地震地质 ›› 2025, Vol. 47 ›› Issue (4): 1075-1089.DOI: 10.3969/j.issn.0253-4967.2025.04.20240127

• 研究论文 • 上一篇    下一篇

积石山M6.2地震不同场地地震动观测数据的差异性分析

任佳1,3)(), 王秀英1,2), 赵国存2), 范熙伟4), 高鹏5), 张珊珊3), 马志霞2)   

  1. 1)河北红山巨厚沉积与地震灾害国家野外科学观测研究站, 邢台 054000
    2)应急管理部国家自然灾害防治研究院, 北京 100086
    3)张家口地震监测中心站, 张家口 075000
    4)中国地震局地质研究所, 北京 100029
    5)甘肃省地震局, 兰州 730000
  • 收稿日期:2024-10-25 修回日期:2024-12-09 出版日期:2025-08-20 发布日期:2025-10-09
  • 作者简介:

    任佳, 男, 1970年生, 高级工程师, 现主要从事地震观测技术与灾害监测技术研究, E-mail:

  • 基金资助:
    中国地震局地质研究所基本科研业务专项(IGCEA2106); 国家重点研发计划项目(2022YFC3003700); 国家自然科学基金(42071337); 中国地震局星火攻关项目(XH24002B)

COMPARISON OF DIFFERENCES IN GROUND MOTION DATA OBTAINED BY DIFFERENT SITE CONDITIONS OF THE JISHISHAN M6.2 EARTHQUAKE

REN Jia1,3)(), WANG Xiu-ying1,2), ZHAO Guo-cun2), FAN Xi-wei4), GAO Peng5), ZHANG Shan-shan3), MA Zhi-xia2)   

  1. 1)Hebei Hongshan National Observatory on Thick Sediments and Seismic Hazards, Xingtai 054000, China
    2)National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100086, China
    3)Zhangjiakou Central Seismic Station, Hebei Earthquake Agency, Zhangjiakou 075000, China
    4)Institute of Geology, China Earthquake Administration, Beijing 100029, China
    5)Gansu Earthquake Agency, Lanzhou 730000, China
  • Received:2024-10-25 Revised:2024-12-09 Online:2025-08-20 Published:2025-10-09

摘要:

中国地震预警网由部署于基岩、 土层、 基站地面3类场地条件的测震仪、 强震仪和烈度计仪器构成, 其中场地条件为基站地面的烈度计占绝大多数。 为了比较不同场地条件是否对地震动数据造成明显影响, 文中提出了利用计算机模拟置换实验对2组数据展开对比分析的方法。 以积石山M6.2地震获得的预警数据为例, 文中展示了利用建议方法对基岩与基站地面、 基岩与土层及土层与基站地面两两场地观测数据的比较分析过程。 对该地震预警数据的分析结果表明: 在黄土地区, 基站地面观测的地震动数据大于土层场地, 土层场地观测数据大于基岩场地; 仪器安装的场地条件会对地震动数据产生显著影响; 基站地面与土层场地观测数据的显著差异与地表黄土层的放大作用有关。 文中所述方法适用于复杂数据的定量比较和分析, 积石山地震数据分析结果也表明联合应用黄土区不同场地条件的预警数据时需考虑数据差异性问题。

关键词: 积石山地震, 中国地震预警网, 地震动数据, 场地条件, 数据差异性, 置换实验

Abstract:

The China earthquake early warning network(EEW)consists of three kinds of instruments: seismometer, strong motion accelerometer, and intensity meter deployed in rock sites, soil sites, and ground sites of communication stations. Of all the deployment sites, intensity meters account for the majority, and the ground motion data observed by intensity meters plays an essential role in the early warning network, as it can affect the timely response of the early warning system and the accuracy of the early warning parameters. Since the ground site of the communication station for the intensity meters differs significantly from traditional rock and soil sites, it requires more effort to validate the consistency of ground motion data obtained under various site conditions. Therefore, to determine whether deployment conditions can exert significant influence on ground motion data, a method is proposed to carry out the data comparison work using the permutation test technique based on computer simulation, and an application example of the proposed method is also demonstrated using the early warning data obtained from the Jishishan earthquake.

The implementation of the proposed method consists of two steps. Firstly, constructing a comparison dataset. Collocated data from two different site conditions are selected, and then data features extracted from the observations obtained from the two matched sites are used to construct a data pair. A set of data pairs is formed using all the observations from collocated sites, which aims at ensuring that all the influencing factors of ground motion, except the site condition, are similar between the data pairs. Secondly, testing data differences. To test whether there are significant data differences between the two matched data pairs, a computer simulation-based permutation test is used to create a distribution of the statistic quantity and then to compare the actual statistic with a pre-set confidence level to determine whether the data difference is significant. Assuming there is no data difference between the matched data pairs, randomly resampling is performed from the matched data pairs to construct another data pair. A statistical distribution can be obtained after repeating the resampling process many times. If the occurrence probability of the statistic obtained from actual observations, which can be counted from the many times resampled results, is less than the pre-set confidence level, there is a significant difference between the two groups of data pairs; otherwise, there is no significant difference between the two groups of data pairs.

The M6.2 Jishishan earthquake, which occurred in the northwest loess-covered region in China on December 18, 2023, is used to demonstrate the application of the abovementioned method and its implementation steps. Three kinds of comparison processes are shown in the paper, including the comparison processes between data from the rock site and the soil site, from the rock site and the communication station sites, and from the soil site and the communication station sites.

Based on the results obtained by comparing the three cases mentioned above, some conclusions are drawn as follows: (1)In the loess covering region, ground motion data from the communication station sites are significantly greater than that from the soil sites, which are then significantly greater than that from the rock sites. (2)Consistency correction is required when using ground motion data from different site conditions together, as there are significant data differences among the three site conditions. (3)Although both the communication station sites and soil site can be classified as soil condition, the burying depths of the instrument base into the soil layer are different, resulting to the significant greater of the ground motion data obtained from the communication station sites than that of the soil site, which can be explained by the obvious amplification effect of the surface loess layer.

The method proposed in this paper is suitable for the quantitative analysis of complex data, and the results of the Jishishan earthquake have significant reference value for the research and related applications of early warning ground motion data.

Key words: the Jishishan earthquake, the China Earthquake Early Warning Network, ground motion data, deployment condition, method to distinguish data difference, permutation test