科学评估区域地震预警能力既是对国家地震烈度速报与预警工程预期效果的检验,也是进一步优化预警台网的依据.选用台站背景噪声最大概率密度峰值位移(PGD)作为评价指标,计算陕西省预警测震、强震、烈度计台网的背景噪声水平,结果表明,测震台网噪声水平比强震台网小 1 个数量级,比烈度计台网小 3 个数量级.基于所计算的背景噪声水平,评估陕西地区3类台网的地震监测能力,结果表明,测震台网地震监测能力显著高于强震和烈度计台网.考虑到预警系统的时效性以及预警首报时间与地震监测台站分布密度的相关性,将"三网"进行融合,结果发现,地震预警能力得到显著提升,95%的监测区域地震预警最小震级可达ML 3.7,且预警首报时间可达 6.3 s,比测震单网提前约 16.7 s.
Evaluation of regional earthquake early warning capability of Shaanxi Province
Scientific evaluation of the regional earthquake early warning(EEW)capacity is not only the test of the expected effec of the national seismic intensity rapid reporting and early warning project,but also the basis for further optimization of the seismic network.The maximum probability density peak ground displacement(PGD)is adopted as the index parameter of seismic background noise level.We calculate the seismic noise level of three types of sensor networks of Shaanxi Province,including the seismometer network,the strong-motion seismograph network,and the seismic intensity meter network.The results show the noise level of the seismometer network is almost one order of magnitude smaller than that of the strong-motion seismograph network,and three orders of magnitude smaller than that of the seismic intensity meter network.Based on the noise level,the monitoring capability of the three types of sensor networks is evaluated.The results indicate that the capability of the seismometer network is obviously better than that of the strong-motion seismograph network and the seismic intensity meter network.Considering the timeliness of the early warning system and the correlation between the first warning time and the distribution density of earthquake monitoring stations,the"three networks"are integrated,and it is found that the earthquake early warning capability is significantly improved.95%of the monitoring areas had a minimum earthquake magnitude of ML 3.7,and the first warning time could reach 6.3 s,about 16.7 s earlier than the single seismic network.
earthquake early warningambient noise levelmonitoring capabilityfirst warning time
万方数据
维普
