Dynamic evolution and scenario-based prediction of urban flood resilience: A system dynamics modeling approach in Kunming, China

Abstract

The interplay between global climate change and urbanization has exacerbated urban flood disaster risks. However, disaster prevention efforts are often hampered by an insufficient understanding of flood mechanisms and their drivers. To address this issue, this study combines the Pressure-State-Response (PSR) framework with System Dynamics (SD) to develop a coupled PSR-SD model that spans the entire disaster cycle. Focusing on the main urban area of Kunming, China, this study established a dynamic evaluation index system for flood resilience from 2010 to 2030, systematically analyzing its intrinsic driving mechanisms. Five development scenarios—business-as-usual, economic development priority, environmental protection priority, extreme climate challenge, and coordinated development—were designed to quantitatively project flood resilience evolution trends under distinct pathways from 2023 to 2030. Key findings include: (1) Kunming's flood resilience evolution exhibits a three-phase trajectory (“decline-stabilization-recovery”), demonstrating spatiotemporal coupling with urban developmental stages. (2) A 2-year policy effect lag period exists for flood control engineering measures, revealing temporal cost characteristics in resilience-oriented urban development. (3) Multi-scenario simulations indicate that the coordinated development scenario achieves the optimal resilience index (0.8807) by 2030, outperforming the extreme climate scenario by 18.12 %, confirming the marginal flood prevention benefit advantages of multidimensional coordinated governance. This study further discusses the proactive significance of integrated governance strategies in enhancing urban flood resilience, providing dynamic decision-making support for resilient city planning.