Resilience Assessment of Urban Bus–Metro Hybrid Networks in Flood Disasters: A Case Study of Zhengzhou, China

Tianliang Zhu, Hui Li (), Yixuan Wu, Yuzhe Jiang, Jie Pan and Zhenhua Dai
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Tianliang Zhu: Urban Mobility Institute, College of Transportation, Tongji University, Shanghai 201804, China
Hui Li: Urban Mobility Institute, College of Transportation, Tongji University, Shanghai 201804, China
Yixuan Wu: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, College of Transportation, Tongji University, Shanghai 201804, China
Yuzhe Jiang: Urban Mobility Institute, College of Transportation, Tongji University, Shanghai 201804, China
Jie Pan: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, College of Transportation, Tongji University, Shanghai 201804, China
Zhenhua Dai: Key Laboratory of Road and Traffic Engineering of the Ministry of Education, College of Transportation, Tongji University, Shanghai 201804, China

Sustainability, 2025, vol. 17, issue 10, 1-18

Abstract: Urban transportation systems, particularly integrated bus–metro networks, play a critical role in sustaining city functions but face significant vulnerability during extreme flood disasters. Taking Zhengzhou, China, as a case study, this study developed a comprehensive assessment model to evaluate the resilience of urban bus–metro hybrid networks under flood scenarios. First, a complex network-based bus–metro hybrid transportation network model was established, incorporating quantifiable flood disaster risk indices considering disaster-inducing factors, hazard-prone environments, and disaster-bearing entities. A cascading failure model was then constructed to simulate the propagation of node failures and passenger load redistribution during flood events. Subsequently, network resilience was evaluated using the topological metric of the relative size of the largest connected component and the functional metric of global efficiency. The analysis examined the influence of the load capacity sensitivity parameters α and β on resilience outcomes. Simulation results indicated that the parameter combination α = 0.8 and β = 2.0 yielded the highest resilience under the tested conditions, offering a balance between redundancy and the targeted protection of high-load nodes. Additionally, recovery strategies prioritizing nodes based on betweenness centrality significantly improved resilience outcomes. This study provides valuable insights and practical guidance for improving urban transportation resilience, assisting policymakers and planners in better mitigating flood disaster impacts.

Keywords: complex network; transportation resilience; urban transportation system; flood resilience (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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