This assessment framework demonstrates the role of fiscal capacity and drainage infrastructure in urban flood resilience.
Urban flood resilience assessment frameworks persistently suffer from three critical limitations: methodological fragmentation between physical and socioeconomic dimensions, overreliance on inaccessible multi-source data like remote sensing or proprietary datasets, and inadequate attention to causal mechanisms linking urban characteristics to resilience outcomes. This study addresses these gaps using a standardized Exposure-Sensitivity-Adaptability (ESA) framework applied across 41 Yangtze River Delta cities. The yearbook-based approach ensures replicability for cities lacking specialized hydrological data. Entropy weighting objectively assigns importance based on inter-city variability, with subsequent mediation analysis unraveling causal pathways. Key findings demonstrate that per capita fiscal revenue dominates resilience outcomes, contributing 37.15% to adaptability by enabling proactive floodproofing investments. Drainage infrastructure density exhibits counterintuitive negative effects, confirming the safe development paradox where higher pipe density correlates with reduced resilience. Population density indirectly erodes resilience by diluting fiscal resources per capita, a pathway undetected in bivariate models. GDP density enhances resilience through agglomeration economies but concurrently increases exposure magnitude. Road density significantly supports emergency response capabilities. This framework provides cities in developing economies with a low-cost, transferable tool for evidence-based planning without specialized hydrological data. Theoretically, it advances understanding of fiscal governance as a critical mediator between urban scale and resilience. Practically, it enables equitable cross-city benchmarking and prioritizes fiscal capacity building alongside performance-oriented infrastructure upgrades, transforming academic concepts into actionable strategies for flood-vulnerable regions.
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Чан et al. (2025) studied this question.
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