A method for identifying anomalous values of groundwater levels at candidate sites for the geological disposal of high-level radioactive waste
JI Zi-Jian1,2(), Zhou Zhi-Chao1,2, Zhao Jing-Bo1,2, JI Rui-Li1,2, ZHANG Ming1,2
1. Division of Environmental Engineering, Beijing Research Institute of Uranium Geology, Beijing 100029, China 2. CAEA Innovation Center for Geological Disposal of High-Level Radioactive Waste, Beijing 100029, China
Dynamic groundwater monitoring provides critical foundational data for the safety assessment of candidate sites for the geological disposal of high-level radioactive waste. However, research has revealed that actual monitoring data frequently contain numerous anomalous values, severely interfering with the accurate assessment of the dynamic monitoring process. Therefore, there is an urgent need to develop an efficient method to accurately identify these anomalous values. This study built a combined model for anomalous value detection of the groundwater level using local weighted regression-based time series decomposition and the minimum covariance determinant (MCD) method. This combined model allowed the MCD method to achieve anomaly detection in more independent residuals. Results indicate that the combined model exhibited higher sensitivity and detection accuracy for anomalous data than the single MCD model. Furthermore, this study established that the threshold of the combined model should be close to the actual proportion of anomalous values to achieve optimal detection results. Besides, this study validated the applicability of the combined model using groundwater level data from boreholes BSQ01, BSQ25, BS35, and BS26 at the new site. The validation results demonstrate that the combined model can accurately identify anomalous values amidst a large volume of data on the normal groundwater level and is applicable to the detection of different types of anomalous events.
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