Flash flood disaster risk evaluation based on geographic detector and interval number ranking method

Abstract Among natural disasters, flash floods are the most destructive events, causing significant damage to the economy and posing a serious threat to human life and property. Comprehensive risk assessment of these sudden floods is a key strategy to mitigate their impact. Accurate analysis of flash flood hazards can greatly enhance prevention efforts and inform critical decision‐making processes, ultimately improving our ability to protect communities from these fast‐onset disasters. This study analyzed the driving forces of flash flood disaster‐causing factors in Heilongjiang Province. Meanwhile, nine different categories of variables affecting the occurrence of flash floods were selected, and the degree of influence of each driving factor on flash floods was quantitatively analyzed, and the driving force analysis of the driving factors of flash floods in Heilongjiang Province was carried out by using the geographic probe model. This paper employs an uncertainty approach, utilizing a statistical‐based interval weight determination technique for evaluation indices and a two‐dimensional information‐based interval number sorting method. These methodologies are combined to construct a comprehensive flash flood risk assessment model. On this basis, the model was implemented in six regions within China's Heilongjiang province to evaluate and prioritize flash flood risks. The resulting risk ranking for these areas was as follows: Bayan Shuangcheng Boli Suibin Hailun Yian. The findings demonstrate that the interval number‐based evaluation method effectively handles uncertainty, providing a more reliable risk grading system. This approach, by leveraging modern scientific advances and risk quantification techniques, is crucial for improving disaster management and mitigating flash flood impacts.