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A Dynamic Modeling Approach to Predict Water Inflow during Karst Tunnel Excavation
During tunnel construction in strongly developed karst terrain, water inrush hazards often occur due to the complex hydrogeological conditions, which require accurate prediction of water inflow. In this study, a dynamic modeling approach for water inflow prediction of karst tunnels using the conduit flow process (CFP) is developed that considers both karst duality and changing boundary conditions of the tunnel. The CFP model has a good agreement with field-observed hydraulic head after calibration, and the Nash–Sutcliffe model efficiency (NSE) for the CFP model is 97.3%. Numerical calculation of water inflow was conducted in a successive drilling scenario with permeability change of the surrounding rocks. Additionally, a modular three-dimensional finite-difference ground-water flow model (MODFLOW) has been applied to predict the water inflow, for comparison with the CFP model. The prediction results obtained from the CFP model are generally in close agreement with the field-observed results; the percentage errors were 13.3% and 5.4%, respectively. For the MODFLOW model, the percentage errors were 34.2% and 36.8%, respectively. The proposed CFP model is both closer to reality and more reasonable than the MODFLOW model in predictive analysis of water inflow into karst tunnels, reflecting the influence of karst conduits on the water inflow process.
A Dynamic Modeling Approach to Predict Water Inflow during Karst Tunnel Excavation
During tunnel construction in strongly developed karst terrain, water inrush hazards often occur due to the complex hydrogeological conditions, which require accurate prediction of water inflow. In this study, a dynamic modeling approach for water inflow prediction of karst tunnels using the conduit flow process (CFP) is developed that considers both karst duality and changing boundary conditions of the tunnel. The CFP model has a good agreement with field-observed hydraulic head after calibration, and the Nash–Sutcliffe model efficiency (NSE) for the CFP model is 97.3%. Numerical calculation of water inflow was conducted in a successive drilling scenario with permeability change of the surrounding rocks. Additionally, a modular three-dimensional finite-difference ground-water flow model (MODFLOW) has been applied to predict the water inflow, for comparison with the CFP model. The prediction results obtained from the CFP model are generally in close agreement with the field-observed results; the percentage errors were 13.3% and 5.4%, respectively. For the MODFLOW model, the percentage errors were 34.2% and 36.8%, respectively. The proposed CFP model is both closer to reality and more reasonable than the MODFLOW model in predictive analysis of water inflow into karst tunnels, reflecting the influence of karst conduits on the water inflow process.
A Dynamic Modeling Approach to Predict Water Inflow during Karst Tunnel Excavation
Yang Bai (author) / Zheng Wu (author) / Tao Huang (author) / Daoping Peng (author)
2022
Article (Journal)
Electronic Resource
Unknown
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