Urban Waterlogging Risk Assessment Based on the Dynamic Response of Surface–Underground Transportation Networks

In order to improve the assessment of the dynamic risk of urban waterlogging, this study addresses the limitations of existing methods in capturing the responses of surface roads and subway systems to inundation, as well as the resulting spatiotemporal risks. Using the Hanyang District in Wuhan as a case study, the research proposes a framework for assessing urban waterlogging risks based on the dynamic inundation responses of surface and underground transport systems under various rainfall scenarios. The waterlogging process is simulated using seven representative rainfall scenarios with a hydrodynamic model that integrates a one-dimensional pipe network, a two-dimensional surface overland flow model, and a generalized underground space model. A coupled road–subway transportation network is developed to analyze traffic capacity degradation, path redistribution, and cascading failures caused by waterlogging disturbances. Quantified dynamic response indicators are integrated into the H-E-V-C framework to assess dynamic urban waterlogging risk. The results indicate that direct failure caused by water accumulation is typically the primary catalyst for extensive degradation of the transportation network, while the expansion of congestion and localized overload failures further exacerbate cascading effects. Different rainfall patterns influence not only peak risk but also the duration and spatial development of high-risk areas. Incorporating the dynamic response of the transport system enables a more accurate assessment of the degradation of emergency accessibility and the ongoing accumulation of localized high-risk areas. These findings highlight the importance of dynamic risk assessment in identifying time-varying urban vulnerabilities and supporting the planning of sustainable urban drainage, traffic management, and phased early warning systems.