Analysis of the Earthquake Early Warning of the Luding M6.8 Earthquake on September 5, 2022
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摘要: 2022年9月5日，四川省泸定县发生M6.8地震。针对四川地震预警台网部署的EEW和JEEW地震预警处理软件产出的地震预警信息进行分析，从观测数据质量、预警参数测定、减灾效能等方面对地震预警处理过程进行系统性分析，检验预警软件处理结果的可靠性。结果表明，EEW和JEEW分别在震后 4.4、8.2 s产出了首报预警信息，震级偏差分别为−1.6、−0.8，震中位置偏差分别为11.2、0.8 km，随着时间的延长和触发台站的增多，预警处理结果最终与正式目录结果趋于一致；本次地震预警盲区半径为14.7 km，预警盲区以外，烈度Ⅵ度以上区域的预警时间为0～21 s，预警有效获益区内减灾效能显著。Abstract: On September 5, 2022, a M6.8 earthquake struck Luding county, Sichuan province. This paper examines earthquake early warning information generated by two sets of earthquake early warning processing software, EEW and JEEW, deployed within the Sichuan earthquake early warning network. EEW and JEEW issued their initial warning alerts 4.4 seconds and 8.2 seconds after the earthquake, respectively. The magnitude deviations were −1.6 and −0.8, while the epicenter location deviations were 11.2 km and 0.8 km, respectively. Over time and with increased data from additional monitoring stations, the early warning processing results eventually aligned with the findings of the official earthquake catalog. The earthquake early warning information had a blind area radius of 14.7 km. Outside this blind area, regions experiencing intensity level VI or higher were provided with warning times ranging from 0 to 21 seconds. The effectiveness of disaster mitigation was evident within the operational scope of the early warning system.
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图 1 四川地震预警台网台站分布
Figure 1. Distribution of seismic stations of Sichuan earthquake early warning network
图 2 泸定M6.8地震震中距100 km内台站分布
Figure 2. Distribution of stations within 100 km from the epicenter of the Luding M6.8 earthquake
图 3 盲区半径
$ {{R}}_{{{\mathrm{BZ}}}} $ 与台间距$ {D} $ 的关系Figure 3. Relationship between blind-zone radius
$ {{R}}_{{{\mathrm{BZ}}}} $ and interstation distance$ {D} $ 
图 4 预警触发台站震源距与走时拟合结果
Figure 4. The fitting results of hypocentral distance and travel time of early warning-triggered stations
图 5 EEW和JEEW产出第1～30次预警结果参与计算台站数量及用时
Figure 5. The number of stations and time taken for the 1st to 30th warning results produced by EEW and JEEW
图 6 EEW 和JEEW产出第1～30次预警处理结果的震中位置偏差
Figure 6. The epicenter position deviation of the 1 st to 30 th early warning processing results produced by EEW and JEEW
图 7 EEW产出第3～5次预警处理结果的参与计算台站分布
Figure 7. Distribution of participating stations for the processing results of the 3 rd to 5 th EEW early warning output
图 9 泸定M6.8地震预警减灾效能
Figure 9. Map showing earthquake early warning disaster mitigation efficacy of Luding M6.8
表 1 台站主要安装仪器参数特征
Table 1. The specific parameter characteristics of the main instruments installed in the stations
台站类型 仪器名称 仪器型号 安装方式 量程 噪声 频带范围 基准站 宽频带地震计 GL-CS60 摆坑 0.01 m/s −170 dB@10 Hz
−180 dB@0.01 Hz0.016 7～80 Hz GL-CS120 摆坑 0.01 m/s −170 dB@10 Hz
−180 dB@0.01 Hz0.008 3～80 Hz 力平衡式加速度计 JS-A2 地面 2 g −130 dB DC～100 Hz 三分向加速度计 GL-A4 地面 2 g −130 dB DC～250 Hz（−3 dB） DC～150 Hz
（加速度响应平坦）基本站 力平衡式加速度计 JS-A2 地面 2 g −130 dB DC～100 Hz 一般站 MEMS加速度计 MEMS 地表 2 g −60～−110 dB DC～200 Hz以上 
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表 2 震中距100 km内数据缺失台站
Table 2. The stations with data missing within 100 km from the epicenter
震中距范围/km 台站总数 数据缺失台站 台站数 基准站 基本站 一般站 0～50 29 8 2 1 5 0～100 129 10 3 1 6
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表 3 震中距100 km内触发台站延时
Table 3. Statistical delay triggering times for stations within 100 km from the epicenter
类别 延时/s ≤1.0 1.0～2.0 1.51～2.00 2.01～2.5 ≥2.5 三类台站数量 124 0 2 0 3 基准站数量 23 0 2 0 0 基本站数量 18 0 0 0 2 一般站数量 83 0 0 0 1
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表 4 泸定M6.8地震EEW和JEEW预警处理结果（1～30次）
Table 4. EEW and JEEW early warning processing results of Luding M6.8 earthquake （1～30 times）
EEW地震预警产出 JEEW地震预警产出 处理
序号用时/s 触发
台站数纬度/(°N) 经度/(°E) 预警
震级定位
偏差/km处理
序号用时/s 触发
台站数纬度/(°N) 经度/(°E) 预警
震级定位
偏差/km1 3.9 3 29.64 102.18 4.1 10.7 第1报 8.2 19 29.59 102.09 6.0 0.8 第1报 4.4 5 29.64 102.18 5.2 11.2 2 9.3 23 29.59 102.09 6.0 0.5 3 4.9 5 29.64 102.18 5.4 11.2 3 10.1 27 29.59 102.07 6.5 0.6 4 5.5 7 29.57 102.07 5.9 2.0 4 10.7 34 29.59 102.08 6.4 0.2 5 6.0 10 29.58 102.08 5.7 1.1 5 11.4 39 29.59 102.08 6.3 0.4 6 6.5 10 29.58 102.08 6.1 1.1 6 11.6 40 29.59 102.07 6.3 0.6 7 7.0 12 29.58 102.08 6.0 1.1 7 12.3 50 29.59 102.09 6.3 0.9 8 7.6 13 29.59 102.09 6.2 1.1 8 13.2 53 29.60 102.09 6.3 1.1 9 8.1 14 29.59 102.09 6.6 1.1 9 13.5 56 29.59 102.09 6.4 1.2 10 8.5 16 29.59 102.09 6.5 1.1 10 14.2 59 29.59 102.09 6.3 1.1 11 9.1 18 29.59 102.09 6.3 1.1 11 14.6 65 29.60 102.09 6.3 1.5 12 9.6 19 29.59 102.08 5.9 0.4 12 15.3 71 29.60 102.09 6.3 1.4 13 10.2 24 29.59 102.09 6.7 1.1 13 16.3 82 29.60 102.09 6.3 1.5 14 10.7 28 29.59 102.09 6.7 1.1 14 17.3 91 29.60 102.10 6.3 1.6 15 11.2 34 29.60 102.09 6.7 1.2 15 19.4 114 29.60 102.09 6.3 1.3 16 11.7 39 29.59 102.08 6.8 0.4 16 20.5 132 29.60 102.09 6.4 1.5 17 12.2 44 29.60 102.08 6.5 0.7 17 20.9 133 29.60 102.09 6.4 1.5 18 12.9 49 29.60 102.09 6.8 1.2 18 21.8 144 29.60 102.09 6.4 1.4 19 13.7 56 29.60 102.10 6.7 1.8 19 22.7 156 29.60 102.09 6.4 1.5 20 14.6 65 29.60 102.10 6.8 1.8 20 23.6 168 29.60 102.09 6.4 1.5 21 15.2 71 29.60 102.10 6.8 1.8 21 24.3 170 29.60 102.09 6.4 1.5 22 15.9 76 29.60 102.10 6.7 1.8 22 25.1 184 29.59 102.09 6.4 1.4 23 16.9 84 29.60 102.10 6.8 1.8 23 25.6 190 29.60 102.09 6.4 1.4 24 17.4 86 29.60 102.10 6.8 1.8 24 26.6 211 29.59 102.09 6.4 1.4 25 18.1 91 29.60 102.10 6.8 1.8 25 27.1 218 29.59 102.09 6.4 1.4 26 19.2 100 29.60 102.10 6.8 1.8 26 28.2 229 29.59 102.09 6.4 1.3 27 20.7 112 29.60 102.10 6.8 1.8 27 28.8 240 29.59 102.09 6.3 1.3 28 23.4 130 29.60 102.10 6.8 1.8 28 29.7 251 29.59 102.09 6.3 1.2 29 31.9 165 29.60 102.10 6.8 1.8 29 30.5 262 29.59 102.09 6.3 1.2 30 31.6 273 29.60 102.10 6.8 1.8 30 31.2 283 29.59 102.09 6.3 1.1
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表 5 地震预警系统理论处理时间参数含义
Table 5. The parameter explanation of theoretical processing time of earthquake early warning system
影响参数 下标含义 解释说明 影响因素 $ {\Delta }{{t}}_{{{\mathrm{a}}}} $ alert 地震预警理论处理时间 $ {\Delta }{{t}}_{{{\mathrm{s}}}}{、}{\Delta }{{t}}_{{{\mathrm{pa}}}}{、}{\Delta }{{t}}_{{{\mathrm{d}}}}{、}{\Delta }{{t}}_{{{\mathrm{h}}}}{、}{\Delta }{{t}}_{{{\mathrm{p}}}} $ $ {\Delta }{{t}}_{{{\mathrm{s}}}} $ station P波到达台站理论时间 台站密度 $ {}{\Delta }{{t}}_{{{\mathrm{pa}}}} $ pack 台站数据打包时间 地震监测仪器运行状态 $ {\Delta }{{t}}_{{{\mathrm{d}}}} $ delay 数据传输延迟时间 网络传输情况 $ {\Delta }{{t}}_{{{\mathrm{h}}}} $ handle 中心数据处理时间 预警软件及硬件平台性能 $ {\Delta }{{t}}_{{{\mathrm{p}}}} $ p-wave 所用数据的P波窗窗长 时钟准确度及波形记录质量
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杜航,王俊,江昊琳等,2021. 中国地震预警延迟时间算法及其对预警盲区的影响研究. 中国地震,37(1):216−226.Du H., Wang J., Jiang H. L., et al., 2021. Research on the delay time algorithm of earthquake early warning and its influence on the early warning blind area in China. Earthquake Research in China, 37(1): 216−226. (in Chinese) 黄文辉,沈玉松,吕作勇等,2016. 地震超快速报系统试运行结果评估. 华南地震,36(4):1−7.Huang W. H., Shen Y. S., Lyu Z. Y., et al., 2016. Evaluating the results of the earthquake very fast report system. South China Journal of Seismology, 36(4): 1−7. (in Chinese) 金星,2021. 地震预警与烈度速报−−理论与实践. 北京:科学出版社.Jin X. ,2021. Earthquake early warning and rapid intensity reporting:theory and practice. Beijing:Science Press. (in Chinese) 李佳威,2017. 地震早期预警系统(EEWS)“盲区”控制的若干问题. 北京:中国地震局地球物理研究所. Li J. W. ,2017. ‘Blind zone control’ of earthquake early warning system (EEWS). Beijing:Institute of Geophysics,China Earthquake Administration. (in Chinese). 李萍萍,江鹏,李同林等,2022. 2021年9月16日四川泸县 M S6.0地震强地面运动特征分析. 地震学报,44(2):260−270.Li P. P., Jiang P., Li T. L., et al., 2022. The strong ground motion characteristics of M S6.0 Luxian, Sichuan, earthquake on 16 September 2021. Acta Seismologica Sinica, 44(2): 260−270. (in Chinese) 李山有,金星,马强等,2004. 地震预警系统与智能应急控制系统研究. 世界地震工程,20(4):21−26.Li S. Y., Jin X., Ma Q., et al., 2004. Study on earthquake early warning system and intellegent emergency controling system. World Earthquake Engineering, 20(4): 21−26. (in Chinese) 李同林,彭朝勇,李萍萍等,2021. 四川地震预警网外玛多7.4级地震预警分析研究. 中国地震,37(3):551−563.Li T. L., Peng C. Y., Li P. P., et al., 2021. Early warning processing results for 22 May 2021 Maduo, Qinghai M 7.4 earthquake from outside the Sichuan earthquake early warning network. Earthquake Research in China, 37(3): 551−563. (in Chinese) 梁艳,吕芳,李丽,2017. 山西地震台网地震预警时间及盲区半径分析. 地震地磁观测与研究,38(4):65−69.Liang Y., Lv F., Li L., 2017. The warning times and blind-zone radius of Shanxi seismic network. Seismological and Geomagnetic Observation and Research, 38(4): 65−69. (in Chinese) 马强,2008. 地震预警技术研究及应用. 哈尔滨:中国地震局工程力学研究所. 宋晋东,余聪,李山有,2021. 地震预警现地PGV连续预测的最小二乘支持向量机模型. 地球物理学报,64(2):555−568.Song J. D., Yu C., Li S. Y., 2021. Continuous prediction of onsite PGV for earthquake early warning based on least squares support vector machine. Chinese Journal of Geophysics, 64(2): 555−568. (in Chinese) 王俊,刘红桂,周昱辰,2021. 地震预警技术的应用与展望. 防灾减灾工程学报,41(4):874−882.Wang J., Liu H. G., Zhou Y. C., 2021. Application and prospect of earthquake early warning technology. Journal of Disaster Prevention and Mitigation Engineering, 41(4): 874−882. (in Chinese) 王澜,戴贤春,习年生等,2019. 高速铁路地震预警及紧急处置时效性研究. 中国铁道科学,40(5):118−127.Wang L., Dai X. C., Xi N. S., et al., 2019. Study on time effectiveness of earthquake early warning and emergency disposal for high speed railway. China Railway Science, 40(5): 118−127. (in Chinese) 王勇胜,韦永祥,2018. 地震预警技术研究现状及展望. 科学技术创新,(14):22−24. 杨陈,郭凯,张素灵等,2015. 中国地震台网现状及其预警能力分析. 地震学报,37(3):508−515.Yang C., Guo K., Zhang S. L., et al., 2015. Status quo of China earthquake networks and analyses on its early warning capacity. Acta Seismologica Sinica, 37(3): 508−515. (in Chinese) 应急管理部,2022. 应急管理部发布四川泸定6.8级地震烈度图. (2022-09-11). https://www.mem.gov.cn/xw/yjglbgzdt/202209/t20220911_422190.shtml. 张晁军,陈会忠,沈萍等,2022. 地震预警实质的探讨. 地震科学进展,52(4):154−160.Zhang C. J., Chen H. Z., Shen P., et al., 2022. Discussion on the essence of earthquake early warning. Progress in Earthquake Sciences, 52(4): 154−160. (in Chinese) Erdik M., Fahjan Y., Ozel O., et al., 2003. Istanbul earthquake rapid response and the early warning system. Bulletin of Earthquake Engineering, 1(1): 157−163. doi: 10.1023/A:1024813612271 Horiuchi S., Negishi H., Abe K., et al., 2005. An automatic processing system for broadcasting earthquake alarms. Bulletin of the Seismological Society of America, 95(2): 708−718. doi: 10.1785/0120030133 Hsiao N. C., Wu Y. M., Shin T. C., et al., 2009. Development of earthquake early warning system in Taiwan. Geophysical Research Letters, 36(5): L00B02. Kamigaichi O. , Saito M. , Doi K., et al., 2009. Earthquake early warning in Japan: warning the general public and future prospects. Seismological Research Letters, 80 (5): 717−726. Kuyuk H. S., Allen R. M., 2013. Optimal seismic network density for earthquake early warning: a case study from California. Seismological Research Letters, 84(6): 946−954. doi: 10.1785/0220130043 Peng C. Y., Jiang P., Ma Q., et al., 2022. Chinese nationwide earthquake early warning system and its performance in the 2022 Lushan M6.1 earthquake. Remote Sensing, 14(17): 4269. doi: 10.3390/rs14174269 Song J. D., Zhu J. B., Wang Y., et al., 2022. On-site alert-level earthquake early warning using machine-learning-based prediction equations. Geophysical Journal International, 231(2): 786−800. doi: 10.1093/gji/ggac220 Song J. D., Zhu J. B., Li S. Y., 2023. MEANet: magnitude estimation via physics-based features time series, an attention mechanism, and neural networks. Geophysics, 88(1): V33−V43. doi: 10.1190/geo2022-0196.1 Suárez G., Espinosa-Aranda J. M., Cuéllar A., et al., 2018. A dedicated seismic early warning network: the Mexican seismic alert system (SASMEX). Seismological Research Letters, 89(2A): 382−391. doi: 10.1785/0220170184 Vallée M., Ampuero J. P., Juhel K., et al., 2017. Observations and modeling of the elastogravity signals preceding direct seismic waves. Science, 358(6367): 1164−1168. doi: 10.1126/science.aao0746 Wu Y. M., Teng T. L., 2002. A virtual subnetwork approach to earthquake early warning. Bulletin of the Seismological Society of America, 92(5): 2008−2018. doi: 10.1785/0120010217 -
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