ORIGINAL RESEARCH
Risk Assessment of Water Inrush in Karst Tunnels
Based on the Ideal Point Method
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1
State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, China
2
Civil, Architectural, and Environmental Engineering Department, Missouri University of Science
and Technology, Rolla, MO, USA
3
Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA
4
School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, China
Submission date: 2017-10-24
Final revision date: 2017-12-20
Acceptance date: 2018-02-10
Online publication date: 2018-08-31
Publication date: 2018-12-20
Corresponding author
Yingchao Wang
China university of mining & technology, Daxue road 1, 221116 Xuzhou, China
Pol. J. Environ. Stud. 2019;28(2):901-911
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ABSTRACT
Water inrush is one of the typical geological hazards in the construction of high-risk tunnels,
and has caused severe losses. To predict water inrush accurately, a novel model was put forward for karst
tunnels in the present study. The ideal point method coupled with the analytic hierarchy process method
(AHP) was applied for risk assessment of water inrush. First, the ideal point method was introduced as
a brand-new way to predict the risk level of water inrush. Second, the water inrush risk in karst tunnels
was discussed in terms of influencing factors. With the consideration of karst hydrological and
engineering geological conditions, seven key factors were selected as evaluation indices, including
formation lithology, unfavorable geological conditions, groundwater level, landform and physiognomy,
modified strata inclination, contact zones of dissolvable and insoluble rock, and layer and interlayer
fissures. Then the ideal point method was used to deal with the multiple evaluation indices to determine
the ideal point and the anti-ideal point. Meanwhile, the analytic hierarchy process method (AHP)
was applied to determine the weight coefficient of each evaluation index. Thus, the minkowski distances
respectively for the ideal point and the anti-ideal point were calculated. Based on the discriminant
analysis theory, the closeness degrees to the ideal points were brought out to specify the risk level
of water inrush. Finally, the proposed model was applied to a typical deep-buried karst tunnel: Jigongling
Tunnel in China. The obtained results were compared with the results of the relevant methods and
the practical findings, and reasonable agreements could validate the presented approach. The obtained
results not only provide guidance for the construction of high-risk tunnels, but also bring out an alternative
way for risk assessment of water inrush.