Intelligent identification and management of flood risk areas in high-density blocks from the perspective of flood regulation supply and demand matching

Global climate change has led to frequent extreme climate disasters, which are increasingly serious threats to high-density urban blocks. Flood risk mapping research is emerging from flood regulation (FR) supply and demand perspectives. However, the existing research on FR supply and demand in high-density blocks lacks effective models, intelligent technology, and risk-management applications. From the perspective of supply and demand matching of FR, this study constructed a method for identifying and managing flood-risk areas in highdensity blocks by integrating urban hydrological models and intelligent computing technology. SWMM was used to simulate the FR supply level of the high-density blocks under rainstorm conditions. The intelligent technology of the random forest model and entropy weight TOPSIS were used to calculate the demand level of FR. Flood risk management zones were identified by comparing supply and demand. Considering the Yuandang blocks in Xiamen, China, as the research scope, the results show that (1) with the increase in the recurrence period, the scope of the low-supply area of FR continues to expand, and the subcatchment areas with low-supply levels are concentrated in Lianqian West, Lakeside South, and Houdaixi Streets. (2) The high-demand areas for FR are mainly located in the high-intensity development blocks on the south side of Yandang Lake and the middle of Dongping Mountain. (3) Twenty (4.63%) subcatchment areas and 112 (3.00%) plot units belong to the high-risk areas of the low-supply, high-demand type, which can be divided into four categories and three levels of flood control zones. From the flood risk management perspective, the research results can provide a decision-making basis for land use and facility optimisation layouts of high-density blocks.