Coastal algal blooms, driven by complex land–sea interactions, pose widespread ecological risks. Integrating process‑based modeling with remote sensing (RS) provides a powerful approach to investigate bloom dynamics. Here, we present a land–sea coupled modeling framework that treats deltaic rivers as critical transition zones, applied to the Pearl River Estuary (PRE) from 2002 to 2024. The model quantifies terrestrial water and nutrient fluxes. Both the extent and intensity of blooms in the PRE declined over the study period, primarily due to reduced terrestrial total phosphorus (TP) loads linked to enhanced wastewater treatment and afforestation in the Pearl River Basin. RS offered a cost‑effective means of validating model results, while simulations compensated for cloud‑related data gaps, improving characterization of blooms in optically complex waters. Anthropogenic measures were the dominant driver of the overall decline in bloom occurrence, whereas climate variability chiefly influenced spatial redistribution. This integrated framework advances understanding of coastal bloom patterns and their drivers from a basin‑to‑coast perspective, supporting marine management and conservation. The combined use of process‑based modeling and RS provides a transferable methodology for coastal algal bloom research.