Magnitude Estimation and Onsite Earthquake Early Warning using Cumulative Absolute Velocity in Taiwan

Author(s):  
Hao-Yun Huang ◽  
Yih-Min Wu

<p>Real-time magnitude determination is one of the critical issues for earthquake early warning (EEW). Magnitude determination may have saturation situation using initial seismic signals after an earthquake occurrence. Previous studies utilized eventual cumulative absolute velocity (eCAV) to determine magnitude up to 9.0 without any saturation. However, to determine eCAV will be too late for EEW application. In order to shorten time to obtain eCAV, 4,754 strong motion records from 64 events with M<sub>L </sub>large than 5.5 in Taiwan are used to establish the relationship between eCAV and initial shaking parameters (initial CAV, initial cumulative absolute displacement, initial cumulative absolute integral displacement,  P<sub>d</sub> and  τ<sub>c</sub>) from 1 s to 20 s after P arrival. Our preliminary results show that eCAV can be estimated using initial shaking parameters. Logarithm linear correlation coefficients vary from 0.78 to 0.97 with standard deviations from 0.27 to 0.10 for time windows from 1 s to 20 s after P arrival. Eventually, we can timely estimate eCAV for magnitude determination as well as or on-site EEW purpose.</p>

Author(s):  
Mark Netanel ◽  
Andreas Samuel Eisermann ◽  
Alon Ziv

ABSTRACT Regional source-based earthquake early warning systems perform three consecutive tasks: (1) detection and epicenter location, (2) magnitude determination, and (3) ground-motion prediction. The correctness of the magnitude determination is contingent on that of the epicenter location, and the credibility of the ground-motion prediction depends on those of the epicenter location and the magnitude determination. Thus, robust epicenter location scheme is key for regional earthquake early warning systems. Available source-based systems yield acceptably accurate locations when the earthquakes occur inside the real-time seismic network, but they return erroneous results otherwise. In this study, a real-time algorithm that is intended as a supplement to an existing regional earthquake early warning systems is introduced with the sole objective of ameliorating its off-network location capacity. The new algorithm combines measurements from three or more network stations that are analyzed jointly using an array methodology to give the P-wave slowness vector and S-phase arrival time. Prior to the S-phase picking, the nonarrival of the S phase is used for determining a minimum epicentral distance. This estimate is updated repeatedly with elapsed time until the S phase is picked. Thus, the system timeliness is not compromised by waiting for the S-phase arrival. After the S wave is picked, an epicentral location can be determined using a single array by intersecting the back-azimuth beam with the S-minus-P annulus. When several arrays are assembled, the back azimuth and P and S picks from all arrays are combined to constrain the epicenter. The performance of the array processing for back azimuth and S-wave picking is assessed using a large number of accelerograms, recorded by nine strong motion sensors of the KiK-net seismic network in Japan. The nine stations are treated as three distinct seismic arrays, comprising three stations each. Good agreement is found between array-based and catalog-reported parameters. Finally, the advantage of the new array methodology with respect to alternative schemes for back azimuth and distance is demonstrated.


2012 ◽  
Vol 28 (3) ◽  
pp. 931-941 ◽  
Author(s):  
Kenneth W. Campbell ◽  
Yousef Bozorgnia

Arias intensity (AI) and cumulative absolute velocity (CAV) have been proposed as instrumental intensity measures that can incorporate the cumulative effects of ground motion duration and intensity on the response of structural and geotechnical systems. In this study, we have developed a ground motion prediction equation (GMPE) for the horizontal component of AI in order to compare its predictability to a similar GMPE for CAV. Both GMPEs were developed using the same strong motion database and functional form in order to eliminate any bias these factors might cause in the comparison. This comparison shows that AI exhibits significantly greater amplitude scaling and aleatory uncertainty than CAV. The smaller standard deviation and less sensitivity to amplitude suggests that CAV is more predictable than AI and should be considered as an alternative to AI in engineering and geotechnical applications where the latter intensity measure is traditionally used.


2020 ◽  
Vol 110 (3) ◽  
pp. 1276-1288
Author(s):  
Mitsuyuki Hoshiba

ABSTRACT Earthquake early warning (EEW) systems aim to provide advance warnings of impending strong ground shaking. Many EEW systems are based on a strategy in which precise and rapid estimates of source parameters, such as hypocentral location and moment magnitude (Mw), are used in a ground-motion prediction equation (GMPE) to predict the strength of ground motion. For large earthquakes with long rupture duration, the process is repeated, and the prediction is updated in accordance with the growth of Mw during the ongoing rupture. However, in some regions near the causative fault this approach leads to late warnings, because strong ground motions often occur during earthquake ruptures before Mw can be confirmed. Mw increases monotonically with elapsed time and reaches its maximum at the end of rupture, and ground motion predicted by a GMPE similarly reaches its maximum at the end of rupture, but actual generation of strong motion is earlier than the end of rupture. A time gap between maximum Mw and strong-motion generation is the first factor contributing to late warnings. Because this time gap exists at any point of time during the rupture, a late warning is inherently caused even when the growth of Mw can be monitored in real time. In the near-fault region, a weak subevent can be the main contributor to strong ground motion at a site if the distance from the subevent to the site is small. A contribution from a weaker but nearby subevent early in the rupture is the second factor contributing to late warnings. Thus, an EEW strategy based on rapid estimation of Mw is not suitable for near-fault regions where strong shaking is usually recorded. Real-time monitoring of ground motion provides direct information for real-time prediction for these near-fault locations.


2014 ◽  
Vol 539 ◽  
pp. 741-746
Author(s):  
Jie Ning Xia ◽  
Zhi Gao Chen ◽  
Jun Huang ◽  
Jiang Yang ◽  
Jian Yang ◽  
...  

Characteristics of cumulative absolute velocity parameter (CAV) of Lushan earthquake is discussed and presented in this paper. Based on a brief analysis of the background information of the Lushan earthquake, the value of CAV which is calculated from the recorded data of the Lushan earthquake is compared with the commonly used value peak ground acceleration (PGA). Accordingly, the relationship between the CAV and the PGA is studied, and 3 CAV/PGA ratio charts in 3 different sub-directions are obtained. Then the linear fitting operation and the polynomial fitting operation are performed to analyze the potential discipline and characteristics thereof. The applicability of utilizing the CAV parameter in earthquake observation systems is further studied in this paper, and the CAV parameter is cooperated with the currently used value PGA to provide the work of earthquake observation and emergency response with corresponding theoretical basis.


2021 ◽  
Vol 9 ◽  
Author(s):  
Jiawei Li ◽  
Maren Böse ◽  
Yu Feng ◽  
Chen Yang

Earthquake early warning (EEW) not only improves resilience against the risk of earthquake disasters, but also provides new insights into seismological processes. The Finite-Fault Rupture Detector (FinDer) is an efficient algorithm to retrieve line-source models of an ongoing earthquake from seismic real-time data. In this study, we test the performance of FinDer in the Sichuan-Yunnan region (98.5oE–106.0oE, 22.0oN–34.0oN) of China for two datasets: the first consists of seismic broadband and strong-motion records of 58 earthquakes with 5.0 ≤ MS ≤ 8.0; the second comprises additional waveform simulations at sites where new stations will be deployed in the near future. We utilize observed waveforms to optimize the simulation approach to generate ground-motion time series. For both datasets the resulting FinDer line-source models agree well with the reported epicenters, focal mechanisms, and finite-source models, while they are computed faster compared to what traditional methods can achieve. Based on these outputs, we determine a theoretical relation that can predict for which magnitudes and station densities FinDer is expected to trigger, assuming that at least three neighboring stations must have recorded accelerations of 4.6 cm/s2 or more. We find that FinDer likely triggers and sends out a report, if the average distance between the epicenter and the three closest stations, Depi, is equal or smaller than log10 (Ma + b) + c, where a = 1.91, b = 5.93, and c = 2.34 for M = MW ≥ 4.8, and c = 2.49 for M = MS ≥ 5.0, respectively. If the data used in this study had been available in real-time, 40–70% of sites experiencing seismic intensities of V-VIII (on both Chinese and MMI scales) and 20% experiencing IX-X could have been issued a warning 5–10 s before the S-wave arrives. Our offline tests provide a useful reference for the planned installation of FinDer in the nationwide EEW system of Chinese mainland.


2021 ◽  
Vol 9 ◽  
Author(s):  
Yadab P. Dhakal ◽  
Takashi Kunugi

We analyzed strong-motion records at the ground and borehole in and around the Kanto Basin and the seafloor in the Japan Trench area from three nearby offshore earthquakes of similar magnitudes (Mw 5.8–5.9). The seafloor strong-motion records were obtained from S-net, which was established to enhance tsunami and earthquake early warnings after the 2011 great Tohoku-oki earthquake disaster. The borehole records were obtained from MeSO-net, a dense network of seismometers installed at a depth of 20 m in the Tokyo metropolitan area. The ground records were obtained from the K-NET and KiK-net networks, established after the 1995 great Hanshin-Awaji earthquake disaster. The MeSO-net and S-net stations record the shakings continuously, while the K-NET and KiK-net records are based on triggering thresholds. It is crucial to evaluate the properties of strong motions recorded by the S-net for earthquake early warning (EEW). This paper compared the peak ground accelerations (PGAs) and peak ground velocities (PGVs) between the S-net and K-NET/KiK-net stations. Because the MeSO-net records were from the borehole, we compared the PGAs and significant durations of the low-frequency motions (0.1–0.5 Hz) between the S-net and MeSO-net stations from identical record lengths. We found that the horizontal PGAs and PGVs at the S-net sites were similar to or larger than the K-NET/KiK-net sites for the S wave. In contrast, the vertical PGAs and PGVs at the S-net sites were similar to or smaller than those at the K-NET/KiK-net sites for the S wave. Particularly, the PGAs and PGVs for the P-wave parts on the vertical-component records of S-net were, on average, much smaller than those of K-NET/KiK-net records. The difference was more evident in the PGAs. The average ratios of S-wave horizontal to vertical PGAs were about 2.5 and 5 for the land and S-net sites, respectively. The low-frequency PGAs at the S-net sites were similar to or larger than those of the MeSO-net borehole records. The significant durations between the two-networks low-frequency records were generally comparable. Quantification of the results from a larger dataset may contribute to ground-motion prediction for EEW and the design of the offshore facilities.


2020 ◽  
Vol 91 (6) ◽  
pp. 3236-3255 ◽  
Author(s):  
Ittai Kurzon ◽  
Ran N. Nof ◽  
Michael Laporte ◽  
Hallel Lutzky ◽  
Andrey Polozov ◽  
...  

Abstract Following the recommendations of an international committee (Allen et al., 2012), since October 2017, the Israeli Seismic Network has been undergoing significant upgrades, with 120 stations being added or upgraded throughout the country and the addition of two new datacenters. These enhancements are the backbone of the TRUAA project, assigned to the Geological Survey of Israel (GSI) by the Israeli Government, to provide earthquake early warning (EEW) capabilities for the state of Israel. The GSI contracted Nanometrics (NMX), supported by Motorola Solutions Israel, to deliver these upgrades through a turnkey project, including detailed design, equipment supply, and deployment of the network and two datacenters. The TRUAA network was designed and tailored by the GSI, in collaboration with the NMX project team, specifically to achieve efficient and robust EEW. Several significant features comprise the pillars of this network:Coverage: Station distribution has high density (5–10 km spacing) along the two main fault systems—the Dead Sea Fault and the Carmel Fault System;Instrumentation: High-quality strong-motion accelerometers and broadband seismometers with modern three-channel and six-channel dataloggers sampling at 200 samples per second;Low latency acquisition: Data are encapsulated in small packets (<1  s), with primary routing via high-speed, high-capacity telemetry links (<1  s latency);Robustness: High level of redundancy throughout the system design:Dual active-active redundant acquisition routes from each station, each utilizing multicast streaming over an IP security Virtual Private Network tunnel, via independent high-bandwidth telemetry systemsTwo active-active independent geographically separate datacentersDual active-active redundant independent automatic seismic processing tool chains within each datacenter, implemented in a high availability protected virtual environment. At this time, both datacenters and over 100 stations are operational. The system is currently being commissioned, with initial early warning operation targeted for early 2021.


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