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Research on Structural Toughness of Railway City Network in Yellow River Basin and Case Study of Zhengzhou 7–20 Rainstorm Disaster

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  • Yajun Xiong

    (College of Urban and Environmental Science, Central China Normal University, Wuhan 430079, China)

  • Hui Tang

    (College of Urban and Environmental Science, Central China Normal University, Wuhan 430079, China
    School of Architecture and Urban Planning, Hunan City University, Yiyang 413000, China)

  • Xiaobo Tian

    (College of Urban and Environmental Science, Central China Normal University, Wuhan 430079, China)

Abstract

With the gradual networking of inter-city relations and the increase in acute impact and chronic stress, the measurement of the resilience of urban network structures is particularly prominent. Based on the construction of the urban network by passenger train trips in the Yellow River Basin, this paper analyzes and assesses the characteristics of the structural resilience of the urban network, and probes into the network resilience and urban response under the circumstances of node failure and line failure in Zhengzhou. The main conclusions are as follows: (1) The urban network in the Yellow River Basin was clearly hierarchical, with a significant spatial distribution of “low in the north and high in the south”, and the overall characteristics of “robustness” in small areas and “fragility” in large areas. The network connection forms were diversified and open. The network transmission efficiency was high, and the edge cities depended on the core cities with prominent characteristics, and the risk load of regional core cities rose. (2) The network structure was “robust” as it maintained high operational efficiency and connectivity under random attacks. Under deliberate attacks, the city network operated efficiently with a small increase in connectivity before the 60% threshold, and after the threshold, the overall network started to split into many sub-networks, and the network fragmentation gradually increased until the network collapsed. (3) Zhengzhou node failure and line failure states in the Yellow River Basin urban network were resilient, in the sense that when suffering important nodes and lines going down it could still maintain good network operation efficiency, and the core nodes in the impact of natural disasters could adapt to the destructive nature of the network through the urban network structure self-regulation.

Suggested Citation

  • Yajun Xiong & Hui Tang & Xiaobo Tian, 2022. "Research on Structural Toughness of Railway City Network in Yellow River Basin and Case Study of Zhengzhou 7–20 Rainstorm Disaster," Sustainability, MDPI, vol. 14(19), pages 1-17, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12515-:d:930784
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    References listed on IDEAS

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    1. Christopher G. Burton, 2015. "A Validation of Metrics for Community Resilience to Natural Hazards and Disasters Using the Recovery from Hurricane Katrina as a Case Study," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 105(1), pages 67-86, January.
    2. Lordan, Oriol & Sallan, Jose M. & Escorihuela, Nuria & Gonzalez-Prieto, David, 2016. "Robustness of airline route networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 18-26.
    3. Suleiman Hassan Otuoze & Dexter V. L. Hunt & Ian Jefferson, 2021. "Neural Network Approach to Modelling Transport System Resilience for Major Cities: Case Studies of Lagos and Kano (Nigeria)," Sustainability, MDPI, vol. 13(3), pages 1-20, January.
    4. Chan, Ho-Yin & Chen, Anthony & Li, Guoyuan & Xu, Xiangdong & Lam, William, 2021. "Evaluating the value of new metro lines using route diversity measures: The case of Hong Kong's Mass Transit Railway system," Journal of Transport Geography, Elsevier, vol. 91(C).
    5. Jungyeol Hong & Reuben Tamakloe & Soobeom Lee & Dongjoo Park, 2019. "Exploring the Topological Characteristics of Complex Public Transportation Networks: Focus on Variations in Both Single and Integrated Systems in the Seoul Metropolitan Area," Sustainability, MDPI, vol. 11(19), pages 1-26, September.
    6. Jialu Shi & Xuan Wang & Fuyi Ci & Kai Liu, 2022. "Spatiotemporal Characteristics and Patterns of the COVID-19 Pandemic in China: An Empirical Study Based on 413 Cities or Regions," IJERPH, MDPI, vol. 19(4), pages 1-16, February.
    7. Chao Fang & Piao Dong & Yi-Ping Fang & Enrico Zio, 2020. "Vulnerability analysis of critical infrastructure under disruptions: An application to China Railway High-speed," Journal of Risk and Reliability, , vol. 234(2), pages 235-245, April.
    8. Dirk Helbing, 2013. "Globally networked risks and how to respond," Nature, Nature, vol. 497(7447), pages 51-59, May.
    9. Yi Ge & Wen Dou & Haibo Zhang, 2017. "A New Framework for Understanding Urban Social Vulnerability from a Network Perspective," Sustainability, MDPI, vol. 9(10), pages 1-16, September.
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