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Logistic regression model for sinkhole susceptibility due to damaged sewer pipes

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  • Kiyeon Kim

    (Seoul National University)

  • Joonyoung Kim

    (Seoul National University)

  • Tae-Young Kwak

    (Seoul National University)

  • Choong-Ki Chung

    (Seoul National University)

Abstract

The occurrence of anthropogenic sinkholes in urban areas can lead to severe socioeconomic losses. A damaged underground sewer pipe is regarded as one of the primary causes of such a phenomenon. This study adopted the best subsets regression method to produce a logistic regression model that evaluates the susceptibility for sinkholes induced by damaged sewer pipes. The model was developed by analyzing the sewer pipe network as well as cases of sinkholes in Seoul, South Korea. Among numerous sewer pipe characteristics tested as explanatory variables, the length, age, elevation, burial depth, size, slope, and materials of the sewer pipe were found to influence the occurrence of sinkhole. The proposed model reasonably estimated the sinkhole susceptibility in the area studied, with an area value under the receiver-operating characteristics curve of 0.753. The proposed methodology will serve as a useful tool that can help local governments to choose a cavity inspection regime, and to prevent sinkholes induced by damaged sewer pipes.

Suggested Citation

  • Kiyeon Kim & Joonyoung Kim & Tae-Young Kwak & Choong-Ki Chung, 2018. "Logistic regression model for sinkhole susceptibility due to damaged sewer pipes," 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. 93(2), pages 765-785, September.
    • Handle: RePEc:spr:nathaz:v:93:y:2018:i:2:d:10.1007_s11069-018-3323-y
    DOI: 10.1007/s11069-018-3323-y
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    References listed on IDEAS

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    1. H. Pourghasemi & H. Moradi & S. Fatemi Aghda, 2013. "Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances," 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. 69(1), pages 749-779, October.
    2. G. Ciotoli & E. Di Loreto & M.G. Finoia & L. Liperi & F. Meloni & S. Nisio & A. Sericola, 2016. "Sinkhole susceptibility, Lazio Region, central Italy," Journal of Maps, Taylor & Francis Journals, vol. 12(2), pages 287-294, March.
    3. Yamijala, Shridhar & Guikema, Seth D. & Brumbelow, Kelly, 2009. "Statistical models for the analysis of water distribution system pipe break data," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 282-293.
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    Cited by:

    1. Gabriele Medio & Giada Varra & Çağrı Alperen İnan & Luca Cozzolino & Renata Della Morte, 2024. "Sinkhole Risk-Based Sensor Placement for Leakage Localization in Water Distribution Networks with a Data-Driven Approach," Sustainability, MDPI, vol. 16(12), pages 1-20, June.
    2. Xu-Wei Wang & Ye-Shuang Xu, 2022. "Investigation on the phenomena and influence factors of urban ground collapse in China," 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. 113(1), pages 1-33, August.
    3. Nhat-Duc Hoang & Quoc-Lam Nguyen & Xuan-Linh Tran, 2019. "Automatic Detection of Concrete Spalling Using Piecewise Linear Stochastic Gradient Descent Logistic Regression and Image Texture Analysis," Complexity, Hindawi, vol. 2019, pages 1-14, July.
    4. Rita Tufano & Luigi Guerriero & Mariagiulia Annibali Corona & Giuseppe Bausilio & Diego Di Martire & Stefania Nisio & Domenico Calcaterra, 2022. "Anthropogenic sinkholes of the city of Naples, Italy: an update," 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. 112(3), pages 2577-2608, July.
    5. Pooya Dastpak & Rita L. Sousa & Daniel Dias, 2023. "Soil Erosion Due to Defective Pipes: A Hidden Hazard Beneath Our Feet," Sustainability, MDPI, vol. 15(11), pages 1-23, June.
    6. Jeonghun Lee & Chan Young Park & Seungwon Baek & Seung H. Han & Sungmin Yun, 2021. "Risk-Based Prioritization of Sewer Pipe Inspection from Infrastructure Asset Management Perspective," Sustainability, MDPI, vol. 13(13), pages 1-21, June.

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