Real-time numerical shake prediction and updating for earthquake early warning

Ground motion prediction is important for earthquake early warning systems, because the region’s peak ground motion indicates the potential disaster. In order to predict the peak ground motion quickly and precisely with limited station wave records, we propose a real-time numerical shake prediction and updating method. Our method first predicts the ground motion based on the ground motion prediction equation after P waves detection of several stations, denoted as the initial prediction. In order to correct the prediction error of the initial prediction, an updating scheme based on real-time simulation of wave propagation is designed. Data assimilation technique is incorporated to predict the distribution of seismic wave energy precisely. Radiative transfer theory and Monte Carlo simulation are used for modeling wave propagation in 2-D space, and the peak ground motion is calculated as quickly as possible. Our method has potential to predict shakemap, making the potential disaster be predicted before the real disaster happens. 2008 M _S8.0 Wenchuan earthquake is studied as an example to show the validity of the proposed method.     

Performance-based earthquake early warning

Significant investments are undergoing internationally to develop earthquake early warning (EEW) systems. So far, reasonably, the most of the research in this field was lead by seismologists as the issues to determine essential feasibility of EEW were mainly related to the earthquake source. Many of them have been brilliantly solved, and the principles of this discipline are collected in the so-called real-time seismology. On the other hand, operating EEW systems rely on general-purpose intensity measures as proxies for the impending ground motion potential and are suitable for population alert. In fact, to date, comparatively little attention was given to EEW by earthquake engineering, and design approaches for structure-specific EEW are mostly lacking. Applications to site-specific systems have not been extensively investigated and EEW convenience is not yet proven except a few pioneering cases, although the topic is certainly worthwhile. For example, in structure-specific EEW the determination of appropriate alarm thresholds is important when the false alarm may induce significant losses; similarly, economic appeal with respect to other risk mitigation strategies as seismic upgrade should be assessed. In the paper the least issues to be faced in the design of engineering applications of EEW are reviewed and some work done in this direction is discussed. The review presented intends to summarize the work of the author and co-workers in this field illustrating a possible performance-based approach for the design of structure-specific applications of EEW.     

On numerical earthquake prediction

Can earthquakes be predicted? How should people overcome the difficulties encountered in the study of earthquake prediction? This issue can take inspiration from the experiences of weather forecast. Although weather forecasting took a period of about half a century to advance from empirical to numerical forecast, it has achieved significant success. A consensus has been reached among the Chinese seismological community that earthquake prediction must also develop from empirical forecasting to physical prediction. However, it is seldom mentioned that physical prediction is characterized by quantitatively numerical predictions based on physical laws. This article discusses five key components for numerical earthquake prediction and their current status. We conclude that numerical earthquake prediction should now be put on the planning agenda and its roadmap designed, seismic stations should be deployed and observations made according to the needs of numerical prediction, and theoretical research should be carried out.     

用于地震预警的P波震相到时自动拾取

P波震相的自动拾取可用于地震预警中地震事件判别和地震定位,是实现基于地震台网地震预警的首要条件.针对地震预警中P波震相拾取的特点,本文发展了一套基于长短时平均(STA/LTA)和池赤准则(AIC)算法的多步骤P波自动拾取技术,应用Delaunay三角剖分提出了一种非几何相关的干扰信号剔除方法,并应用福建省数字地震台网记录对方法进行了验证,目前方法已经用到了福建省地震预警试验系统中.     

用于地震预警的三维实时定位方法

为了尽快定位地震,在“着未着”定位算法基础上,尝试引入三维地壳模型,构建具有三维空间格点分布的走时表.根据已触发台站的到时和未触发台站的位置信息设计概率分布函数,通过八叉树搜索方法,快速给出震源在三维空间的可能位置.使用波前追踪算法,计算中国几个地区三维地壳模型的走时网格,利用中国地震台网资料,对区域内发生的地震进行定位分析.结果显示,在一定的台网密度条件下,三维实时定位方法能在震后数秒给出震源位置,可满足地震预警要求.     

Evaluation of earthquake signal characteristics for early warning

This paper evaluates different characteristics for earthquake early warning.The scaling relationships between magnitude,epicenter distance and calculated parameters are derived from earthquake event data from USGS.The standard STA/LTA method is modified by adding two new parameters to eliminate the effects of the spike-type noise and small pulsetype noise ahead of the onset of the P-wave.After the detection of the P-wave,the algorithm extracts 12 kinds of parameters from the first 3 seconds of the P-wave.Then stepwise regression analysis of these parameters is performed to estimate the epicentral distance and magnitude.Six different parameters are selected to estimate the epicentral distance,and the median error for all 419 estimates is 16.5 km.Four parameters are optimally combined to estimate the magnitude,and the mean error for all events is 0.0 magnitude units,with a standard deviation of 0.5.Finally,based on the estimation results,additional work is proposed to improve the accuracy of the results.     

利用P波参数阈值实时估算地震预警潜在破坏区范围

由于传统的潜在破坏区范围估算方法只能在已获取到震中位置和地震事件结束后才能产出,且往往需要数分钟的耗时,其实时性已无法满足地震预警要求。因此,为了快速产出潜在破坏区范围估算结果并将其用于预警,本文采用了一种结合现地预警技术和区域预警技术、基于预警参数（位移幅值P_d和特征周期τ_c）阈值的实时潜在破坏区范围估算方法。首先利用国内地震事件（4.0≤M_S≤8.0）的记录数据和日本强震动观测事件（6.5≤M_J≤8.0）的数据拟合出特定的适应于我国的参数关系式,包括τ_c与震级M的相关性、P_d与峰值速度PGV的相关性以及P_d与τ_c和震源距R的相关性;其次,根据最小震级（M_S6.0）和仪器烈度（Ⅶ度）定义相应的参数阈值（P_d＝0.1 cm和τ_c＝1.1 s）;最后,利用已有的3次破坏性地震事件数据开展线下模拟,对该方法的适应性和时效性进行了验证。结果表明,对于2013年M_S7.0四川芦山和2014年M_S6.5云南鲁甸两次中强地震,震后约10 s即可获取到比较稳定的潜在破坏区范围估计结果;而对于2008年M_S8.0汶川特大地震,在其记录台站分布密度不高的情况下,震后40 s左右的估算结果始呈稳定状态。      

地震预警的十个问题

地震预警是国内外应用地震学的热点,也是近期公众关心的热门话题.本文就地震预警的一些基本问题、概念、关键技术及其在防震减灾方面的作用等问题做了简要概述,指出了地震预警存在的问题,以及需要研究的方向.首次提出了地震预警系统的确认和解除及地震预警社会容忍度的概念.同时强调地震预警是复杂的社会工程,需要全社会的共同参与.     

地震预警立法问题的探讨

地震预警作为一种防震减灾手段,目前受到我国政府和公众的极大关注。为了实现地震预警的社会效能,必须将其纳入法制化管理。本文首先论述了地震预警立法的必要性和可行性,然后就立法思路展开分析,最后对地震预警的主要立法内容进行了较为详细的阐述。     

地震预警现地PGV连续预测的最小二乘支持向量机模型

为提升现地仪器地震烈度预测的准确性与连续性,研究面向地震预警的PGV连续预测模型.以中国仪器地震烈度标准的计算参数：0.1~10 Hz带通滤波三分向矢量合成速度峰值PGV为预测目标,利用日本K-net与KiK-net台网P波触发后1~10 s强震数据,基于人工智能中的机器学习方法-最小二乘支持向量机,选取7种特征参数作为输入构建最小二乘支持向量机PGV预测模型LSSVM-PGV.结果表明,本文建立的LSSVM-PGV模型在训练数据集与测试数据集上的预测误差标准差变化趋于一致,具备泛化性能;P波触发后3 s预测PGV与实测PGV即可整体符合1：1关系,随着时间窗的增长,PGV预测的误差标准差显著减小、并在P波触发后6 s趋向收敛,具备准确连续预测能力;对比同为P波触发后3 s的常用Pd-PGV模型,LSSVM-PGV模型的PGV预测误差标准差明显减小,"小值高估"与"大值低估"现象明显改善,预测准确性得到提升.熊本地震序列的震例分析表明,对于6.5级以下地震,LSSVM-PGV模型最多在P波触发后3 s即可预测出与实测PGV整体符合1：1关系的PGV;对于7.3级主震,由于其破裂过程的复杂性,P波触发后3 s的预测结果出现一定程度的低估,但随着时间窗增长至6 s时,预测PGV与实测PGV符合1：1关系、并直到10 s整体趋势保持一致.本文构建的LSSVM-PGV模型可用于现地地震预警仪器地震烈度的预测.     

地震预报与地震预警

在回顾了地震预报历史沿革的基础上,认为虽然地震预报的难度比较大,但成功地预报地震不是不可能的.地震预警系统已被实践证明是一套有效的避震措施,将在未来的防灾减灾工作中发挥巨大作用,但地震预警并不能代替地震预报.     

地震预警信息可靠度研究

提出了一种地震预警信息可靠度检验方法. 针对地震预警系统对信息的高度时效性及准确性要求, 并结合其应用特点, 从地震动记录信噪比、 特征参数相容性、 特征参数协调性及地震预警定位结果可靠性等4个方面对地震预警信息的综合可靠度进行探讨, 并分别提出了相应的可靠度定量计算方法. 利用日本KiK-net台网记录的444个地震事件共4737条三分向加速度记录对上述4个指标参数及综合可靠度指标参数的验证结果表明, 采用本方法有助于提高地震预警信息发布的准确性和可靠性, 减少“漏报”及“误报”事件的发生.     

地震预警震级确定方法研究

地震预警技术是减轻地震灾害损失的有效手段之一．地震预警系统中,地震震级计算是最重要也是最困难的部分之一．利用日本KiK-net台网和四川汶川余震共142次地震事件的记录,分别采用tau;c和Pd方法统计得到了地震预警震级的计算公式,震级计算的方差分别为0.62和0.56个震级单位．为消除震级计算过程中出现的震级饱和现象,作者拓展了Pd方法,提出了一套对位移幅值连续追踪测定的算法．当时间窗长度为10 s时,采用该方法的震级计算方差仅为0.37个震级单位,充分满足地震预警系统的需求．同时,该方法也实现了信息的连续过渡,提高了对现有信息的利用率．最后,还对位移幅值Pd用于地震动峰值PGV的估计以及不同特征参数间的相容性等内容进行了讨论．      

地震预警定位方法研究

实时地震定位是地震预警系统中必须解决的关键问题之一.文中在借鉴已有实时地震定位方法的基础上并结合我国台网的实际情况,推导得到一套利用前三/四台P波、S波到时信息进行实时定位的算法.作者选取2000年至2008年问福建省地震监测台网记录到的68个3.0级以上地震对该算法进行验证.研究结果表明,采用文中方法的定位结果具有一...     

Deep learning for P-wave arrival picking in earthquake early warning

Fast and accurate P-wave arrival picking significantly affects the performance of earthquake early warning(EEW)systems.Automated P-wave picking algorithms used in EEW have encountered problems of falsely picking up noise,missing P-waves and inaccurate P-wave arrival estimation.To address these issues,an automatic algorithm based on the convolution neural network(DPick)was developed,and trained with a moderate number of data sets of 17,717 accelerograms.Compared to the widely used approach of the short-term average/long-term average of signal characteristic function(STA/LTA),DPick is 1.6 times less likely to detect noise as a P-wave,and 76 times less likely to miss P-waves.In terms of estimating P-wave arrival time,when the detection task is completed within 1 s,DPick′s detection occurrence is 7.4 times that of STA/LTA in the 0.05 s error band,and 1.6 times when the error band is 0.10 s.This verified that the proposed method has the potential for wide applications in EEW.     

An alternative approach for the Istanbul earthquake early warning system

Two recent catastrophic earthquakes that struck the Marmara Region on 17 August 1999 (M_w=7.4) and 12 November 1999 (M_w=7.2) caused major concern about future earthquake occurrences in Istanbul and the Marmara Region. As a result of the preparations for an expected earthquake may occur around Istanbul region, an earthquake early warning system has been established in 2002 with a simple and robust algorithm, based on the exceedance of specified thresholds of time domain amplitudes and the cumulative absolute velocity (CAV) levels (Erdik et al., 2003 [1]). In order to improve the capability of Istanbul earthquake early warning system (IEEWS) for giving early warning of a damaging earthquake in the Marmara Region, we explored an alternative approach with the use of a period parameter (τ_c) and a high-pass filtered vertical displacement amplitude parameter (Pd) from the initial 3 s of the P waveforms as proposed by Kanamori (2005) [2] and Wu and Kanamori (2005) 3 and 4. The empirical relationships both between τ_c and moment magnitude (M_w), and between Pd and peak ground velocity (PGV) for the Marmara Region are presented. These relationships can be used to detect a damaging earthquake within seconds after the arrival of P waves, and can provide on-site warning in the Marmara Region.     

Towards earthquake early warning for the Rion-Antirion bridge,Greece

Patras is the third largest city in Greece and an ideal candidate for earthquake early warning (EEW) applications due to its high seismic hazard, its existing research infrastructure and the presence of critical structures such as the Rion-Antirion bridge. Patras is located a few hundred kilometres from the Hellenic Arc, where very strong and potentially damaging earthquakes occur. This distance is large enough to allow a few tens of seconds of warning time prior to significant shaking, provided earthquakes are timely detected by a dense seismic network. Within the framework of the EC-funded project REAKT, the Virtual Seismologist (VS) EEW software was installed at Patras Seismological Laboratory. Its initial performance evaluation is presented here. In general VS provides magnitudes similar to the official, manually revised ones. Given the current station density and network telemetry, the average time that VS needs to deliver the first magnitude estimate is rather large, of the order of tens of seconds and not yet satisfactory for routine operational use of EEW. Even so, the system is able to provide up to 10 s of warning time prior to S-wave arrivals for events occurring on the Hellenic Arc. Our results indicate that the seismic networks in Greece need enhancements for regional EEW, either by adding stations or by upgrading the hardware to reduce delays. The application of an EEW system in the area is promising and, once operational, capable of mitigating earthquake risk.     

A new prototype system for earthquake early warning in Taiwan

A new prototype earthquake early warning (EEW) system is being developed and tested using a real-time seismographic network currently in operation in Taiwan. This system is based on the Earthworm environment which carries out integrated analysis of real-time broadband, strong-motion and short-period signals. The peak amplitude of displacement in the three seconds after the P arrival, dubbed P_d, is used for the magnitude determination. Incoming signals are processed in real time. When a large earthquake occurs, P-wave arrival times and P_d will be estimated for location and magnitude determinations for EEW purpose. In a test of 54 felt earthquakes, this system can report earthquake information in 18.8±4.1 s after the earthquake occurrence with an average difference in epicenter locations of 6.3±5.7 km, and an average difference in depths of 7.9±6.6 km from catalogues. The magnitudes approach a 1:1 relationship to the reported magnitudes with a standard deviation of 0.51. Therefore, this system can provide early warning before the arrival of S-wave for metropolitan areas located 70 km away from the epicenter. This new system is still under development and being improved, with the hope of replacing the current operational EEW system in the future.