A Dynamic Modeling Approach to Predict Water Inflow during Karst Tunnel Excavation

Abstract

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 Comparative Study on Steady-State Water Inflow into a Circular Underwater Tunnel with an Excavation Damage Zone

“…The constant total head on the inner circumference of lining h a is applied for Equations ( 10)- (12). For Equation ( 13), zero water pressure on the inner circumference of the lining is used, and A = h 2 − r E 2 .…”

“…Many efforts have been devoted to proposing effective methods to predict water inflow into tunnels over the past few decades. Four kinds of methods, including analytical solutions [8][9][10][11][12][13][14], numerical simulations [15][16][17][18][19], empirical formulas [20,21] and physical experiments [22], have been applied to estimate water inflow into tunnels.…”

“…It is worth noting that the formation of an excavation damage zone (EDZ) is expected to occur around tunnels due to excavation, and the EDZ is characterized by increased fractures, which lead to a significant increase in rock permeability [12,[37][38][39][40]. This argument is supported by several field measurements, as follows: Souley et al [41] reported hydraulic experiments by Canada's Underground Research Laboratory, and the results indicated that the permeability of the EDZ can be increased by approximately 5 orders of magnitude, compared with the original rock.…”

Prediction of the Mine Water Inflow of Coal-Bearing Rock Series Based on Well Group Pumping

“…These studies are on the water inflow and water inrush accidents of coal mines, but there are few reports on the water inflow of bauxite mines. The studies of the water inflow in tunnels are also reported [25,26]. Groundwater inflow into Karaj Water Conveyance (KWC) in Northern Iran was estimated using analytical and numerical methods [27].…”

Water Inflow Amount Prediction for Karst Tunnel with Steady Seepage Conditions

“…They used numerical calculations to predict the water inflow situation in the tunnel, providing a reference for corresponding tunnel engineering. Bai et al [22] proposed a tunnel water inflow prediction modeling method based on the pipeline flow process and considering karst bimodality and boundary conditions for tunnel water inflow problems in karst areas, providing some reference for predicting water inflow in karst tunnels. Mahmoodzadeh et al [23] used machine learning algorithms such as LSTM, DNN, KNN, SVR, DT, and GPR combined with hundreds of water inflow data to analyze the performance of LSTM and DNN algorithms in predicting tunnel water inflow.…”