Spatio-Temporal Evaluation and Attribution Analysis of Urban Flood Resilience in the Beijing–Tianjin–Hebei Region: A Multi-Method Coupling Approach

This is the authors' abstract. We don't add key points for this paper.

Urban floods increasingly threaten the mega-regions’ sustainable development, yet the pace and causes of change in urban flood resilience (UFR) remain elusive. This study proposes a new index system for UFR from three dimensions: resistance, recovery, and adaptability. The system includes 18 indicators across natural, economic, social, and infrastructure aspects. A comprehensive evaluation model combining entropy weighting, Criteria Importance Through Intercriteria Correlation (CRITIC), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods is developed and validated for the Beijing–Tianjin–Hebei (BTH) region of China, covering 2011–2022. Spatial dependence is diagnosed with global and local Moran’s I statistics, while an Extreme Gradient Boosting-Shapley Additive Explanations (XGBoost-SHAP) isolates the contribution of each driver. The results indicate that UFR in the BTH region exhibited a generally increasing but fluctuating trend. Spatially, UFR displays a pronounced gradient, with higher levels concentrated in the northwest and lower levels in the southeast. Significant spatial autocorrelation is observed, spatial autocorrelation strength ranging from 0.330 to 0.404. Key drivers contributing to UFR include urban slope, hydrological station density, per capita park green space area, and population density, all with SHAP importance values exceeding 0.02 (ranging from 0.0012 to 0.1343). These indicators collectively play a dominant role in shaping the region’s resilience dynamics, highlighting their crucial influence on sustainable urban development.