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对强震地形变监测预报方法的思考

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简要回顾了中国地形变用于强震监测预报领域的发展过程及现状.对几次强震前得到的比较突出的地形变异常进行了分析,收集了大面积形变异常与强震中长期预测、地震前兆分布存在时间有序和空间配套,强震前发现巨幅形变异常,InSAR给出强震前地面垂向形变,强震前地倾斜异常,慢地震和预滑移等方面的研究成果.综合分析认为,强震前震中区附近存在与孕震体尺度相当的巨幅快速地面异常隆升.及时有效地捕捉强震前巨幅快速地面异常隆升的时间有序和空间配套的异常信息,可望针对人口稠密区域未来发生的强震给出具有减灾实效的预测预报意见,值得尝试.基于本研究提出了针对人口稠密的地震重点监视防御区开展高密度、大量程、低精度地倾斜观测的设想,并初步给出了观测方案、基本原理和数据计算处理方法.
Thoughts on Monitoring and Forecasting Methods of Strong Earthquake with Crust Deformation Data
The development process and present situation of strong earthquake monitoring and prediction with crust deformation data in China are reviewed briefly.The prominent crust deformation anomalies obtained before several strong earthquakes are analyzed.The study results in several aspects are collected including earthquake monitoring and predic-tion,large area deformation anomaly,time order and spatial matching of earthquake pre-cursor distribution,huge deformation anomaly before strong earthquakes,ground vertical deformation before strong earthquakes by InSAR,ground tilt anomaly,slow earthquake and pre-slip,etc.The comprehensive analysis shows that there is a large and rapid ground abnormal uplift near the epicenter of coming earthquakes.It is worth trying to capture timely and effectively the abnormal information of time order and space matching of large and rapid ground abnormal uplift before strong earthquakes,so as to provide effective pre-diction for the future strong earthquakes in densely populated areas.Based on this study,a high density,large range and low precision ground tilt observation is proposed for the key surveillance and defense areas of strong earthquakes with densely populated,and the observation scheme,basic principle and data calculation and processing method are given preliminarily.

Strong earthquake predictionCrust deformation monitoringHuge deforma-tionGround tiltGround uplift

薄万举、张立成、苏国营、徐东卓、赵立军

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中国地震局第一监测中心,天津 300180

强震预报 地形变监测 巨幅形变 地倾斜 地面隆起

中国地震局老科协工作经费及科研基金

301227202

2024

地震
中国地震局地震预测研究所 中国地震学会地震预报专业委员会 中国地震学会地震流体专业委员会 中国地震学会地震电磁学专业委员会

地震

CSTPCD北大核心
影响因子:0.733
ISSN:1000-3274
年,卷(期):2024.44(1)