Status of Earthquake Early Warning in Switzerland

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.

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Real-Time Detection of Rupture Development: Earthquake Early Warning Using P Waves From Growing Ruptures

Geophysical Research Letters ◽

10.1002/2017gl076118 ◽

2018 ◽

Vol 45 (1) ◽

pp. 156-165 ◽

Cited By ~ 8

Author(s):

Yuki Kodera

Keyword(s):

Real Time ◽

Early Warning ◽

Earthquake Early Warning ◽

P Waves ◽

Real Time Detection

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Earthquake Early Warning Technology Progress in Taiwan

Journal of Disaster Research ◽

10.20965/jdr.2009.p0202 ◽

2009 ◽

Vol 4 (4) ◽

pp. 530-538 ◽

Cited By ~ 5

Author(s):

Kuo-Liang Wen ◽

◽

Tzay-Chyn Shin ◽

Yih-Min Wu ◽

Nai-Chi Hsiao ◽

...

Keyword(s):

Real Time ◽

Early Warning ◽

Monitoring Network ◽

Earthquake Early Warning ◽

P Waves ◽

Strong Base ◽

Warning Messages ◽

Online Experimentation ◽

Near Future ◽

Remarkable Progress

The dense real-time earthquake monitoring network established in Taiwan is a strong base for the development of the earthquake early warning (EEW) system. In remarkable progress over the last decades, real-time earthquake warning messages are sent within 20 sec after an event using the regional EEW system with a virtual subnetwork approach. An onsite EEW approach using the first 3 sec of P waves has been developed and under online experimentation. Integrating regional and onsite systems may enable EEW messages to be issued within 10 sec after an event occurred in the near future. This study mainly discusses the methodology for determining the magnitude and ground motion of an event.

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

Frontiers in Earth Science ◽

10.3389/feart.2021.699560 ◽

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.

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Earthquake Early Warning System in Israel—Towards an Operational Stage

Frontiers in Earth Science ◽

10.3389/feart.2021.684421 ◽

2021 ◽

Vol 9 ◽

Author(s):

Ran N. Nof ◽

Itzhak Lior ◽

Ittai Kurzon

Keyword(s):

Ground Motion ◽

Early Warning ◽

Seismic Network ◽

Earthquake Early Warning ◽

Performance Estimation ◽

Motion Prediction ◽

Ground Motion Prediction Equations ◽

Prediction Equations ◽

Ground Motion Prediction ◽

Origin Time

The Geological Survey of Israel has upgraded and expanded the national Israeli Seismic Network (ISN), with more than 110 stations country-wide, as part of the implementation of a governmental decision to build a national Earthquake Early Warning (EEW) system named TRUAA. This upgraded seismic network exhibits a high station density and fast telemetry. The stations are distributed mainly along the main fault systems, the Dead Sea Transform, and the Carmel-Zfira Fault, which may potentially produce Mw 7.5 earthquakes. The system has recently entered a limited operational phase, allowing for initial performance estimation. Real-time performance during eight months of operation (41 earthquakes) matches expectations. Alert delays (interval between origin-time and Earthquake Early Warning alert time) are reduced to as low as 3 s, and source parameter errorstatistics are within expected values found in previous works using historical data playbacks. An evolutionary alert policy is implemented based on a magnitude threshold of Mw 4.2 and peak ground accelerations exceeding 2 cm/s2. A comparison between different ground motion prediction equations (GMPE) is presented for earthquakes from Israel and California using median ground motion prediction equations values. This analysis shows that a theoretical GMPE produced the best agreement with observed ground motions, with less bias and lower uncertainties. The performance of this GMPE was found to improve when an earthquake specific stress drop is implemented.

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Toward Global Earthquake Early Warning with the MyShake Smartphone Seismic Network, Part 2: Understanding MyShake Performance around the World

Seismological Research Letters ◽

10.1785/0220190178 ◽

2020 ◽

Vol 91 (4) ◽

pp. 2218-2233

Author(s):

Qingkai Kong ◽

Robert Martin-Short ◽

Richard M. Allen

Keyword(s):

Early Warning ◽

Mobile Application ◽

Large Scale ◽

Detection Algorithm ◽

Seismic Network ◽

Earthquake Early Warning ◽

High Population ◽

Simulation Platform ◽

Origin Time ◽

The World

Abstract The MyShake project aims to build a global smartphone seismic network to facilitate large-scale earthquake early warning (EEW) and other applications by leveraging the power of crowdsourcing. The MyShake mobile application first detects earthquake shaking on a single phone. The earthquake is then confirmed on the MyShake servers using a “network detection” algorithm that is activated by multiple single-phone detections. In part two of this two-article series, we report the first-order performance of MyShake’s EEW capability in various selected locations around the world. Because of the present sparseness of the MyShake network in most parts of the world, we use our simulation platform to understand and evaluate the system’s performance in various tectonic settings. We assume that 0.1% of the population in each region has the MyShake mobile application installed on their smartphone and use historical earthquakes from the last 20 yr to simulate triggering scenarios with different network configurations in various regions. Then, we run the detection algorithm with these simulated triggers to understand the performance of the system. The system performs best in regions featuring high population densities and onshore, upper crustal earthquakes M<7.0. In these cases, alerts can be generated ∼4–6 s after the origin time, magnitude errors are within ∼0.5 magnitude units, and epicenters are typically within 10 km of true locations. When the events are offshore or in sparsely populated regions, the alerts are slower and the uncertainties in magnitude and location increase. Furthermore, even with 0.01% of the population as the MyShake users, in regions of high population density, the system still performs well for earthquakes larger than M 5.5. The details of the simulation platform and the network detection algorithm are available in part 1 of this two-article series.

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

Bulletin of the Seismological Society of America ◽

10.1785/0120190117 ◽

2020 ◽

Vol 110 (2) ◽

pp. 920-936 ◽

Cited By ~ 1

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.

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The Impact of 3D Finite-Fault Information on Ground-Motion Forecasting for Earthquake Early Warning

Bulletin of the Seismological Society of America ◽

10.1785/0120210162 ◽

2021 ◽

Author(s):

Jessica R. Murray ◽

Eric M. Thompson ◽

Annemarie S. Baltay ◽

Sarah E. Minson

Keyword(s):

Ground Motion ◽

Early Warning ◽

Line Source ◽

Earthquake Early Warning ◽

Source Characterization ◽

Origin Time ◽

Finite Fault ◽

Alert Threshold ◽

The Impact ◽

Fault Information

ABSTRACT We identify aspects of finite-source parameterization that strongly affect the accuracy of estimated ground motion for earthquake early warning (EEW). EEW systems aim to alert users to impending shaking before it reaches them. The U.S. West Coast EEW system, ShakeAlert, currently uses two algorithms based on seismic data to characterize the earthquake’s location, magnitude, and origin time, treating it as a point or line source. From this information, ShakeAlert calculates shaking intensity and alerts locations where shaking estimates exceed a threshold. Several geodetic EEW algorithms under development would provide 3D finite-fault information. We investigate conditions under which this information produces sufficiently better intensity estimates to potentially improve alerting. Using scenario crustal and subduction interface sources, we (1) identify the most influential source geometry parameters for an EEW algorithm’s shaking forecast, and (2) assess the intensity alert thresholds and magnitude ranges for which more detailed source characterization affects alert accuracy. We find that alert regions determined using 3D-source representations of correct magnitude and faulting mechanism are generally more accurate than those obtained using line sources. If a line-source representation is used and magnitude is calculated from the estimated length, then incorrect length estimates significantly degrade alert region accuracy. In detail, the value of 3D-source characterization depends on the user’s chosen alert threshold, tectonic regime, and faulting style. For the suite of source models we tested, the error in shaking intensity introduced by incorrect geometry could reach levels comparable to the intrinsic uncertainty in ground-motion calculations (e.g., 0.5–1.3 modified Mercalli intensity [MMI] units for MMI 4.5) but, especially for crustal sources, was often less. For subduction interface sources, 3D representations substantially improved alert area accuracy compared to line sources, and incorrect geometry parameters were more likely to cause error in calculated shaking intensity that exceeded uncertainties.

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

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.599-601.1487 ◽

2014 ◽

Vol 599-601 ◽

pp. 1487-1490 ◽

Cited By ~ 1

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.

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