关键词: 地震前兆, 异常识别, 长期异常, 中期异常, 短临异常, 空间分布特征

Abstract: The complication of tectonics in CHina gives us an advantage to find some anomalies near orfar from the coming earthquake.They may be alert to the occurrence of a strong earthquake.However the problems are:1)before some strong earthquakes there were no anomalies,2)insome cases no earthquake occurred after the anomalies,and 3)in some cases the place with obvi-ous anomalies did not correspond to the epicenter.Therefore,studying the stages of anomaliesand analysing the cause and spatial distribution may help us to elucidate the problems.The deformation process in a region may be divided into 4 stages:stage Ⅰ is before the yieldpoint,and stage Ⅱ is between the yield point and peak strength point.Stages Ⅰ and Ⅱ may berelated to the long-term to medium-term stages before earthquake。Stage Ⅲ is between strengthpoint and instable point and stage Ⅳ is after instable point.Stage Ⅲ may be related to the short-term to imminent stages before earthquake.The anomalies appearing in stages Ⅰ and Ⅱ may becaused by the change of driving force and the anomalies in stage Ⅲ may be caused by the propa-gation or weakening of the fault and smoothening of the fault surface.A numerical modelling has been made to study the spatial distribution of anomalies in eachstages. In order to reveal the distribution and its causes more clearly,the increment mean stressδσ_m and the increment maximum shear stress δτ_max are calculated. It is shown that the distributionof δτ_max in stages Ⅰ and Ⅱ is similar to the background stress field.The distribution of δσ_m instage Ⅱ is outstanding on the en-echelon jogs.the distribution of δτ_max and δσ_m display an eight-petaline pattern and a four-quadrant pattern,respectively,the propagation point is in the center ofthe pattern.The temporal process of the distribution of the increment stress field in an en-eche-lon fault system has also been studied.

Key words: Earthquake precursor, Anomaly recognition, Long-term anomaly, Medium-term anomaly, Short-impending anomaly, Spatial distribution characteristic