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A Narrative of Urban Underground Pipeline System Disasters in China in 2021: Spatial and Temporal Distribution, Causal Analysis, and Response Strategies

Author

Listed:
  • Zhiqiang Xie

    (School of Earth Sciences, Yunnan University, Kunming 650500, China)

  • Fengshan Jiang

    (School of Earth Sciences, Yunnan University, Kunming 650500, China)

  • Jiarui Xu

    (International Institute of Rivers and Ecological Security, Yunnan University, Kunming 650500, China)

  • Zhengang Zhai

    (Beijing New Technology Research Center, Beijing 100013, China)

  • Jianglong He

    (Kunming Institute of Surveying and Mapping, Kunming 650051, China)

  • Daoyang Zheng

    (School of Earth Sciences, Yunnan University, Kunming 650500, China)

  • Junyu Lian

    (School of Earth Sciences, Yunnan University, Kunming 650500, China)

  • Zhiqun Hou

    (Kunming Institute of Surveying and Mapping, Kunming 650051, China)

  • Lei Zhao

    (Kunming Surveying and Mapping Management Center, Kunming 650500, China)

  • Yanxia Wang

    (Beijing Academy of Science and Technology, Beijing 100744, China)

  • Yuyun Feng

    (School of Earth Sciences, Yunnan University, Kunming 650500, China)

Abstract

In recent years, there have been frequent disasters and accidents in the underground pipeline system of Chinese cities, posing a continuous threat to the safety of life and property of the public and the order of urban operations. This article uses statistical data on the spatiotemporal distribution of major underground pipeline disasters in various provinces of China in 2021. By using Pearson’s correlation coefficient and regression analysis, a causal analysis model for urban underground pipeline accidents is constructed, and the correlation between urban underground pipeline accident rate and economic and social indicators is analyzed. From the analysis, it has been found that the correlation coefficients of gross domestic product (GDP) per capita, the pipeline density in the built-up area, and the urban pipeline accident rate reach −0.4019 and −0.4275, respectively, showing a negative correlation. Further, the regression analysis results show that the underground pipeline accident rate shows a decreasing trend as the per capita GDP and the density of pipelines in the built-up areas increase. Among them, the results of the power function fitting model show that the GDP per capita accounts for 48.10% of the urban underground pipeline accidents, whereas the pipeline density of the built-up area accounts for 58.27% of these accidents. The construction of underground pipeline regulations is influential in reducing underground pipeline disaster accidents. In this study, the role and effectiveness of the factors, such as the construction of professional regulations in maintaining the safe operation of urban underground pipelines, has been discussed, and suggestions and methods to improve the problems that need to be solved, such as the construction of a municipal supporting emergency management system in the safe operation of underground pipelines in the future, have been proposed.

Suggested Citation

  • Zhiqiang Xie & Fengshan Jiang & Jiarui Xu & Zhengang Zhai & Jianglong He & Daoyang Zheng & Junyu Lian & Zhiqun Hou & Lei Zhao & Yanxia Wang & Yuyun Feng, 2023. "A Narrative of Urban Underground Pipeline System Disasters in China in 2021: Spatial and Temporal Distribution, Causal Analysis, and Response Strategies," Sustainability, MDPI, vol. 15(13), pages 1-23, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10067-:d:1179161
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    References listed on IDEAS

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    1. Siler-Evans, Kyle & Hanson, Alex & Sunday, Cecily & Leonard, Nathan & Tumminello, Michele, 2014. "Analysis of pipeline accidents in the United States from 1968 to 2009," International Journal of Critical Infrastructure Protection, Elsevier, vol. 7(4), pages 257-269.
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    Cited by:

    1. Xiuyu Wu & Pengkai Sun, 2024. "Dynamic Analysis and Temporal Governance of Safety Risks: Evidence from Underground Construction Accident Reports," Sustainability, MDPI, vol. 16(19), pages 1-24, September.

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