Integrating Multi-Source Geospatial Datasets with Hydrodynamic Models for Coastal Storm Surge Risk Assessment: A Case Study of Zhoushan, China

Coastal cities face substantial storm surge flood risk, yet detailed information on the urban functions exposed to inundation is often limited. This study presents an integrated, semi-quantitative framework for assessing storm surge risk in four subdistricts of Zhoushan, China. Points of interest (POIs), areas of interest (AOIs), OpenStreetMap (OSM) roads, and land-cover data were integrated to construct an Essential Urban Land Use/Cover (EULUC) map, which provided the spatial basis for assigning relative vulnerability to different land-use categories. Maximum inundation depths from Finite-Volume Community Ocean Model (FVCOM) simulations were used to classify inundation hazard under five typhoon central-pressure scenarios ranging from 955 to 915 hPa. The hazard classes and EULUC-based vulnerability were then combined through a hazard–vulnerability matrix to delineate risk zones for each scenario. The total area classified for storm surge risk increased from 1.25 km2 at 955 hPa to 47.90 km2 at 915 hPa, with the largest increase between the 945 and 935 hPa scenarios, from 4.69 to 34.69 km2. The composition of the classified area also shifted toward higher risk levels. Under the 915 hPa scenario, extremely high risk was the largest class, covering approximately 19.6 km2 (41%), followed by high risk at approximately 12.9 km2 (27%). The dominant risk class varied among subdistricts. High risk was the largest class in Donggang, whereas extremely high risk dominated in Shenjiamen and Lincheng. By identifying where severe inundation coincides with vulnerable urban functions, the framework supports scenario-based risk screening and helps prioritize locations for emergency preparedness and spatial planning.