The SCCF Marine Lab collaborated with the University of Florida (UF), University of South Florida (USF), and North Carolina State University (NCSU) scientists on a next-day prediction model to help water managers be better informed about harmful algal blooms.

The Marine Lab hosted the researchers and provided data from SCCF’s River, Estuary and Coastal Observing Network (RECON) and field campaigns in support of the research. 

The study, published in the March 2025 issue of Journal of Environmental Management, developed a statistical risk forecasting framework for the Caloosahatchee River and Estuary, which receives engineered water releases from the eutrophic Lake Okeechobee, as well as hydrologic inputs from the surrounding watershed. 

“In a highly managed system, such as the Caloosahatchee, there are opportunities to provide recommendations on water releases based on the current conditions provided by RECON,” Marine Lab Director Eric Milbrandt.

“The research team sought to unravel the complexities of the system and identify drivers of algal blooms. This provides a decision support tool that is more user-friendly for water managers.”

Milbrandt served as co-Principal Investigator (PI) on the project, along with David Kaplan, a professor with the Engineering School of Sustainable Infrastructure and Environment in the Herbert Wertheim College of Engineering and director of the Howard T. Odum Center for Wetlands. Mauricio Arias, an associate professor at USF also helped lead the study.

The SCCF Marine Lab’s location at Tarpon Bay on Sanibel Island made it a perfect host for the study. The lab’s real-time RECON data and long-term data sets also assisted in the development of the model.

“We have collected water samples and analyzed nutrients and chlorophyll monthly in the Caloosahatchee since 2018. There were 15 sites from Lake Okeechobee to the Gulf of Mexico,” said Milbrandt. 

For this particular analysis, the study used chlorophyll data from discrete samples. These are lab-analyzed samples, which provide the traditional methodology. The RECON data were used in other parts of the study, but for this analysis, monthly water samples using standard lab analysis were used.  

UF assistant professor Elise Morrison, as well as NCSU’s Maria Menchu Maldonado and Natalie Nelson, also contributed to the study.

Using water samples as well as computer algorithms, the researchers created prediction models based on Lake Okeechobee releases and the river’s watershed — the water run-off from the surrounding land. 

The models serve as an improvement from traditional forecasting models for algal blooms that are typically very complex and require much computing power. They are intended to inform daily decision-making, particularly for the South Florida Water Management District (SFWMD), which has made improving the health of the Caloosahatchee Estuary a state priority.