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- W4387016822 abstract "Deep geological disposal is internationally accepted as a feasible and safe approach for high-level radioactive waste (HLW) disposal. To evaluate hydrogeological conditions in support of safety assessments for HLW disposal at the Xinchang preselected site in China, stochastic inverse models of site-scale groundwater flow were developed in this study to generate highly parameterized hydraulic conductivity fields for the fractured medium by adopting pilot point and null-space Monte Carlo methods. The hydraulic influence zones of the faults were carefully considered to have homogenous parameter values across the zones. A total of 120 multiple random realizations were generated to characterize the 3D spatial variations in hydraulic conductivity by conditioning to 1218 fixed pilot points. The simulated hydraulic heads of the realizations were in good agreement with observational data. The hydraulic conductivity fields close to the boreholes could be characterized in detail and had relatively low uncertainties. Furthermore, the hydraulic conductivity (K) values around underground research laboratory (URL) at the HLW disposal zone depth were less than 10-9 m/s. The K values obtained for most of the influence zones of these faults at this depth were consistent with hydraulic test data and ranged from 10-10 to 10-9 m/s, thereby indicating that the surrounding rock has low permeability and is suitable for HLW disposal. These findings offer new insights into hydrogeological conditions by providing key information on the permeability characteristics that need further focus on HLW disposal." @default.
- W4387016822 created "2023-09-26" @default.
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- W4387016822 date "2023-11-01" @default.
- W4387016822 modified "2023-10-18" @default.
- W4387016822 title "Numerical modeling of site-scale groundwater flow with stochastic parameterized hydraulic conductivity fields for geological disposal of high-level radioactive waste in China" @default.
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- W4387016822 doi "https://doi.org/10.1016/j.jhydrol.2023.130225" @default.
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