System dynamics approach to extreme weather adaptation: Dynamic assessment and optimization of urban resilience in Shenzhen

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Under the dual pressures of intensifying global warming and rapid urbanization, conventional static assessment frameworks struggle to capture dynamic interactions and nonlinear characteristics within complex urban subsystems. This study develops an integrated urban resilience assessment model by synthesizing entropy method, factor analysis, and system dynamics (SD), establishing a comprehensive indicator system encompassing ecological, social, economic, and infrastructural dimensions through a case study of Shenzhen. Key findings reveal: (1) The composite urban resilience index demonstrated a sustained annual growth rate of 1.81% during 2000-2022, primarily driven by infrastructural resilience enhancement. (2) SD simulations identified critical resilience tipping points, showing that urban systems transition from vulnerability traps to positive adaptation trajectories when environmental governance growth rates exceed 0.8 times the precipitation intensity escalation rate. (3) Sensitivity analysis revealed urban resilience exhibits highest responsiveness to economic inputs. The quantified thresholds proposed in this research provide actionable policy references for resilience optimization, particularly emphasizing the necessity for coastal megacities to prioritize infrastructural reinforcement while maintaining sustained environmental governance investments to effectively address climate change challenges.