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地震 ›› 1998, Vol. 18 ›› Issue (2): 189-194.

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地震非均匀度在甘肃及邻区中强地震中短期预报中的应用

肖丽珠, 柳永秀, 石航   

  1. 中国兰州 730000 国家地震局兰州地震研究所
  • 收稿日期:1997-09-01 修回日期:1997-11-05 出版日期:1998-04-30 发布日期:2022-05-10
  • 作者简介:肖丽珠,女,1951年2月出生,高级工程师,主要从事测震学分析预报等研究工作。

APPLICATION OF INHOMOGENEOUS DEGREE OF SEISMICITY TO MEDIUM-AND SHORT-TERM EARTHQUAKE PREDICTION IN GAN SU PROVINCE AND ITS NEIGHBOURING AREA

Xiao Lizhu, Liu Yongxiu, Shi Hang   

  1. Lanzhou Institute of Seismology, SSB, Lanzhou 73000, China
  • Received:1997-09-01 Revised:1997-11-05 Online:1998-04-30 Published:2022-05-10

摘要: 在地震学中长期预报的基础上,近几年地震学攻关指南的应用实践中发现,刻画强震前中小地震活动在时空分布上不均匀性的参量——地震非均匀度(GL值)能较好地反映震前小震活动由稳定向非稳定过渡的中短期震兆特点。 结合甘肃及邻区中强以上地震的预报研究,运用GL值进行时空扫描,结果发现除个别省界边缘地区地震外,所有5.4级以上地震前1~2a,在震中300 km范围内, 2.0级以上小震活动在不同时段均显示出明显的非均匀特性——GL≥1.0。

关键词: 中短期异常分析, 地震非均匀度, GL值时空扫描监, 测预报

Abstract: Through study and application of “Guide to Earthquake Prediction by the Seismo logical Method”, based on the practice of long-and medium-term earthquake prediction in recent years, the authors discovered that the inhomogeneous degree of seismicity (GL value) is a useful parameter for describing the temporal and spatial inhomogeneous distribution of small and moderate earthquakes prior to the strong ones. It can reflect the characteristics of earthquake precursors in short-medium term, that is, the activity of small earthquakes changes from both stable and unstable statuses before a moderate or strong earthquake. Synthesizing the study of the moderate and strong earthquake predictions in Gansu and its neighbouring area, and applying GL value in time and space scanning of earthquakes occurred in the study region, it is found that one or two years before occurrence of all moderate and strong earthquakes (MS≥5.4) except a few events, the activity of small earthquakes (MS≥2.0) shows obviously the inhomog eneous feature of seismicity (GL≥1.0), 300 km from the epicenters during different periods.

Key words: Analysis of medium-and short-term precursors, Seismic inhomogeneous degree, Time-space scanning of GL value, Monitoring and synthesizing the study of the prediction