Temporal and spatial variation of apparent stress of small and medium earthquakes in Pingxiang and adjacent areas
The digital waveform data of 181 small and medium earthquakes ML≥1.8 in Pingxiang and adjacent areas of Jiangxi Province from 2009 to 2022 were selected.Based on Brune disk model and genetic algorithm,the apparent seismic stress in the area was calculated.By analyzing the spatio-temporal variation of the apparent stress,the stress level in the study area was discussed.The results show that the apparent stress values in Pingxiang and its adjacent areas range from 0.001 8 MPa to 1.76 MPa,and the average apparent stress is 0.076 MPa,which can be used as the background apparent stress level in this area.The apparent stress value increases with the increase of earthquake magnitude,and they are positively correlated with each other.The temporal variation of the apparent stress reveals that Pingxiang and its neighboring areas are in the stage of slow accumulation of stress,and the overall level is relatively low.The spatial distribution characteristics of the apparent stress show that the higher apparent stress values are concentrated in the north of the Pingxiang-Fengcheng fault zone.Through magnitude-frequency fitting,the average b-value in the study area is about 1.15.It is found that the small and medium earthquake intensive area is concentrated in the low b-value anomaly area of this fault zone,and the apparent stress value of this area is relatively high,indicating that the distribution of low b-value and high apparent stress value is more consistent with the distribution of small and medium earthquake intensive area.Further analysis shows that the seismic activity intensity and apparent stress level in the study area are lower than those in other areas of Jiangxi Province,but the frequent small earthquakes may be related to the wide distribution of coal resources and the relatively developed soluble rock formation in the area.
Pingxiang and adjacent areasapparent stresssource dynamic parameterspatio-temporal variation characteristicsb value
万方数据
维普
