Abstract
The main purpose of seepage control in dams is to prevent dams and other foundation abutments from being destroyed by seepage erosion. This control is important for safe and efficient maintenance of hydraulic and geotechnical engineering structures in the reservoir areas. Back analysis of a seepage field based on measured data is an effective way to determine the initial distribution of the seepage field, which is essential for seepage control planning and implementation of safety measures. In this paper, a back analysis method and super-equivalent continuum model were used to analyse the natural seepage field parameters and seepage field analysis in the construction zone of the dam. The results of previous analyses of the seepage field and seepage control measures provided the basic parameters and model foundation; back analysis was used to determine the boundaries of the groundwater and the calculation parameters, modify the boundary conditions of the dam foundation excavation pit, and obtain the seepage field during the construction of the hub area. The results of the back analysis show that the natural groundwater distribution simulation is generally consistent with the field data, indicating that the finite element model is an important tool for simulating the engineering geological conditions of the dam area and rock mass permeability partition.
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Acknowledgments
This work reported here is supported by the CRSRI Open Research Program (No. CKWV2013202/KY) and National Natural Science Foundation of China (No. 51309189) and the State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin (China Institute of Water Resources and Hydropower Research) (No. IWHR-SKL-201303) and the Development of Characteristic Key Disciplines in the Local University by the Central Financial (Nos. 106-00X101, 106-5X1205) and the Program for Shaanxi Provincial Key Innovative Research Team (No. 2013KCT-015).
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Ren, J., Shen, Zz., Yang, J. et al. Back analysis of the 3D seepage problem and its engineering applications. Environ Earth Sci 75, 113 (2016). https://doi.org/10.1007/s12665-015-4837-1
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DOI: https://doi.org/10.1007/s12665-015-4837-1