Predicting and Improving the Waterlogging Resilience of Urban Communities in China—A Case Study of Nanjing

In recent years, urban communities in China have been continuously affected by extreme weather and emergencies, among which the rainstorm waterlogging disasters pose a great threat to infrastructure personnel safety. Chinese governments issue series of prevention control policies, but mitigation still needs be optimized. The concept “resilience” has unique advantages field community disaster management, building resilient can effectively make up for limitations traditional top-down management. Therefore, this paper focuses on pre-disaster China, following idea “concept analysis–influencing factor identification–evaluation indicators selection–impact mechanism analysis–resilience simulation prediction–empirical research–disaster adaptation strategy formulation”. structural equation model BP neural network are used investigating existing anti-waterlogging capitals target predict future resilience. Based prediction model, combined with incentive restraint mechanisms, suggestions corrective measures put forward before occurrence waterlogging.