Refined urban flood risk assessment serves as a fundamental safeguard for urban sustainability. However, most studies based on scenario analysis method tend to rely on a single risk evaluation criterion, with limited consideration of applicability differences arising from underlying computational principles. Furthermore, as flood events are inherently dynamic spatial–temporal processes, most studies often overlook the three-dimensional characteristics of flood risk, particularly the connectivity of risk in physically adjacent spaces. To address these issues, this paper proposes a comprehensive flood risk assessment framework that integrates the spatial–temporal characteristics of disaster-causing factors. An improved analysis method for grid-scale flood assessment is proposed based on the comprehensive mechanical analysis method and the drowning factor. In addition, a quantitative approach for characterizing the spatial aggregation of urban flood risk is established using risk thresholds and aggregation area thresholds. These methods are then integrated through a combination weighting–cluster analysis framework for comprehensive flood risk assessment. The results show that the improved analysis method can better reflect the change in risk of flow velocity and water depth combined. Spatiotemporally, the Yinshan Road and western section of the Dongzhong Road, exhibiting high localized risk, moderate overall risk, high risk on the time scale and high spatial agglomeration status, are comprehensively assessed as extremely high-risk flooded zones. The proposed framework effectively characterizes the spatial–temporal distribution of disaster-causing factors, providing a scientific basis for disaster prevention and contributing to urban sustainability.
Xu et al. (2026) studied this question.