A method for identifying anomalous values of groundwater levels at candidate sites for the geological disposal of high-level radioactive waste
Dynamic groundwater monitoring provides critical foundational data for the safety assessment of candidate sites for the geolog-ical disposal of high-level radioactive waste.However,research has revealed that actual monitoring data frequently contain numerous a-nomalous 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 val-ue detection of the groundwater level using local weighted regression-based time series decomposition and the minimum covariance de-terminant(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 anoma-lous 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 detec-tion of different types of anomalous events.
万方数据
维普
