Evaluating the Dynamic Comprehensive Resilience of Urban Road Network: A Case Study of Rainstorm in Xi’an, China

Yilin Hong, Zhan Zhang (), Xinyi Fang and Linjun Lu
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Yilin Hong: Department of Traffic Engineering, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Zhan Zhang: School of Design, Shanghai Jiao Tong University, Shanghai 200240, China
Xinyi Fang: Department of Traffic Engineering, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Linjun Lu: Department of Traffic Engineering, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Land, 2024, vol. 13, issue 11, 1-24

Abstract: Rainstorms and flooding are among the most common natural disasters, which have a number of impacts on the transport system. This reality highlights the importance of understanding resilience—the ability of a system to resist disruptions and quickly recover to operational status after damage. However, current resilience assessments often overlook transport network functions and lack dynamic spatiotemporal analysis, posing challenges for comprehensive disaster impact evaluations. This study proposes an SR-PR-FR comprehensive resilience evaluation model from three dimensions: structure resilience (SR), performance resilience (PR), and function resilience (FR). Moreover, a simulation model based on Geographic Information System (GIS) and Simulation of Urban MObility (SUMO) is developed to analyze the dynamic spatial–temporal effects of a rainstorm on traffic during Xi’an’s evening rush hour. The results reveal that the southwest part of Xi’an is most prone to being congested and slower to recover, while downtown flooding is the deepest, severely affecting emergency services’ efficiency. In addition, the road network resilience returns to 70% of the normal values only before the morning rush the next day. These research results are presented across both temporal and spatial dimensions, which can help managers propose more targeted recommendations for strengthening urban risk management.

Keywords: rainstorm; resilience; traffic performance; network structure; urban function (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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