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Numerical modeling is widely acknowledged as a highly precise method for understanding the dynamics of contaminant transport in groundwater. However, due to the intricate characteristics of environmental systems and the lack of accurate information, the results are susceptible to a significant degree of uncertainty. Numerical models must explicitly consider related uncertainties in parameters to facilitate robust decision-making. In a Chromium Residue Site located in southern China (the study area), this study employed Monte Carlo simulation to assess the impact of variability in key parameters uncertainty on the simulation outcomes. Variogram analysis of response surface (VARS), global sensitivity analysis, and an XGBoost (version 2.0.0)-based surrogate model was employed to overcome the substantial computational cost of Monte Carlo simulation. The results of numerical simulation indicate that the contaminant is spreading downstream towards the northern boundary of contaminated site near Lianshui River, threatening water quality. Furthermore, migration patterns are complex due to both downstream convection and upstream diffusion. Sensitivity analysis identified hydraulic conductivity, recharge rate, and porosity as the most influential model parameters, selected as key parameters. Moreover, uncertainty analysis indicated that the variability in key parameters has a minimal impact on the simulation outcomes at monitoring wells near the contaminant source. In contrast, at wells positioned a considerable distance from the contaminant source, the variability in key parameters significantly influences the simulation outcomes. The surrogate model markedly mitigated computational workload and calculation time, while demonstrating superior precision and effectively capture the non-linear correlations between input and output of the simulation model. [ABSTRACT FROM AUTHOR]

• First hydrogeological model established for URL site of HLW disposal in China. • The effect of the hydraulic influence zones of faults is incorporated in the numerical model. • Different variations in the horizontal and vertical directions of hydraulic conductivity are considered. • A total of 120 stochastic parameterized models are presented. • Hydraulic conductivity < 10−9 m/s at high-level radioactive waste disposal depth. 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. [ABSTRACT FROM AUTHOR]