Safety Risk Evaluation of Water and Mud Inrush in Karst Tunnel Based on an Improved Weighted Cloud Model

Baofu Duan, Anni Chu (), Liankai Bu, Zhihong Li and Keyan Long
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Baofu Duan: Shandong Key Laboratory of Civil Engineering Disaster Prevention and Mitigation, College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China
Anni Chu: Shandong Key Laboratory of Civil Engineering Disaster Prevention and Mitigation, College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China
Liankai Bu: Shandong Key Laboratory of Civil Engineering Disaster Prevention and Mitigation, College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China
Zhihong Li: Shandong Key Laboratory of Civil Engineering Disaster Prevention and Mitigation, College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China
Keyan Long: Shandong Key Laboratory of Civil Engineering Disaster Prevention and Mitigation, College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China

Sustainability, 2025, vol. 17, issue 20, 1-20

Abstract: Frequent water and mud inrush accidents during karst tunnel construction severely impact tunnel construction safety, environmental sustainability, and the long-term use of infrastructure. Therefore, conducting practical risk assessment for karst tunnel water and mud inrush is crucial for promoting sustainable practices in tunnel engineering, as it can mitigate catastrophic events that lead to resource waste, ecological damage, and economic loss. This paper establishes an improved weighted cloud model for karst tunnel water and mud inrush risk to evaluate the associated risk factors. The calculation of subjective weight for risk metrics adopts the ordinal relationship method (G1 method), which is a subjective weighting method improved from the analytic hierarchy process. The calculation of objective weight employs the improved entropy weight method, which is superior to the traditional entropy weight method by effectively preventing calculation distortion. Game theory is applied to calculate the optimal weight combination coefficient for two computational methods, and cloud model theory is finally introduced to reduce the fuzziness of the membership interval during the assessment process. This study applied the established risk assessment model to five sections of the Furong Tunnel and Cushishan Tunnel in Southwest China. The final risk ratings for these sections were determined as “High Risk,” “High Risk,” “Medium Risk,” “High Risk,” and “Moderate Risk”, respectively. These results align with the findings from field investigations, validating the effectiveness and reliability of the cloud model-based mud and water outburst risk assessment using combined weighting. Compared to traditional methods such as fuzzy comprehensive evaluation and entropy weighting, the evaluation results from this study’s model demonstrate higher similarity and reliability. This provides a foundation for assessing mud and water outburst hazards and other tunnel disasters.

Keywords: karst tunnel; water and mud inrush; risk assessment; cloud model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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