Modeling and application of urban waterlogging resilience assessment based on PSR–NES framework and analysis of driving mechanisms

ABSTRACT Extreme weather events are escalating globally, intensifying urban waterlogging disasters and endangering inhabitants and assets while hindering socio-economic progress. This study explores factors hindering cities' waterlogging disaster mitigation using urban resilience theory. It introduces a pressure–state–response (PSR)–natural–economic–social (NES) assessment model to evaluate urban waterlogging resilience, focusing on Nanjing as a key city in flood control. Flood scenarios are simulated using the MIKE model for different rainstorm recurrence periods. Urban flooding resilience is assessed with a hybrid approach. Geodetector analysis identifies primary resilience drivers. Results validate the PSR–NES composite resilience index, showing complex resilience patterns across the study area. High-resilience areas are mainly in the east and southeast, while low-resilience areas cluster along roads and low-lying communities. Key resilience indicators include waterlogging duration, inundation depth, warning capacity, economic density, and road accessibility. These factors interact with nonlinear enhancements and synergies. The study's insights can identify urban management or flood defense infrastructure deficiencies, guiding tailored flood defense strategies for stakeholders.