scholarly journals Real-Time Characterization of Finite Rupture and Its Implication for Earthquake Early Warning: Application of FinDer to Existing and Planned Stations in Southwest China

2021 ◽  
Vol 9 ◽  
Author(s):  
Jiawei Li ◽  
Maren Böse ◽  
Yu Feng ◽  
Chen Yang
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Line Source ◽  
Average Distance ◽  
Strong Motion ◽  
Earthquake Early Warning ◽  
Time Data ◽  
Yunnan Region ◽  
Motion Time ◽  
Source Models

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.

Estimating Rupture Dimensions of Three Major Earthquakes in Sichuan, China, for Early Warning and Rapid Loss Estimates

2020 ◽  
Vol 110 (2) ◽  
pp. 920-936 ◽  
Author(s):  
Jiawei Li ◽  
Maren Böse ◽  
Max Wyss ◽  
David J. Wald ◽  
Alexandra Hutchison ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Line Source ◽  
Source Parameters ◽  
Strong Motion ◽  
Preventive Action ◽  
Fault Rupture ◽  
S Wave ◽  
Finite Fault ◽  
Source Models

ABSTRACT Large earthquakes, such as Wenchuan in 2008, Mw 7.9, Sichuan, China, provide an opportunity for earthquake early warning (EEW), as many heavily shaken areas are far (∼50  km) from the epicenter and warning times could be sufficient (≥5  s) to take preventive action. On the other hand, earthquakes with magnitudes larger than ∼M 6.5 are challenging for EEW because source dimensions need to be defined to adequately estimate shaking. Finite-fault rupture detector (FinDer) is an approach to identify fault rupture extents from real-time seismic records. In this study, we playback local and regional onscale strong-motion waveforms of the 2008 Mw 7.9 Wenchuan, 2013 Mw 6.6 Lushan, and 2017 Mw 6.5 Jiuzhaigou earthquakes to study the performance of FinDer for the current layout of the China Strong Motion Network. Overall, the FinDer line-source models agree well with the observed spatial distribution of aftershocks and models determined from waveform inversion. However, because FinDer models are constructed to characterize seismic ground motions (as needed for EEW) instead of source parameters, the rupture length can be overestimated for events radiating high levels of high-frequency motions. If the strong-motion data used had been available in real time, 50%–80% of sites experiencing intensity modified Mercalli intensity IV–VII (light to very strong) and 30% experiencing VIII–IX (severe to violent) could have been issued a warning with 10 and 5 s, respectively, before the arrival of the S wave. We also show that loss estimates based on the FinDer line source are more accurate compared to point-source models. For the Wenchuan earthquake, for example, they predict a four to six times larger number of fatalities and injured, which is consistent with official reports. These losses could be provided 1/2∼3  hr faster than if they were based on more complex inversion rupture models.

Too-Late Warnings by Estimating Mw: Earthquake Early Warning in the Near-Fault Region

2020 ◽  
Vol 110 (3) ◽  
pp. 1276-1288
Author(s):  
Mitsuyuki Hoshiba
Keyword(s):  
Real Time ◽  
Ground Motion ◽  
Early Warning ◽  
Strong Motion ◽  
Earthquake Early Warning ◽  
Motion Generation ◽  
Near Fault ◽  
Time Gap ◽  
Fault Region ◽  
Strong Ground

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.

scholarly journals One minute after: Strong-motion map, effective epicenter, and effective magnitude

1997 ◽  
Vol 87 (5) ◽  
pp. 1209-1219 ◽  
Author(s):  
Ta-liang Teng ◽  
Ludan Wu ◽  
Tzay-Chyn Shin ◽  
Yi-Ben Tsai ◽  
William H. K. Lee
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Initial Point ◽  
Strong Motion ◽  
Large Earthquake ◽  
Seismic Monitoring ◽  
Earthquake Early Warning ◽  
Force Balance ◽  
Total Energy Release ◽  
Intensity Map

Abstract This article reports the recent progress on real-time seismic monitoring in Taiwan, particularly the real-time strong-motion monitoring by the Taiwan Central Weather Bureau's telemetered seismic network (CWBSN), which is presently aiming at rapid reporting immediately after a large earthquake occurrence. If rapid reporting can be achieved before the arrival of the strong shaking, earthquake early warning will become possible. CWBSN has achieved the generation of the intensity map, epicenter, and magnitude within 1 min of the occurrence of a large earthquake. Both rapid reporting and early warning are principally applied to large (M ≫ 5) events; the requirement of on-scale waveform recording prompted CWBSN in 1995 to integrate strong-motion sensors (e.g., force-balance accelerometers) into its telemetered seismic monitoring system. Time-domain recursive processing is applied to the multi-channel incoming seismic signals by a group of networked personal computers to generate the intensity map. From the isoseismal contours, an effective epicenter is immediately identified that resides in the middle of the largest (usually the 100-gal) contour curve of the intensity map. An effective magnitude is also defined that can be derived immediately from the surface area covered by the largest (usually the 100-gal) contour curve. For a large event with a finite rupture surface, the epicenter and magnitude so derived are more adequate estimates of the source location and of the strength of destruction. The effective epicenter gives the center of the damage area; it stands in contrast with the conventional epicenter location, which only gives the initial point of rupture nucleation. The effective magnitude reflects more closely the earthquake damage potential, instead of the classical magnitude definition that emphasizes the total energy release. The CWBSN has achieved in obtaining the above crucial source information well within 1 min. This time can further be reduced to better than 30 sec, as illustrated by the example in this article, showing that earthquake early warning is indeed an achievable goal. The rapid reporting and early warning information is electronically transmitted to users to allow rapid response actions, with or without further human intervention.

Could a Decentralized Onsite Earthquake Early Warning System Help in Mitigating Seismic Risk in Northeastern Italy? The Case of the 1976 Ms 6.5 Friuli Earthquake

2020 ◽  
Vol 91 (6) ◽  
pp. 3323-3333
Author(s):  
Stefano Parolai ◽  
Luca Moratto ◽  
Michele Bertoni ◽  
Chiara Scaini ◽  
Alessandro Rebez
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Seismic Risk ◽  
Warning System ◽  
Strong Motion ◽  
Early Warning Systems ◽  
Earthquake Early Warning ◽  
Industrial Facilities ◽  
Earthquake Early Warning System ◽  
The Impact

Abstract In May 1976, a devastating earthquake of magnitude Ms 6.5 occurred in Friuli, Italy, resulting in 976 deaths, 2000 injured, and 60,000 homeless. It is notable that, at the time of the earthquake, only one station was installed in the affected region. The resulting lack of information, combined with a dearth of mitigation planning for responding to such events, lead to a clear picture of the impact of the disaster being available only after a few days. This region is now covered by nearly 100 seismological and strong-motion stations operating in real time. Furthermore, 30 average-cost strong-motion stations have been recently added, with the goals of improving the density of real-time ground-motion observations and measuring the level of shaking recorded at selected buildings. The final goal is to allow rapid impact estimations to be made to improve the response of civil protection authorities. Today, considering the higher density seismological network, new efforts in terms of the implementation and testing of earthquake early warning systems as a possible tool for mitigating seismic risk are certainly worthwhile. In this article, we show the results obtained by analyzing in playback and using an algorithm for decentralized onsite earthquake early warning, broadband synthetic strong-motion data calculated at 18 of the stations installed in the region, while considering the magnitude and location of the 1976 Friuli earthquake. The analysis shows that the anisotropy of the lead times is related not only to the finite nature of the source but also to the slip distribution. A reduction of 10% of injured persons appears to be possible if appropriate mitigating actions are employed, such as the development of efficient automatic procedures that improve the safety of strategic industrial facilities.

scholarly journals Trans-national earthquake early warning (EEW) in north-eastern Italy, Slovenia and Austria: first experience with PRESTo at the CE<sup>3</sup>RN network

2015 ◽  
Vol 40 ◽  
pp. 51-61 ◽  
Author(s):  
M. Picozzi ◽  
L. Elia ◽  
D. Pesaresi ◽  
A. Zollo ◽  
M. Mucciarelli ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Data Exchange ◽  
Warning System ◽  
Strong Motion ◽  
Earthquake Early Warning ◽  
Research Network ◽  
Earthquake Early Warning System ◽  
Management Platform

Abstract. The region of central and eastern Europe is an area characterised by a relatively high seismic risk. Since 2001, to monitor the seismicity of this area, the OGS (Istituto Nazionale di Oceanografia e di Geofisica Sperimentale) in Italy, the Agencija Republike Slovenije za Okolje (ARSO) in Slovenia, the Zentralanstalt für Meteorologie und Geodynamik (ZAMG) in Austria, and the Università di Trieste (UniTS) have cooperated in real-time seismological data exchange. In 2014 OGS, ARSO, ZAMG and UniTS created a cooperative network named the Central and Eastern European Earthquake Research Network (CE3RN), and teamed up with the University of Naples Federico II, Italy, to implement an earthquake early warning system based on the existing networks. Since May 2014, the earthquake early warning system (EEWS) given by the integration of the PRESTo (PRobability and Evolutionary early warning SysTem) alert management platform and the CE3RN accelerometric stations has been under real-time testing in order to assess the system's performance. This work presents a preliminary analysis of the EEWS performance carried out by playing back real strong motion recordings for the 1976 Friuli earthquake (MW= 6.5). Then, the results of the first 6 months of real-time testing of the EEWS are presented and discussed.

scholarly journals Status of Earthquake Early Warning in Switzerland

2021 ◽  
Vol 9 ◽  
Author(s):  
Frédérick Massin ◽  
John Clinton ◽  
Maren Böse
Keyword(s):  
Real Time ◽  
Open Source Software ◽  
Early Warning ◽  
Seismic Network ◽  
Earthquake Early Warning ◽  
Fault Rupture ◽  
Time Data ◽  
Origin Time ◽  
P Waves ◽  
Finite Fault

The Swiss Seismological Service (SED) at ETH has been developing methods and open-source software for Earthquake Early Warning (EEW) for more than a decade and has been using SeisComP for earthquake monitoring since 2012. The SED has built a comprehensive set of SeisComP modules that can provide EEW solutions in a quick and transparent manner by any seismic service operating SeisComP. To date, implementations of the Virtual Seismologist (VS) and Finite-Fault Rupture Detector (FinDer) EEW algorithms are available. VS provides rapid EEW magnitudes building on existing SeisComP detection and location modules for point-source origins. FinDer matches growing patterns of observed high-frequency seismic acceleration amplitudes with modeled templates to identify rupture extent, and hence can infer on-going finite-fault rupture in real-time. Together these methods can provide EEW for all event dimensions from moderate to great, if a high quality, EEW-ready, seismic network is available. In this paper, we benchmark the performance of this SeisComP-based EEW system using recent seismicity in Switzerland. Both algorithms are observed to be similarly fast and can often produce first EEW alerts within 4–6 s of origin time. In real time performance, the median delay for the first VS alert is 8.7 s after origin time (56 earthquakes since 2014, from M2.7 to M4.6), and 7 s for FinDer (10 earthquakes since 2017, from M2.7 to M4.3). The median value for the travel time of the P waves from event origin to the fourth station accounts for 3.5 s of delay; with an additional 1.4 s for real-time data sample delays. We demonstrate that operating two independent algorithms provides redundancy and tolerance to failures of a single algorithm. This is documented with the case of a moderate M3.9 event that occured seconds after a quarry blast, where picks from both events produced a 4 s delay in the pick-based VS, while FinDer performed as expected. Operating on the Swiss Seismic Network, that is being continuously optimised for EEW, the SED-ETHZ SeisComP EEW system is achieving performance that is comparable to operational EEW systems around the world.

Early Warning of Power Plant Equipment Based on Massive Real-Time Data Mining Technology

2014 ◽  
Vol 599-601 ◽  
pp. 1487-1490 ◽  
Author(s):  
Li Kun Zheng ◽  
Kun Feng ◽  
Xiao Qing Xiao ◽  
Wei Qiao Song
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Early Warning ◽  
Time Data ◽  
Mining Technology ◽  
Equipment Safety ◽  
State Evaluation ◽  
Power Plant Equipment ◽  
Real Time Data

This paper mainly discusses the application of the mass real-time data mining technology in equipment safety state evaluation in the power plant and the realization of the equipment comprehensive quantitative assessment and early warning of potential failure by mining analysis and modeling massive amounts of real-time data the power equipment. In addition to the foundational technology introduced in this paper, the technology is also verified by the application case in the power supply side remote diagnosis center of Guangdong electric institute.

Sign in / Sign up

Export Citation Format

Share Document