A multi-scenario urban resilience simulation study based on the system dynamics model

Scientific quantification of urban resilience can provide a basis for decision-making on the construction of resilient cities to ensure safe and high-quality urban development. This study used text mining and big data statistical analysis to construct an urban resilience evaluation index system from four dimensions: social, economic, infrastructure, and ecological, and constructed an urban resilience evaluation model based on the system dynamics approach to elucidate the interactions among the indicators. Taking 11 cities in the Yangtze River Economic Belt as study cases, four future development scenarios were set under Shared Socio-economic Pathways (SSPs), and the variations in the urban resilience index of each city to 2030 were simulated. The research results show that: (1) The resilience of the 11 cities currently shows an upward trend, but the stratification phenomenon is obvious, and the overall situation is high in the east and low in the west, high in the north and low in the south; (2) The variations of resilience index vary among cities under different scenarios, and in a comprehensive comparison, SSP1 is the optimal development path; (3) The resilience gap among the 11 cities will remain in the future, but the gap in the east-west direction may gradually decrease, while the gap in the north-south direction remains significant.