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Road criticality assessment to improve commutes during floods

  • Huiting Chen
  • , Hongxin Zhang
  • , Sung Gheel Jang
  • , Xiaoyan Liu
  • , Lijun Xing
  • , Zihao Wu
  • , Lin Zhang
  • , Yaolin Liu
  • , Cuizhen Chen
  • Wuhan University
  • Beijing Normal University
  • Hubei University
  • China University of Mining and Technology
  • Wuhan Institute of Water Science Researching in Hubei Province

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Flooding undermines the functionality of road links, leading to commute disruption, such as increased commuting time and immobility. Therefore, identifying the critical roads under different flood scenarios is of great significance for transportation planning to minimize flood risk. Previous studies on the road criticality under pluvial floods have focused on mostly structural characteristics of the roads, lacking the quantification of the flood impact on traffic. We employed an integrated framework coupling pluvial flood modeling with commute simulation to assess the criticality of flooded road links under three scenarios (10, 30, and 50 year floods). The output of the flood modeling was used to reconstruct the road network. The routes of each individual commuter under a business as usual (BAU) scenario and three flood scenarios were obtained from the commute simulation. As the flood return period increased, the distribution of traffic flow became more uneven. The road criticality assessment revealed that greater flood impact on roads was closely related to the proximity of water bodies, low-lying topography, and greater commute demands of the region and provided evidence to prioritize locations for interventions. This study helps understand the resilience of transportation systems during floods, thereby enabling practitioners to design effective strategic plans in terms of emergency response, risk management, and urban planning.

Original languageEnglish
Article number119592
JournalJournal of Environmental Management
Volume349
DOIs
StatePublished - Jan 1 2024

Keywords

  • Commute simulation
  • Flood scenarios
  • LBS big data
  • Road criticality

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