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In this study, a number of typical precursory anomalies recorded by stations in Qinghai, Gansu, Sichuan, Xinjiang, Ningxia, Hebei and Shaanxi provinces and autonomous regions before the M_S8.1 earthquake in the west of Kunlun Mountains Pass are collected and checked. According to the standards of earthquake cases in China, the criteria of the precursory anomalies are determined, and 53 distinguished. The characteristics of these anomalies before the M_S8.1 earthquake are analyzed, with results showing a very large earthquake affected area. The precursory anomalies recorded by instruments were 2900 km away from the epicenter, and according to the study in this paper, reached 2100 km away. The results also show that the anomalies present characteristics of long duration, multi-measurement items and large-amplitude variation. The authors believe that in large earthquake monitoring, attention should be paid to the variation of data over a large area, ranging up to thousands kilometers, with much denser earthquake observation networks.
In this study, a number of typical precursory anomalies recorded by stations in Qinghai, Gansu, Sichuan, Xinjiang, Ningxia, Hebei and Shaanxi provinces and autonomous regions before the M_S8.1 earthquake in the west of Kunlun Mountains Pass are collected and checked. to the standards of earthquake cases in China, the criteria of the precursory anomalies are determined, and 53 distinguished. The characteristics of these anomalies before the M_S8.1 earthquake are analyzed, with results showed a very large shock affected area. The precursory anomalies recorded by instruments were 2900 km away from the epicenter, and according to the study in this paper, reached 2100 km away. The results also show that the anomalies present characteristics of long duration, multi-measurement items and large-amplitude variation. The authors believe that in large earthquake monitoring, attention should be paid to the variation of data over a large area, ranging up to thousands kilometers, wit h much denser earthquake observation networks.