Urban flooding has emerged as a significant challenge for densely populated cities, particularly in the context of increasing extreme rainfall events. This study focuses on the Guangdong-Hong Kong-Macao Greater Bay Area, developing a “hazard-exposure-vulnerability” framework to assess flood risks and resource equity using a variety of data sources. By employing a Bayesian-optimized LightGBM-SHAP method, the study uncovers the mechanisms underlying key disaster-inducing factors. Additionally, the distribution of flood defense resources is evaluated for spatial inequities using the Dagum Gini coefficient and Lorenz curve. The findings indicate that flood risk decreases from coastal to inland areas, with high-risk zones concentrated in core cities and densely riverine regions. There is a pronounced spatial imbalance in the allocation of safety resources, with the fragmentation of planning and infrastructure isolation in emerging areas exacerbating risk exposure. Key disaster drivers shift from topographical and physical factors to hydrological and ecological factors as risk levels rise. Impervious surface rate and vegetation coverage are identified as critical variables influencing overall flood risk. This research integrates risk mechanism analysis with equity-based assessments, offering scientific support and policy recommendations for climate-adaptive urban planning.