Geomechanics and Engineering

  • 제18권5호
  • /
  • Pages.515-525
  • /
  • 2019
  • /
  • 2005-307X(pISSN)
  • /
  • 2092-6219(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Risk assessment of karst collapse using an integrated fuzzy analytic hierarchy process and grey relational analysis model

  • Ding, Hanghang (College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing)) ;
  • Wu, Qiang (College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing)) ;
  • Zhao, Dekang (College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing)) ;
  • Mu, Wenping (School of Water Resources and Environment, China University of Geosciences) ;
  • Yu, Shuai (College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing))
  • 투고 : 2019.04.16
  • 심사 : 2019.07.18
  • 발행 : 2019.08.10
⟨ 이전 논문 다음 논문 ⟩

초록

A karst collapse, as a natural hazard, is totally different to a normal collapse. In recent years, karst collapses have caused substantial economic losses and even threatened human safety. A risk assessment model for karst collapse was developed based on the fuzzy analytic hierarchy process (FAHP) and grey relational analysis (GRA), which is a simple and effective mathematical algorithm. An evaluation index played an important role in the process of completing the risk assessment model. In this study, the proposed model was applied to Jiaobai village in southwest China. First, the main controlling factors were summarized as an evaluation index of the model based on an investigation and statistical analysis of the natural formation law of karst collapse. Second, the FAHP was used to determine the relative weights and GRA was used to calculate the grey relational coefficient among the indices. Finally, the relational sequence of evaluation objects was established by calculating the grey weighted relational degree. According to the maximum relational rule, the greater the relational degree the better the relational degree with the hierarchy set. The results showed that the model accurately simulated the field condition. It is also demonstrated the contribution of various control factors to the process of karst collapse and the degree of collapse in the study area.

키워드

과제정보

연구 과제 주관 기관 : China National Natural Science Foundation

참고문헌

  1. Dai, J. and Lei, M. (2018), "Standard guide for karst collapse investigation and its technical essential", Environ. Earth Sci., 77(4), 133. https://doi.org/10.1007/s12665-018-7288-7.
  2. Deng, J.L. (1989), Introduction To Grey System Theory, Huazhong University of Science and Technology Press, Wuhan, China.
  3. Ding, J.P., Chu, X.W., Duan, X.Q., Liang, F. and Wang, Z.M. (2017), Karst Collapse in Guizhou, Geological Publishing House, Beijing, China.
  4. Duan, X.Q., Chu, X.W. and Bo, L. (2016), "Risk prediction and evaluation of the karst collapse based on the set pair mechanism analysis", J. Safety Environ., 16(4), 72-76. https://doi.org/10.13637/j.issn.1009-6094.2016.04.014.
  5. Farrant, A.R. and Cooper, A.H. (2008), "Karst geohazards in the UK: The use of digital data for hazard management", Quart. J. Eng. Geol. Hydrogeol., 41(3), 339-356. https://doi.org/10.1144/1470-9236/07-201.
  6. Galve, J.P., Gutierrez, F., Lucha, P., Guerrero, J., Bonachea, J., Remondo, J. and Cendrero, A. (2009), "Probabilistic sinkhole modelling for hazard assessment", Earth Surface Proc. Landforms, 34(3), 437-452. https://doi.org/10.1002/esp.1753.
  7. Galve, J.P., Gutierrez, F., Remondo, J., Bonachea, J., Lucha, P. and Cendrero, A. (2009), "Evaluating and comparing methods of sinkhole susceptibility mapping in the Ebro valley evaporite karst (NE Spain)", Geomorphology, 111(3), 160-172. https://doi.org/10.1016/j.geomorph.2009.04.017.
  8. Gao, L. and Hailu, A. (2012), "Ranking management strategies with complex outcomes: an AHP-fuzzy evaluation of recreational fishing using an integrated agent-based model of a coral reef ecosystem", Environ. Model. Software, 31(7), 3-18. https://doi.org/10.1016/j.envsoft.2011.12.002.
  9. Gomez-Ortiz, D. and Martin-Crespo, T. (2012), "Assessing the risk of subsidence of a sinkhole collapse using ground penetrating radar and electrical resistivity tomography", Eng. Geol., 149(4), 1-12. https://doi.org/10.1016/j.enggeo.2012.07.022.
  10. He, K.Q., Du, R.L. and Jiang, W.F. (2010), "Contrastive analysis of karst collapses and the distribution rules in northern and southern China", Environ. Earth Sci., 59(6), 1309-1318. https://doi.org/10.1007/s12665-009-0118-1.
  11. He, K.Q., Liu, C.L. and Wang, S.J. (2003), "Karst collapse related to over-pumping and a criterion for its stability", Environ. Geol., 43(6), 720-724. https://doi.org/10.1007/s00254-002-0669-x.
  12. He, S.N., Zhou, G.Q., Li, Y.F. and Chen, K.H. (2014), "The studying on relationship between collapse points and geological factors based on GIS: a case study of Laibin, Jili in Guangxi", Geomat. Spatial Inform. Technol., 37(02), 38-42. (in Chinese)
  13. Isalou, A.A., Zamani, V. Shahmoradi, B. and Alizadeh, H. (2013), "Landfill site selection using integrated fuzzy logic and analytic network process (F-ANP)", Environ. Earth Sci., 68(6), 1745-1755. https://doi.org/10.1007/s12665-012-1865-y.
  14. Jiang, X.Z. (2003), "Application of GIS to the assessment of surfaces collapse hazards in china", Acta Geosicientia Sinica, 24(5), 469-473 (in Chinese).
  15. Jiang, X.Z., Lei, M.T. and Guan, Z.D. (2012), "Characterization criteria of karst collapse hazard on groundwater fluctuations in Qingyun village, Guigang, Guangxi, China", Chin. J. Undergr. Sp. Eng., 72(1), 43-43 (in Chinese).
  16. Kahraman, C., Cebeci, U. and Ruan, D. (2004), "Multi-attribute comparison of catering service companies using fuzzy AHP: The case of Turkey", Int. J. Prod. Econ., 87(2), 171-184. https://doi.org/10.1016/S0925-5273(03)00099-9.
  17. Kaufmann, G. (2014), "Geophysical mapping of solution and collapse sinkholes", J. Appl. Geophys., 111, 271-288. https://doi.org/10.1016/j.jappgeo.2014.10.011.
  18. Kaufmann, G., Romanov, D., Tippelt, T., Vienken, T., Werban, U., Dietrich, P., Mai, F. and Boerner, F. (2018), "Mapping and modelling of collapse sinkholes in soluble rock: The Munsterdorf site, northern Germany", J. Appl. Geophys., 154, 64-80. https://doi.org/10.1016/j.jappgeo.2018.04.021.
  19. Kim, K.D., Lee, S. and Oh, H.J. (2009), "Prediction of ground subsidence in Samcheok City, Korea using artificial neural networks and GIS", Environ. Geol., 58(1), 61-70. https://doi.org/10.1007/s00254-008-1492-9.
  20. Kuo Y.Y., Yang T.H. and Huang G.W. (2008), "The use of grey relational analysis in solving multiple attribute decision-making problems", Comput. Indust. Eng., 55(1), 80-93. https://doi.org/10.1016/j.cie.2007.12.002.
  21. Lei, M.T., Jiang, X.Z. and Yu, L. (2002), "New advances in karst collapse research in china", Environ. Geol., 42(5), https://doi.org/462-468.10.1007/s00254-001-0506-7.
  22. Liao, Y.L. (2004), Carbonate Laterite in Guizhou, Guizhou People's Publishing House, Guiyang, China.
  23. Lin, P., Li, S.C., Xu, Z.H., Huang, X., Pang, D.D., Wang, X.T. and Wang, J. (2018), "Location determining method of critical sliding surface of fillings in a karst cave of tunnel", Geomech. Eng., 16(4), 415-421. https://doi.org/10.12989/gae.2018.16.4.415.
  24. Lu, Y.J. (2002), "Weight calculation method of fuzzy analytical hierarchy process", Fuzzy Syst. Math., 2002(02), 79-85. (in Chinese)
  25. Naghadehi, M.Z., Mikaeil, R. and Ataei, M. (2009), "The application of fuzzy analytic hierarchy process (FAHP) approach to selection of optimum underground mining method for Jajarm Bauxite Mine, Iran", Expert Syst. Appl., 36(4), 8218-8226. https://doi.org/10.1016/j.eswa.2008.10.006.
  26. Oh, H.J. and Lee, S. (2010), "Assessment of ground subsidence using GIS and the weights-of-evidence model", Eng. Geol., 115(1), 36-48. https://doi.org/10.1016/j.enggeo.2010.06.015.
  27. Papadopoulou-Vrynioti, K., Bathrellos, G.D., Skilodimou, H.D., Kaviris, G. and Makropoulos, K. (2013), "Karst collapse susceptibility mapping considering peak ground acceleration in a rapidly growing urban area", Eng. Geol., 158(8), 77-88. https://doi.org/77-88.10.1016/j.enggeo.2013.02.009.
  28. Taheri, K., Gutierrez, F., Mohseni, H., Raeisi, E. and Taheri, M. (2015), "Sinkhole susceptibility mapping using the analytical hierarchy process (AHP) and magnitude-frequency relationships: A case study in Hamadan province, Iran", Geomorphology, 234, 64-79. https://doi.org/10.1016/j.geomorph.2015.01.005.
  29. Wei, G.W. (2010), "A method for multiple attribute decision making with incomplete weight information in intuitionistic fuzzy setting", Knowledge-Based Syst., 23(3), 243-247. https://doi.org/10.1016/j.knosys.2010.01.003.
  30. Yuan, Y.C., Li, S.C., Zhang, Q.Q., Li, L.P., Shi, S.S. and Zhou, Z.Q. (2016), "Risk assessment of water inrush in karst tunnels based on a modified grey evaluation model: Sample as Shangjiawan Tunnel", Geomech. Eng., 11(4), 493-513. https://doi.org/10.12989/gae.2016.11.4.493.
  31. Zhang, L.F., Zeng, X.S., Yao, Y.S. and Liao, W.L. (2007), "Review on karst collapse in china", Chin. J. Geol. Hazard Control, 18(3), 126-130. https://doi.org/10.16031/j.cnki.issn.1003-8035.2007.03.022.
  32. Zhou, Z.Q., Li, S.C., Li, L.P., Shi, S.S. and Xu, Z.H. (2015), "An optimal classification method for risk assessment of water inrush in karst tunnels based on grey system theory", Geomech. Eng., 8(5), 631-647. https://doi.org/10.12989/gae.2015.8.5.631.