Assessment of Urban Flood Resilience Under a Novel Framework and Method: A Case Study of the Taihu Lake Basin

Urban flooding poses escalating threats to socioeconomic stability and human safety, exacerbated by urbanization and climate change. While urban flood resilience (UFR) has emerged as a critical framework for flood risk management, existing studies often overlook the systemic integration of post-disaster recovery capacity and multidimensional interactions in UFR assessment. This study develops a novel hazard–vulnerability–exposure–defense capacity–recovery capacity (HVEDR) framework to address research gaps. We employ a hybrid game theory combined weight method (GTCWM)-TOPSIS approach to evaluate UFR in China’s Taihu Lake Basin (TLB), a region highly vulnerable to monsoon- and typhoon-driven floods. Spanning 1999–2020, the analysis reveals three key insights: (1) weight allocation via GTCWM identifies defense capacity (0.224) and hazard (0.224) as dominant dimensions, with drainage pipeline density (0.091), flood-season precipitation (0.087), and medical capacity (0.085) ranking as the top three weighted indicators; (2) temporal trends show an overall upward trajectory in UFR, interrupted by a sharp decline in 2011 due to extreme hazard events, with Shanghai and Hangzhou exhibiting the highest UFR levels, contrasting Zhenjiang’s persistently low UFR; (3) spatial patterns reveal stronger UFR in southern and eastern areas and weaker resilience in northern and western regions. The proposed HVEDR framework and findings provide valuable insights for UFR assessments in other flood-prone basins and regions globally.

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Publication Details

Journal
Land
Published
2025-06-22
DOI
https://doi.org/10.3390/land14071328
Citations
1
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
1.11
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article

Assessment of Urban Flood Resilience Under a Novel Framework and Method: A Case Study of the Taihu Lake Basin

Xiaoping Gao, Jia-Xing Zhong, Tingting Cui, Kaidong Lu et al.
1 citations
Land
Flood Risk Assessment and Management
1.11
article

Assessment of Urban Flood Resilience Under a Novel Framework and Method: A Case Study of the Taihu Lake Basin

Xiaoping Gao, Jia-Xing Zhong, Tingting Cui, Kaidong Lu, Yong Liu, Zijiang Zhou, Yintang Wang
article en
1 citations

Abstract

Urban flooding poses escalating threats to socioeconomic stability and human safety, exacerbated by urbanization and climate change. While urban flood resilience (UFR) has emerged as a critical framework for flood risk management, existing studies often overlook the systemic integration of post-disaster recovery capacity and multidimensional interactions in UFR assessment. This study develops a novel hazard–vulnerability–exposure–defense capacity–recovery capacity (HVEDR) framework to address research gaps. We employ a hybrid game theory combined weight method (GTCWM)-TOPSIS approach to evaluate UFR in China’s Taihu Lake Basin (TLB), a region highly vulnerable to monsoon- and typhoon-driven floods. Spanning 1999–2020, the analysis reveals three key insights: (1) weight allocation via GTCWM identifies defense capacity (0.224) and hazard (0.224) as dominant dimensions, with drainage pipeline density (0.091), flood-season precipitation (0.087), and medical capacity (0.085) ranking as the top three weighted indicators; (2) temporal trends show an overall upward trajectory in UFR, interrupted by a sharp decline in 2011 due to extreme hazard events, with Shanghai and Hangzhou exhibiting the highest UFR levels, contrasting Zhenjiang’s persistently low UFR; (3) spatial patterns reveal stronger UFR in southern and eastern areas and weaker resilience in northern and western regions. The proposed HVEDR framework and findings provide valuable insights for UFR assessments in other flood-prone basins and regions globally.

LandVol. 14(7)
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering (CN), Nanjing Hydraulic Research Institute (CN), Anhui and Huaihe River Institute of Hydraulic Research (CN)
Openalex Percentile: Top 23%
Flood Risk Assessment and Management
1.11
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