Phenological Patterns of Coastal Algal Blooms in the optically complex waters of the northern Patagonian Continental Shelf: a remote sensing approach

Understanding the spatial and temporal variability of chlorophyll-a (Chl-a) is crucial for assessing phytoplankton dynamics and ecosystem productivity in coastal waters. In this study, we characterized phytoplankton biomass variability in El Rincón, a shallow and biologically productive coastal region in the Patagonian Continental Shelf, using as a proxy 7-years (2017-2024) of Sentinel-3 OLCI satellite data and a regionally validated algorithm (MuRB&NDCI). This model provides more accurate Chl-a estimates compared to traditional algorithms, particularly in optically complex waters. Self-organizing maps (SOM) neural network was applied to identify four distinct bio-geographical regions with unique bloom dynamics. The phenological estimates revealed phytoplankton blooms typically initiate in fall (March), peak during winter (May–August), and are more pronounced near the Bahía Blanca Estuary (BBE), where nutrient and sediment inputs drive high productivity. The findings presented in this work highlight the utility of Optical Water Class based algorithms for capturing the fine-scale spatiotemporal variability of Chl-a in coastal systems. This study advances our understanding of phytoplankton dynamics in El Rincón and underscores the importance of customized satellitederived approaches for monitoring and managing productivity in shallow coastal environments.