297 - Harmful Algal Blooms in Bay-Estuary Systems Under Future Climate: The Case of Apalachicola Bay, Florida

Harmful algal blooms (HABs) are some of water quality issues that can harm human health and lead to fish kills and dead zone formation. Algae, as the primary producer in aquatic systems, can be largely and easily influenced by environmental changes in waterbodies. In bay-estuary systems, factors such as ocean-exchange flow, sea level rise, freshwater inflow, and high flushing patterns have dynamic relationships with algal productivity. Climate change, which results in more intense rainstorms and warmer climate regimes, affects the occurrence of HABs by influencing those factors. Machine learning-based models are capable of learning complex patterns in large datasets and predicting HABs under different observed or hypothetical scenarios, including future climate variability. In this study, we use machine learning models (Decision Trees, Random Forest, and eXtreme Gradient Boosting), pre-validated with a monthly dataset of water quality and meteorological parameters monitored at 10 sites and covering a 20-year period (2002–2021), to predict HAB events under future climate (with increased air temperatures and precipitation) scenarios in complex settings of a bay-estuary system in the Florida panhandle, Apalachicola Bay. This system has a history of water pollution issues that have harmed the rich coastal ecosystem and raised socio-economic concerns. Our comparative analyses between HABs under historical and future climates evaluate the impact of climate change on Apalachicola Bay. The climate change analyses can assist the management authorities and coastal planners in making provocative decisions for reducing the occurrence of HABs and protecting marine ecosystems in future climates.