Real-time detection of harmful algal blooms using GOCI II and buoy-based dissolved oxygen variations

Abstract

Harmful algal blooms (HABs) threaten aquatic ecosystems and water quality, necessitating timely monitoring. Traditional satellite observations, including high-frequency sensors like Geostationary Ocean Color Imager II (GOCI-II), are often hindered by cloud cover and low-light conditions, limiting their temporal resolution and coverage. We propose a real-time approach using diel variations in dissolved oxygen (DO) measured by buoys to detect HAB initiation and dynamics. By isolating biologically driven oxygen variation ( Obio) from physical processes, we identify increases in Obio, elevated temperature, and maximum DO as key HAB indicators. This method captures bloom activity under cloudy or low-light conditions when satellites fail. To enhance spatial coverage, we integrate buoy-based DO data with high-frequency GOCI-II satellite observations, providing hourly, all-weather bloom detection. While satellite or buoy observations alone face limitations, their integration overcomes traditional barriers. Our results demonstrate a robust tool for real-time HAB monitoring and early warning, supporting sustainable water resource management.