IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v93y2018i2d10.1007_s11069-018-3323-y.html
   My bibliography  Save this article

Logistic regression model for sinkhole susceptibility due to damaged sewer pipes

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-018-3323-y
    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/s11069-018-3323-y?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. 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.
    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.

    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. Rajesh Khatakho & Dipendra Gautam & Komal Raj Aryal & Vishnu Prasad Pandey & Rajesh Rupakhety & Suraj Lamichhane & Yi-Chung Liu & Khameis Abdouli & Rocky Talchabhadel & Bhesh Raj Thapa & Rabindra Adhi, 2021. "Multi-Hazard Risk Assessment of Kathmandu Valley, Nepal," Sustainability, MDPI, vol. 13(10), pages 1-27, May.
    2. Garyfallos Arabatzis & Georgios Kolkos & Anastasia Stergiadou & Apostolos Kantartzis & Stergios Tampekis, 2024. "Optimal Allocation of Water Reservoirs for Sustainable Wildfire Prevention Planning via AHP-TOPSIS and Forest Road Network Analysis," Sustainability, MDPI, vol. 16(2), pages 1-27, January.
    3. Amin Salehpour Jam & Jamal Mosaffaie & Faramarz Sarfaraz & Samad Shadfar & Rouhangiz Akhtari, 2021. "GIS-based landslide susceptibility mapping using hybrid MCDM models," 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 1025-1046, August.
    4. Robles-Velasco, Alicia & Cortés, Pablo & Muñuzuri, Jesús & Onieva, Luis, 2020. "Prediction of pipe failures in water supply networks using logistic regression and support vector classification," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    5. Kabir, Golam & Tesfamariam, Solomon & Sadiq, Rehan, 2015. "Predicting water main failures using Bayesian model averaging and survival modelling approach," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 498-514.
    6. Chen, Thomas Ying-Jeh & Guikema, Seth David & Daly, Craig Michael, 2019. "Optimal pipe inspection paths considering inspection tool limitations," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 156-166.
    7. Daulat, Shamsuddin & Rokstad, Marius Møller & Bruaset, Stian & Langeveld, Jeroen & Tscheikner-Gratl, Franz, 2024. "Evaluating the generalizability and transferability of water distribution deterioration models," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    8. Xu, Qiang & Chen, Qiuwen & Li, Weifeng & Ma, Jinfeng, 2011. "Pipe break prediction based on evolutionary data-driven methods with brief recorded data," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 942-948.
    9. Jara-Arriagada, Carlos & Stoianov, Ivan, 2021. "Pipe breaks and estimating the impact of pressure control in water supply networks," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    10. Hamid Reza Pourghasemi & Amiya Gayen & Sungjae Park & Chang-Wook Lee & Saro Lee, 2018. "Assessment of Landslide-Prone Areas and Their Zonation Using Logistic Regression, LogitBoost, and NaïveBayes Machine-Learning Algorithms," Sustainability, MDPI, vol. 10(10), pages 1-23, October.
    11. Yuxin Guo & Zhanya Xu & Shuang Zhu & Xiangang Luo & Yinli Xiao, 2023. "Using distributed root soil moisture data to enhance the performance of rainfall thresholds for landslide warning," 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(2), pages 1167-1192, January.
    12. Alicia Robles-Velasco & Pablo Cortés & Jesús Muñuzuri & Luis Onieva, 2021. "Estimation of a logistic regression model by a genetic algorithm to predict pipe failures in sewer networks," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(3), pages 759-776, September.
    13. Chen Cao & Peihua Xu & Yihong Wang & Jianping Chen & Lianjing Zheng & Cencen Niu, 2016. "Flash Flood Hazard Susceptibility Mapping Using Frequency Ratio and Statistical Index Methods in Coalmine Subsidence Areas," Sustainability, MDPI, vol. 8(9), pages 1-18, September.
    14. Anna Małka, 2021. "Landslide susceptibility mapping of Gdynia using geographic information system-based statistical models," 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. 107(1), pages 639-674, May.
    15. Meireles, Inês & Sousa, Vitor & Matos, José Pedro & Cruz, Carlos Oliveira, 2023. "Determinants of water loss in Portuguese utilities," Utilities Policy, Elsevier, vol. 83(C).
    16. Kozłowski Edward & Kowalska Beata & Kowalski Dariusz & Mazurkiewicz Dariusz, 2019. "Survival Function in the Analysis of the Factors Influencing the Reliability of Water Wells Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4909-4921, November.
    17. Deliang Sun & Danlu Chen & Jialan Zhang & Changlin Mi & Qingyu Gu & Haijia Wen, 2023. "Landslide Susceptibility Mapping Based on Interpretable Machine Learning from the Perspective of Geomorphological Differentiation," Land, MDPI, vol. 12(5), pages 1-37, May.
    18. Vahdettin Demir, 2022. "Trend analysis of lakes and sinkholes in the Konya Closed Basin, in Turkey," 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 2873-2912, July.
    19. Alaa M. Al-Abadi & Noor A. Al-Najar, 2020. "Comparative assessment of bivariate, multivariate and machine learning models for mapping flood proneness," 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. 100(2), pages 461-491, January.
    20. Eseosa Halima Ighile & Hiroaki Shirakawa & Hiroki Tanikawa, 2022. "Application of GIS and Machine Learning to Predict Flood Areas in Nigeria," Sustainability, MDPI, vol. 14(9), pages 1-33, April.

    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:93:y:2018:i:2:d:10.1007_s11069-018-3323-y. 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.