IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v115y2023i3d10.1007_s11069-022-05632-0.html
   My bibliography  Save this article

Exploring the road icing risk: considering the dependence of icing-inducing factors

Author

Listed:
  • Qiang Liu

    (Harbin Institute of Technology, Nangang Dist)

  • Aiping Tang

    (Harbin Institute of Technology, Nangang Dist
    Harbin Institute of Technology)

  • Zhongyue Wang

    (Harbin Institute of Technology, Nangang Dist)

  • Buyue Zhao

    (Beijing Jiaotong University)

Abstract

This study reports a method to explore the icing risk of roads considering the dynamic dependence between icing-inducing factors. The joint distribution of inducing factors was first constructed by employing the Copula theory, which then yielded the possibility of icing events. Meanwhile, hazard zones and intensities of icing were proposed under different exceeding probabilities. After finishing the analysis of road vulnerability, the risk matrix was applied to conduct the icing risk for roads in the study area, which was then applied to the construction of the risk zoning map. Results show that there is an upper-tail dependence between extreme precipitation and the temperature of the study area in winter, which can be captured by the Gumbel Copula. Besides, the line of Hegang-Yichun maintains a high vulnerability. Further, the case application indicates that during March 2020, the traffic lines with a high icing risk are distributed around Fujin, Jiamusi, Hegang, and Qitaihe cities, and the Hegang-Yichun keeps the highest icing risk; while the low-risk lines are concentrated in the western part of the study area. This study is of great significance for the prevention and control of ice-snow disasters on the roads in cold regions.

Suggested Citation

  • Qiang Liu & Aiping Tang & Zhongyue Wang & Buyue Zhao, 2023. "Exploring the road icing risk: considering the dependence of icing-inducing factors," 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. 115(3), pages 2161-2178, February.
    • Handle: RePEc:spr:nathaz:v:115:y:2023:i:3:d:10.1007_s11069-022-05632-0
    DOI: 10.1007/s11069-022-05632-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-022-05632-0
    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/s11069-022-05632-0?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Nelsen, Roger B., 1997. "Dependence and Order in Families of Archimedean Copulas," Journal of Multivariate Analysis, Elsevier, vol. 60(1), pages 111-122, January.
    2. Qiang Liu & Delong Huang & Aiping Tang & Xiaosheng Han, 2021. "Model performance analysis for landslide susceptibility in cold regions using accuracy rate and fluctuation characteristics," 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. 108(1), pages 1047-1067, August.
    3. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    4. Shi, Yuji & Blainey, Simon & Sun, Chao & Jing, Peng, 2020. "A literature review on accessibility using bibliometric analysis techniques," Journal of Transport Geography, Elsevier, vol. 87(C).
    5. Bell, Michael G.H. & Kurauchi, Fumitaka & Perera, Supun & Wong, Walter, 2017. "Investigating transport network vulnerability by capacity weighted spectral analysis," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 251-266.
    6. Berrocal, Veronica J. & Raftery, Adrian E. & Gneiting, Tilmann & Steed, Richard C., 2010. "Probabilistic Weather Forecasting for Winter Road Maintenance," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 522-537.
    7. Leng Jun-qiang & Yang Long-hai & Wei-yi Liu & Lin Zhao, 2017. "Measuring Road Network Vulnerability with Sensitivity Analysis," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-11, January.
    8. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
    9. Ling Hu, 2006. "Dependence patterns across financial markets: a mixed copula approach," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 717-729.
    Full references (including those not matched with items on IDEAS)

    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. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    2. Li, Tao & Rong, Lili & Yan, Kesheng, 2019. "Vulnerability analysis and critical area identification of public transport system: A case of high-speed rail and air transport coupling system in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 55-70.
    3. Lu, Qing-Chang & Zhang, Lei & Xu, Peng-Cheng & Cui, Xin & Li, Jing, 2022. "Modeling network vulnerability of urban rail transit under cascading failures: A Coupled Map Lattices approach," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    4. Sugiura, Satoshi & Chen, Anthony, 2021. "Vulnerability analysis of cut-capacity structure and OD demand using Gomory-Hu tree method," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 111-127.
    5. Rostislav Vodák & Michal Bíl & Tomáš Svoboda & Zuzana Křivánková & Jan Kubeček & Tomáš Rebok & Petr Hliněný, 2019. "A deterministic approach for rapid identification of the critical links in networks," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-18, July.
    6. Pan, Shouzheng & Yan, Hai & He, Jia & He, Zhengbing, 2021. "Vulnerability and resilience of transportation systems: A recent literature review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    7. Allan Peñafiel Mera & Chandra Balijepalli, 2020. "Towards improving resilience of cities: an optimisation approach to minimising vulnerability to disruption due to natural disasters under budgetary constraints," Transportation, Springer, vol. 47(4), pages 1809-1842, August.
    8. Ahmad Mohamad El-Maissi & Sotirios A. Argyroudis & Fadzli Mohamed Nazri, 2020. "Seismic Vulnerability Assessment Methodologies for Roadway Assets and Networks: A State-of-the-Art Review," Sustainability, MDPI, vol. 13(1), pages 1-31, December.
    9. Jiangang Shi & Shiping Wen & Xianbo Zhao & Guangdong Wu, 2019. "Sustainable Development of Urban Rail Transit Networks: A Vulnerability Perspective," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    10. Gu, Yu & Chen, Anthony & Xu, Xiangdong, 2023. "Measurement and ranking of important link combinations in the analysis of transportation network vulnerability envelope buffers under multiple-link disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 118-144.
    11. Yanan Zhang & Hongke Xu & Qing-Chang Lu & Shan Lin & Jiacheng Song, 2023. "Vulnerability Analysis of Bus Network Based on Land-Use Type of Bus Stops: The Case of Xi’an, China," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    12. Akbarzadeh, Meisam & Salehi Reihani, Sayed Farzin & Samani, Keivan Aghababaei, 2019. "Detecting critical links of urban networks using cluster detection methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 288-298.
    13. Xu, Xiangdong & Chen, Anthony & Jansuwan, Sarawut & Yang, Chao & Ryu, Seungkyu, 2018. "Transportation network redundancy: Complementary measures and computational methods," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 68-85.
    14. Gu, Yu & Fu, Xiao & Liu, Zhiyuan & Xu, Xiangdong & Chen, Anthony, 2020. "Performance of transportation network under perturbations: Reliability, vulnerability, and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    15. Bergström, Anna & Krüger, Niclas A., 2013. "Modeling passenger train delay distributions: evidence and implications," Working papers in Transport Economics 2013:3, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    16. Richard Connors & David Watling, 2015. "Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation," Networks and Spatial Economics, Springer, vol. 15(2), pages 367-395, June.
    17. Ning, Cathy & Wirjanto, Tony S., 2009. "Extreme return-volume dependence in East-Asian stock markets: A copula approach," Finance Research Letters, Elsevier, vol. 6(4), pages 202-209, December.
    18. Yanzhao Wang & Jianfei Cao, 2023. "Examining the Effects of Socioeconomic Development on Fine Particulate Matter (PM2.5) in China’s Cities Based on Spatial Autocorrelation Analysis and MGWR Model," IJERPH, MDPI, vol. 20(4), pages 1-23, February.
    19. Burda Martin & Bélisle Louis, 2019. "Copula multivariate GARCH model with constrained Hamiltonian Monte Carlo," Dependence Modeling, De Gruyter, vol. 7(1), pages 133-149, January.
    20. Wang, Xiaoxi & Zhang, Yaojun & Yu, Danlin & Qi, Jinghan & Li, Shujing, 2022. "Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China," Land Use Policy, Elsevier, vol. 119(C).

    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:115:y:2023:i:3:d:10.1007_s11069-022-05632-0. 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.