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ORIGINAL RESEARCH article

Front. Earth Sci.
Sec. Geohazards and Georisks
Volume 12 - 2024 | doi: 10.3389/feart.2024.1404133

A Novel Model for Risk Prediction of Water Inrush and Its Application in a Tunnel in Xinjiang, China

Provisionally accepted
Yuanyue Pi Yuanyue Pi *Zhong Sun Zhong Sun Yangyang Lu Yangyang Lu Jian Xu Jian Xu
  • Nanyang Institute of Technology, Nanyang, China

The final, formatted version of the article will be published soon.

    Tunnel water inrush may not only cause hundreds of millions of economic losses and serious casualties, but also leads to a series of ecological and environmental problems such as the decline of groundwater level, soil salinization and surface vegetation degradation. In this study, considering hydrogeology, construction, and dynamic monitoring factors, a new risk prediction model of water inrush is proposed based on fuzzy mathematical theory. The element of novelty is that this approach comprehensively considers nonlinearity and randomness factors, and the index values, weights, and membership are expressed as interval numbers instead of constant values. The interval membership degree of each index is calculated by an improved sigmoid membership function (SMF). A coupling algorithm of improved analytic hierarchy process and entropy method is used to calculate the index weight. In addition, the Boolean matrix is introduced into the relative advantage analysis of the interval vector, and the final risk level of water inrush is determined by the ranking result. The proposed model is applied to the analysis of the water inrush risk in the Ka-Shuang 2 (KS2) tunnel in Xinjiang, China. The predicted results align well with the actual excavation results, which indicates that this novel model has high accuracy and reliability.Simultaneously, a risk management response mechanism for different risk levels of water inrush is discussed, which is expected to provide a new research perspective for risk control of other related projects and promote regional sustainable development.

    Keywords: Water inrush, SMF, Comprehensive weight, Interval number, risk prediction

    Received: 20 Mar 2024; Accepted: 17 Jul 2024.

    Copyright: © 2024 Pi, Sun, Lu and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yuanyue Pi, Nanyang Institute of Technology, Nanyang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.