Predicting Algal Bloom Dynamics From Coastal Turbidity Front Movements Using Satellite Data and Numerical Modeling in Tide‐Dominated Coasts

Abstract

Algal bloom predictions remain challenging in coastal regions such as the East China Sea (ECS) because of limited in situ observations and inaccurate chlorophyll– a numerical predictions. Along tide–dominated coasts, phytoplankton growth is primarily light limited in summer because of tide–induced high turbidity. Satellite observations reveal that the optimal phytoplankton growth conditions occur exactly at the outer edges of turbidity fronts where light availability and nutrients converge, facilitating the formation of bloom initiation zones. Algal blooms generally expand coastward with the shoreward movement of turbidity fronts and dissipate as these fronts recede offshore. A U–Net based turbidity prediction model for ECS coasts was developed via numerical modeling of tidal data and satellite–derived turbidity data. This model could accurately predict the movements and offshore distances of turbidity fronts and could provide algal bloom dynamics 1–2 days in advance. This study provides new insights for early warning of algal blooms along tidal–dominated coasts.