IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v120y2024i12d10.1007_s11069-024-06613-1.html
   My bibliography  Save this article

Risk analysis of rainstorm-urban lifeline system disaster chain based on the PageRank-risk matrix and complex network

Author

Listed:
  • Hai-xiang Guo

    (China University of Geosciences
    China University of Geosciences)

  • Xin-yu He

    (China University of Geosciences
    China University of Geosciences)

  • Xin-biao Lv

    (China University of Geosciences
    China University of Geosciences)

  • Yang Wu

    (China University of Geosciences)

Abstract

Rainstorm disasters cause serious threats to people’s lives and property. Enhancing emergency response and decision-making capabilities for rainstorm disasters is necessary. In this paper, 87 rainstorm disasters worldwide were first analysed, and secondary events across 15 urban lifeline systems were summarized. Based on the obtained findings and the characteristics of rainstorm disaster evolution and complex network theory, a model of rainstorm disaster chains in urban lifeline systems was constructed, and both partial and overall analyses of this model were performed. With the use of the PageRank risk matrix method, quantitative node risk levels were calculated for different parts of the model, and complex network theory was applied to assess the overall chain risk. The results showed that the highest risk disaster chain was flood → houses submerged or collapsed → road damaged → traffic congestion or paralysis. The most important node was traffic congestion or paralysis, underlining the acute need for emergency response measures in urban traffic systems during rainstorm disasters. Overall, this research provides a crucial direction for preventing rainstorm disasters in urban lifeline systems.

Suggested Citation

  • Hai-xiang Guo & Xin-yu He & Xin-biao Lv & Yang Wu, 2024. "Risk analysis of rainstorm-urban lifeline system disaster chain based on the PageRank-risk matrix and complex network," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(12), pages 10583-10606, September.
    • Handle: RePEc:spr:nathaz:v:120:y:2024:i:12:d:10.1007_s11069-024-06613-1
    DOI: 10.1007/s11069-024-06613-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-024-06613-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-024-06613-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Kai & Wang, Ming & Zhu, Weihua & Wu, Jinshan & Yan, Xiaoyong, 2018. "Vulnerability analysis of an urban gas pipeline network considering pipeline-road dependency," International Journal of Critical Infrastructure Protection, Elsevier, vol. 23(C), pages 79-89.
    2. Fotouhi, Hossein & Moryadee, Seksun & Miller-Hooks, Elise, 2017. "Quantifying the resilience of an urban traffic-electric power coupled system," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 79-94.
    3. Heracleous, Constantinos & Kolios, Panayiotis & Panayiotou, Christos G. & Ellinas, Georgios & Polycarpou, Marios M., 2017. "Hybrid systems modeling for critical infrastructures interdependency analysis," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 89-101.
    4. Chen, Duanbing & Lü, Linyuan & Shang, Ming-Sheng & Zhang, Yi-Cheng & Zhou, Tao, 2012. "Identifying influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1777-1787.
    5. Nan, Cen & Sansavini, Giovanni, 2015. "Multilayer hybrid modeling framework for the performance assessment of interdependent critical infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 10(C), pages 18-33.
    6. Zhao, Chen & Li, Nan & Fang, Dongping, 2018. "Criticality assessment of urban interdependent lifeline systems using a biased PageRank algorithm and a multilayer weighted directed network model," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 100-112.
    7. Xianhua Wu & Ji Guo, 2021. "Economic Impacts and Emergency Management of Disasters in China," Springer Books, Springer, edition 1, number 978-981-16-1319-7, December.
    8. Qiyuan Wang & Jundong Hou, 2023. "Hazard assessment of rainstorm-geohazard disaster chain based on multiple scenarios," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(1), pages 589-610, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Songtao Yu & Yuxian Ke & Qian Kang & Wenzhe Jin & Haifeng Zhong & Danyan Cheng & Fading Wu & Hongwei Deng, 2025. "Disaster Chain Evolution and Risk Mitigation in Non-Coal Underground Mines with Fault Zones: A Complex Network Approach," Sustainability, MDPI, vol. 17(12), pages 1-21, June.
    2. Tianliang Zhu & Hui Li & Yixuan Wu & Yuzhe Jiang & Jie Pan & Zhenhua Dai, 2025. "Resilience Assessment of Urban Bus–Metro Hybrid Networks in Flood Disasters: A Case Study of Zhengzhou, China," Sustainability, MDPI, vol. 17(10), pages 1-18, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhou, Shenghua & Yang, Yifan & Ng, S. Thomas & Xu, J. Frank & Li, Dezhi, 2020. "Integrating data-driven and physics-based approaches to characterize failures of interdependent infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 31(C).
    2. Zou, Qiling & Chen, Suren, 2019. "Enhancing resilience of interdependent traffic-electric power system," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    3. Galbusera, Luca & Trucco, Paolo & Giannopoulos, Georgios, 2020. "Modeling interdependencies in multi-sectoral critical infrastructure systems: Evolving the DMCI approach," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    4. Wei, Bo & Liu, Jie & Wei, Daijun & Gao, Cai & Deng, Yong, 2015. "Weighted k-shell decomposition for complex networks based on potential edge weights," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 277-283.
    5. Berahmand, Kamal & Bouyer, Asgarali & Samadi, Negin, 2018. "A new centrality measure based on the negative and positive effects of clustering coefficient for identifying influential spreaders in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 41-54.
    6. Oster, Matthew R. & Amburg, Ilya & Chatterjee, Samrat & Eisenberg, Daniel A. & Thomas, Dennis G. & Pan, Feng & Ganguly, Auroop R., 2024. "A tri-level optimization model for interdependent infrastructure network resilience against compound hazard events," International Journal of Critical Infrastructure Protection, Elsevier, vol. 47(C).
    7. Sheikhahmadi, Amir & Nematbakhsh, Mohammad Ali & Shokrollahi, Arman, 2015. "Improving detection of influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 833-845.
    8. Wang, Xiaojie & Zhang, Xue & Zhao, Chengli & Yi, Dongyun, 2018. "Effectively identifying multiple influential spreaders in term of the backward–forward propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 404-413.
    9. Wei, Daijun & Deng, Xinyang & Zhang, Xiaoge & Deng, Yong & Mahadevan, Sankaran, 2013. "Identifying influential nodes in weighted networks based on evidence theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2564-2575.
    10. Chaharborj, Sarkhosh Seddighi & Nabi, Khondoker Nazmoon & Feng, Koo Lee & Chaharborj, Shahriar Seddighi & Phang, Pei See, 2022. "Controlling COVID-19 transmission with isolation of influential nodes," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    11. Wu, Tao & Xian, Xingping & Zhong, Linfeng & Xiong, Xi & Stanley, H. Eugene, 2018. "Power iteration ranking via hybrid diffusion for vital nodes identification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 802-815.
    12. Zhao, Zhili & Liu, Xupeng & Sun, Yue & Zhang, Nana & Hu, Ahui & Wang, Shiling & Tu, Yingyuan, 2025. "Influence maximization based on bottom-up community merging," Chaos, Solitons & Fractals, Elsevier, vol. 193(C).
    13. Chen, Yahong & Li, Jinlin & Huang, He & Ran, Lun & Hu, Yusheng, 2017. "Encouraging information sharing to boost the name-your-own-price auction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 108-117.
    14. Zhou, Ming-Yang & Xiong, Wen-Man & Wu, Xiang-Yang & Zhang, Yu-Xia & Liao, Hao, 2018. "Overlapping influence inspires the selection of multiple spreaders in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 76-83.
    15. Zhe Li & Xinyu Huang, 2023. "Identifying Influential Spreaders Using Local Information," Mathematics, MDPI, vol. 11(6), pages 1-14, March.
    16. Ahmadi, Somayeh & Saboohi, Yadollah & Vakili, Ali, 2021. "Frameworks, quantitative indicators, characters, and modeling approaches to analysis of energy system resilience: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    17. Yan, Jiaye & Zhou, Jiaying & Wu, Zhaoyan, 2019. "Structure identification of unknown complex-variable dynamical networks with complex coupling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 256-265.
    18. Faxu Li & Hui Xu & Liang Wei & Defang Wang, 2023. "RETRACTED ARTICLE: Identifying vital nodes in hypernetwork based on local centrality," Journal of Combinatorial Optimization, Springer, vol. 45(1), pages 1-13, January.
    19. Wang, Jingjing & Xu, Shuqi & Mariani, Manuel S. & Lü, Linyuan, 2021. "The local structure of citation networks uncovers expert-selected milestone papers," Journal of Informetrics, Elsevier, vol. 15(4).
    20. Xiao, Yunpeng & Zhang, Li & Li, Qian & Liu, Ling, 2019. "MM-SIS: Model for multiple information spreading in multiplex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 135-146.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:120:y:2024:i:12:d:10.1007_s11069-024-06613-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.