Urban flooding increasingly threatens human safety, infrastructure, and socio-economic systems due to rapid urbanization and climate change. Accurately assessing urban flood resilience is critical for informing disaster prevention, mitigation, and adaptation strategies. This study develops a process-oriented framework integrating the Driving force–Pressure–State–Response (DPSR)model and Natural–Economic–Social–Hazard (NESH) models to evaluate urban flood resilience across multiple rainfall scenarios, incorporating spatially explicit and dynamically weighted indicators for fine-grained sub-regional assessment. Applied to the central urban area of Zhengzhou City, China, the framework identifies spatial resilience patterns, key influencing indicators, and vulnerable zones. Results show that driving force resilience is moderate with lower values in central districts; pressure resilience declines systematically with increasing rainfall intensity; state resilience exhibits a ring-shaped spatial structure; and response resilience is concentrated in the urban core. Overall urban flood resilience decreases from 0.592 under moderate rainfall to 0.538 under extreme events. Simulation of grey-green infrastructure interventions, including stormwater pipe dredging and increased vegetation coverage, demonstrates substantial flood risk reduction under moderate rainfall but diminished effectiveness under extreme events. This framework provides a scientifically rigorous and actionable tool for urban flood resilience assessment, enabling identification of vulnerable zones and guiding targeted mitigation and urban planning strategies.
Di et al. (Tue,) studied this question.