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Volume 31 Issue 3
Jun.  2018
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Journal of Southwest Jiaotong University  > 2018  >  53(3): 565-573.
ZHANG Kai, HUO Xiaolong, CHEN Shougen, TU Peng, TAN Xinrong. Preliminary Study of Assessment System for Subsurface Karst Development Degree[J]. Journal of Southwest Jiaotong University, 2018, 53(3): 565-573. doi: 10.3969/j.issn.0258-2724.2018.03.018
Citation: ZHANG Kai, HUO Xiaolong, CHEN Shougen, TU Peng, TAN Xinrong. Preliminary Study of Assessment System for Subsurface Karst Development Degree[J]. Journal of Southwest Jiaotong University, 2018, 53(3): 565-573. doi: 10.3969/j.issn.0258-2724.2018.03.018
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Preliminary Study of Assessment System for Subsurface Karst Development Degree

doi: 10.3969/j.issn.0258-2724.2018.03.018
  • Received Date: 01 Mar 2017
  • Publish Date: 25 Jun 2018
    Abstract
  • An attempt was made to establish an assessment system for subsurface karst development by combining quantitative and qualitative methods. The assessment results can assist the preliminary determination of the extent of underground karst development and guide the planning and construction of underground engineering projects. Firstly, the major factors influencing the karst development were selected as the assessment indices in the system, and the varying degrees of subsurface karst development are defined. Then, the weights of these assessment indices were determined using a synthetic weighting method, in which the fuzzy hierarchy analytic process determines the qualitative weights, while the quantitative weights were determined by a sensitivity analysis of the Bayesian belief network. The Fuzzy Analytic Hierarchy Process was used to determine the ratings of the karst development states in the assessment indices. Moreover, based on the statistical data, the quantitative assessment results belonging to each degree of karst development were determined by comparing the calculated assessment results with the real karst development status. The proposed assessment system was applied to a railway tunnelling project in China to evaluate the degree of surface karst development before tunnel construction. A comparative analysis of the assessment results with the recorded results shows that the assessment of the tunnel zone, accounting for 97.1% of the total tunnel length, is consistent with the recorded results. Assessment errors only occur in 2.9% of the tunnel zone, where the degree of karst development was assigned as "developed", while the records indicated it was "extremely developed". However, the quantitative assessment result of the karst development degree is 0.69, which is close to the value range of "extremely developed", 0.70-1.00. As this minor error is acceptable in the preliminary assessment of the degree of karst development, the proposed assessment system is verifiably reliable.

     

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  • 吴德胜, 苏有财, 丁建芳, 等.山区特长岩溶隧道施工阶段勘察方法探讨[J].西南交通大学学报, 2012(增刊):202-207. http://d.old.wanfangdata.com.cn/Conference/7913605

    WU Desheng, SU Youcai, DING Jianfang, et al. The discussion of the surveying method during the construction of the mountainous long karst tunnel[J]. Journal of Southwest Jiaotong University, 2012(Sup.):202-207. http://d.old.wanfangdata.com.cn/Conference/7913605
    SOKOLOV D S. Main conditions for karst development[M]. Moscow:GosGeolTechIzdat, 1962:320-323.
    LEGRAND H E, STRINGFILD V T. Karst hydrology-areview[J]. Journal of Hydrology, 1973, 20(2):97-120. doi: 10.1016/0022-1694(73)90034-6
    STRINGFIELD V T, RAPP J R, ANDERS R B. Effect of karst and geological structure on the circulation of water and permeability in carbonate aquifers[J]. Journal of Hydrology, 1979, 43(1/2/3/4):313-332. http://www.sciencedirect.com/science/article/pii/0022169479901781
    FORD D, WILLIAMS P. Karst hydrogeology and geomorphology[M]. Chichester:John Wiley & Sons Ltd., 2007:9-38, 401-440.
    中国科学院地质研究所.中国岩溶研究[M].北京:科学出版社, 1977:73-110.
    任美锷, 刘振中.岩溶学概论[M].北京:商务印书馆.1983:21-59.
    铁道部第二勘测设计院.岩溶工程地质[M].北京:中国铁道出版社, 1984:1-62.
    袁道先.中国岩溶学[M].北京:地质出版社, 1993:9-52.
    STOKES T R, GRIFFITHS P. A preliminary discussion of karst inventory systems and principles (KISP) for British Columbia[R]. Victoria: Ministry of Forests, Lands and Natural Resource Operations of British Columbia, 2000.
    涂国强, 杨立中, 贺玉龙.铁路沿线岩溶塌陷预测模型[J].西南交通大学学报, 2001, 36(4):341-345. doi: 10.3969/j.issn.0258-2724.2001.04.002

    TU Guoqiang, YANG Lizhong, HE Yulong. Prediction model for sinkholes along railways[J]. Journal of Southwest Jiaotong University, 2001, 36(4):341-345. doi: 10.3969/j.issn.0258-2724.2001.04.002
    李术才, 石少帅, 李利平, 等.三峡库区典型岩溶隧道突涌水灾害防治与应用[J].岩石力学与工程学报, 2014, 33(9):1887-1896. http://d.old.wanfangdata.com.cn/Periodical/yslxygcxb201409022

    LI Shucai, SHI Shaoshuai, LI Liping, et al. Control of water inrush in typical karst tunnels in three gorges reservoir area and its application[J]. Journal of Southwest Jiaotong University, 2014, 33(9):1887-1896. http://d.old.wanfangdata.com.cn/Periodical/yslxygcxb201409022
    李苍松, 高波, 梅志荣.岩溶地质预报的分形理论应用基础研究[J].西南交通大学学报, 2007, 42(5):542-547. doi: 10.3969/j.issn.0258-2724.2007.05.005

    LI Cangsong, GAO Bo, MEI Zhirong. Basic study on method of karst geology forecasting based on fractal theory[J]. Journal of Southwest Jiaotong University, 2007, 42(5):542-547. doi: 10.3969/j.issn.0258-2724.2007.05.005
    刘招伟, 张民庆, 王树仁.岩溶隧道灾变预测与处置技术[M].北京:科学出版社, 2007:81-83.
    CHANG Dayong. Application of the extent analysis method on fuzzy AHP[J]. European Journal of Operational Research, 1996, 95(3):649-655. doi: 10.1016/0377-2217(95)00300-2
    SAATY T L. The analytic hierarchy process[M]. New York:McGrew-Hill International, 1980:271-278.
    DENG H. Multicriteria analysis with fuzzy pair-wise comparison[J]. International Journal of Approximate Reasoning, 1999, 21(3):215-231. doi: 10.1016/S0888-613X(99)00025-0
    WANG T C, CHEN Y H. Applying consistent fuzzy preference relations to partnership selection[J]. International Journal of Manage Science, 2007, 35(4):384-388. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=164e5cba31c534205e0c29b1f4b3106c
    KAHRANMAN C, RUAN D, DOGAN I. Fuzzy group decision making for facility location selection[J]. Information Sciences, 2003, 157:135-153. doi: 10.1016/S0020-0255(03)00183-X
    NEZARAT H, SERESHKI F, ATAEI M. Rangking of geological risks in mechanized tunneling by using Fuzzy Analytical Hierarchy Process (FAHP)[J]. Tunneling and Underground Technology, 2015, 50:358-364. doi: 10.1016/j.tust.2015.07.019
    KRAGT M E. A beginner's guide to Bayesian network modelling for integrated catchment management[R]. Huntly: Landscape Logic Research Hub, 2009.
    PEARL J. Probabilistic reasoning in intelligent systems:networks of plausible inference[M]. San Mateo:Morgan Kaufmann Publishers, 1988:1022-1027.
    SAATY T L. Decision making with the analytic hierarchy process[J]. International Journal of Services Science, 2008, 1(1):83-98. doi: 10.1504/IJSSCI.2008.017590
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