IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i24p17003-d1007054.html
   My bibliography  Save this article

Cause Analysis and Preventive Measures of Guizhou D2809 Train Derailment Accident in Guizhou, China on 4 June 2022

Author

Listed:
  • Yan-Ning Wang

    (MOE Key Laboratory of Intelligence Manufacturing Technology, Department of Civil and Environmental Engineering, Shantou University, Shantou 515063, China
    State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou 221116, China)

  • Han Chen

    (MOE Key Laboratory of Intelligence Manufacturing Technology, Department of Civil and Environmental Engineering, Shantou University, Shantou 515063, China)

  • Bin-Song Jiang

    (State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou 221116, China)

  • Jing-Rui Peng

    (MOE Key Laboratory of Intelligence Manufacturing Technology, Department of Civil and Environmental Engineering, Shantou University, Shantou 515063, China)

  • Jun Chen

    (Department of Civil Engineering, Shanghai Jiao Tong University, Shanghai 200030, China)

Abstract

This paper summarizes the cause of the debris flow impact train accident by investigating the local geological condition, meteorological data and field investigation that happened in Guizhou, China on 4 June 2022. The result showed that the major reason is the continuous heavy rain in the surrounding area, which led to a small landslide at the upper right of the tunnel entrance. Besides, the construction of the Jianrong Expressway in the upper reaches increased the catchment area, which makes the water content of the upper soil increase while the shear strength decreases. Such large-scale catastrophic accidents significantly threaten the local environment and public safety. Therefore, it is urgent to pay special attention to the changes in geological conditions along the line, especially the adverse effects of construction, to improve the early risk warning and post-accident treatment ability.

Suggested Citation

  • Yan-Ning Wang & Han Chen & Bin-Song Jiang & Jing-Rui Peng & Jun Chen, 2022. "Cause Analysis and Preventive Measures of Guizhou D2809 Train Derailment Accident in Guizhou, China on 4 June 2022," IJERPH, MDPI, vol. 19(24), pages 1-14, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:17003-:d:1007054
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/24/17003/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/24/17003/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shuai Li & Zhongyun Ni & Yinbing Zhao & Wei Hu & Zhenrui Long & Haiyu Ma & Guoli Zhou & Yuhao Luo & Chuntao Geng, 2022. "Susceptibility Analysis of Geohazards in the Longmen Mountain Region after the Wenchuan Earthquake," IJERPH, MDPI, vol. 19(6), pages 1-30, March.
    2. Tung-Chiung Chang, 2007. "Risk degree of debris flow applying neural networks," 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. 42(1), pages 209-224, July.
    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. Bin Yu & Yuan Zhu & Tao Wang & Yuanjing Chen & Yunbo Zhu & Yongbo Tie & Ke Lu, 2014. "A prediction model for debris flows triggered by a runoff-induced mechanism," 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. 74(2), pages 1141-1161, November.
    2. Chen Cao & Peihua Xu & Jianping Chen & Lianjing Zheng & Cencen Niu, 2016. "Hazard Assessment of Debris-Flow along the Baicha River in Heshigten Banner, Inner Mongolia, China," IJERPH, MDPI, vol. 14(1), pages 1-19, December.
    3. Shuai Li & Haiyu Ma & Di Yang & Wei Hu & Hao Li, 2023. "The Main Drivers of Wetland Evolution in the Beijing-Tianjin-Hebei Plain," Land, MDPI, vol. 12(2), pages 1-25, February.
    4. Wen Zhang & Jian-ping Chen & Qing Wang & Yuke An & Xin Qian & Liangjun Xiang & Longxiang He, 2013. "Susceptibility analysis of large-scale debris flows based on combination weighting and extension methods," 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. 66(2), pages 1073-1100, March.
    5. Zhiye Wang & Chuanming Ma & Yang Qiu & Hanxiang Xiong & Minghong Li, 2022. "Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China," IJERPH, MDPI, vol. 19(15), pages 1-22, August.
    6. Hao Mei & Jin Yang & Mingshun Xiang & Xiaofeng Yang & Chunjian Wang & Wenheng Li & Suhua Yang, 2022. "Evaluation and Optimization Model of Rural Settlement Habitability in the Upper Reaches of the Minjiang River, China," IJERPH, MDPI, vol. 19(22), pages 1-18, November.
    7. Yong-Jun Lin & Yuan-Hsiou Chang & Yih-Chi Tan & Hong-Yuan Lee & Yu-Jia Chiu, 2011. "National policy of watershed management and flood mitigation after the 921 Chi-Chi earthquake in Taiwan," 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. 56(3), pages 709-731, March.
    8. Bin Yu & Li Li & Yufu Wu & Shengming Chu, 2013. "A formation model for debris flows in the Chenyulan River Watershed, Taiwan," 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. 68(2), pages 745-762, September.
    9. Shahram Kaboodvandpour & Jamil Amanollahi & Samira Qhavami & Bakhtiyar Mohammadi, 2015. "Assessing the accuracy of multiple regressions, ANFIS, and ANN models in predicting dust storm occurrences in Sanandaj, Iran," 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. 78(2), pages 879-893, September.
    10. Cencen Niu & Qing Wang & Jianping Chen & Wen Zhang & Liming Xu & Ke Wang, 2015. "Hazard Assessment of Debris Flows in the Reservoir Region of Wudongde Hydropower Station in China," Sustainability, MDPI, vol. 7(11), pages 1-20, November.

    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:gam:jijerp:v:19:y:2022:i:24:p:17003-:d:1007054. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.