摘要
对云南地区43个GNSS连续站2012-01~2018-12站点位移时间序列进行深加工处理,以期间发生的7次M≥5.7地震为样本,分别获取震前面应变和最大剪应变分布,并对震前应变场分布特征进行研究。结果表明:(1)7次M≥5.7地震前,云南地区存在显著的面应变变化趋势,多数情况下存在强挤压和强拉张并存的格局,累积面应变一般超过±4.0×10^(-8),地震多发生在面应变(特别是面挤压)变化的高梯度带上;(2)7次M≥5.7地震前,云南地区存在显著的最大剪应变变化趋势,累积最大剪应变一般超过5.0×10^(-8),地震多发生在最大剪应变变化的高梯度带上;(3)面应变(特别是面挤压)和最大剪应变变化的高梯度带可作为研判未来M≥5.7地震发震地点的重要区域。
To study the distribution characteristics of the strain field before the earthquake,we conduct deep processing of the station displacement time series of 43 continuous GNSS stations in Yunnan from January 2012 to December 2018,and take 7 earthquakes with M≥5.7 as samples to obtain the surface strain and maximum shear strain distribution before earthquakes.The results show that:1)Before the 7 earthquakes with M≥5.7,there is a significant surface strain change trend in Yunnan.In most cases,there is a pattern of strong compression and strong tension coexisting,and the cumulative surface strain generally exceeds±4.0×10^(-8).The earthquakes mostly occur in high-gradient belts where surface strain(especially the surface squeeze)changes.2)Before the 7 earthquakes with M≥5.7,there is a significant trend in the maximum shear strain change in Yunnan,and the cumulative maximum shear strain generally exceeds 5.0×10^(-8).The earthquakes mostly occur in the high gradient zone with the maximum shear strain change.3)The surface strain(especially the surface squeeze)and the high gradient zone of the maximum shear strain change can be used as important areas for the research and judgment of the earthquake location of M≥5.7 earthquakes in the future.
作者
杨建文
叶泵
陈佳
高琼
张华英
YANG Jianwen;YE Beng;CHEN Jia;GAO Qiong;ZHANG Huaying(Dali Center of China Earthquake Science Experimental Site,Binhai Road,Dali 671000,China;Field Scientific Observation and Research Station on Crustal Tectonic Activities in Northwest Yunnan,Binhai Road,Dali 671000,China)
出处
《大地测量与地球动力学》
CSCD
北大核心
2022年第3期225-230,共6页
Journal of Geodesy and Geodynamics
基金
云南省地震局科技人员传帮带培养项目(CQ3-2021004)
中国地震局“三结合”课题(3JH-2021045)
中国地震局震情跟踪定向工作任务(2021010105)
云南省陈颙院士工作站(2014IC007)。