A numerical method for predicting groundwater inflow into mountain tunnel, taking into account rainfall recharge and lithological distribution over a large area. Issue 7 (October 2021)

• Record Type: Journal Article
• Authors: Liu, J H; Zhang, W B; Li, X J; Liu, Bl; Xu, B; Xi, Y
• Is Part Of: IOP conference series. Volume 861:Issue 7(2021)
• Publication Date: 2021-10
• Subjects: numerical method -- iS3 -- mountain tunnel -- groundwater inflow -- large area; Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/861/7/072040
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: Groundwater inflow is related to the safety of the tunnels and the groundwater ecological environment around the tunnel site. Despite the tremendous effort invested in the area, there are few numerical methods for predicting groundwater inflow into a tunnel, taking into account the crossing faults and complex hydrogeology with different lithological distributions. This study presents a numerical method for predicting groundwater inflow into a tunnel using ModFlow software, which considers factors such as rainfall recharge, large area three-dimensional topography, faults, and lithological distribution. Based on groundwater inflow data, hydraulic conductivity inversion is performed to obtain the actual permeability of the surrounding rock. Then the proposed numerical method is verified against the results obtained on the site. Finally, the difference between groundwater inflow and the effect of tunnel excavation on groundwater drawdown is analyzed. The results show that: (1) the errors of groundwater inflow between the proposed numerical method and the measured results between two measurement sites are in the range of 2.0%–28.6%, and the errors of the total groundwater inflow at each measurement point are within the range of 11.0%–28.3%; (2) The maximum drawdown of the tunnel site is 4.5 m. The proposed numerical method aims to provide a reasonable and efficient method for predicting groundwater inflow in a water-rich mountain tunnel in difficult geological conditions. The numerical method is then encapsulated in a groundwater inflow forecasting microservice and integrated into the infrastructure Smart Service System (iS3).