":"https:\/\/live-usc-dornsife.pantheonsite.io\/uscseagrant\/?page_id=1912"},"modified":"2023-11-10T19:11:04","modified_gmt":"2023-11-10T19:11:04","slug":"safe-to-swim","status":"publish","type":"page","link":"https:\/\/dornsife.usc.edu\/uscseagrant\/safe-to-swim\/","title":{"rendered":"Safe to Swim"},"content":{"rendered":"\n\n\n\n\n \n \n\n\n\n\n\n\n\n
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\n Advancing an early warning system for California beach water quality \n <\/h2>\n\n\n<\/div>\n \n \n
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One issue common to populated coastlines is the higher risk of recreational that people who swim or surf in the water have a risk of getting sick from fecal indicator bacteria (FIB) such as <\/span>enterococci <\/span><\/i>and <\/span>Escherichia coli<\/span><\/i>. Usually, levels of FIB are low, but events like rain, an increase in stormwater run-off, waste-treatment plant overflows, changes in currents, and even wind can increase FIB levels. Accurate water quality data is critical for California\u2019s resource managers to keep swimmers safe on beaches. Still, there is often a two-day laboratory turnaround of beach water samples, potentially exposing beachgoers to contaminated water. Water quality managers are turning to forecast models, which usually require extensive, multi-year data sets to predict water quality accurately. University of Southern California (USC) Sea Grant funded a study to determine whether high-frequency sampling over a 1-2 day period could be sufficient to more efficiently develop predictive water quality models for \u201cdata-poor\u201d beaches where more extensive monitoring is unachievable.\u00a0<\/span><\/p>\n\n\n\n<\/div>\n \n \n <\/div>\n \n \n \n\n <\/div><\/div>\n\n\n\n\n \n \n\n\n\n\n\n\n\n

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Key Results<\/b>:<\/span><\/h3>\n