A dynamic impact assessment method for rainstorm waterlogging using land-use data

As a result of rapid urbanization and climate change, many large- and medium-sized cities in China frequently undergo urban disasters with severe impacts that result in many casualties, induce significant economic losses, and restrict sustainable social and economic development. Providing timely and accurate early warnings is the most effective measure for disaster prevention and mitigation before such disasters can impose severe impacts. In this study, we propose a dynamic impact assessment method for rainstorm waterlogging using land-use data. First, based on a detailed collection of disaster prevention and mitigation data, we construct an impact assessment index based on the assessment objects of this study. Then, a waterlogging simulation is performed, and the simulation results are found to meet the assessment requirements. Finally, we conduct an impact assessment every half hour during a heavy rainfall event and evaluate the performance of the proposed method by assessing the socioeconomic impact, object impact, industry impact, regional impact, and comprehensive impact of the event. These assessments produce valuable information for providing diverse and timely services in the event of urban waterlogging.