Ground Motion Estimation Using Front Site Wave Form Data Based on RVM for Earthquake Early Warning

The use of the earthquake early warning system (EEWS), one of the most useful emergency response tools, requires that the accuracy of real-time ground motion prediction (GMP) be enhanced. This requires that waveform information at observation points along earthquake wave propagation paths (hereafter, front-site waveform information) be used effectively. To enhance the combined reliability of different systems, such as on-site and local/regional warning, we present a GMP method using front-site waveform information by applying a relevant vector machine (RVM). We present methodology and application examples for a case study estimating peak ground acceleration (PGA) and peak ground velocity (PGV) for earthquakes in the Miyagi-Ken Oki subduction zone. With no knowledge of source information, front site waveforms have been used to predict ground motion at target sites. Five input variables – earthquake PGA, PGD, pulse rise time, average period and theVpmax/Amaxratio – have been used for the first 4 to 6 seconds of P-waves in training a regression model. We found that RVM is a useful tool for the prediction of peak ground motion.

Download Full-text

Robust, an Earthquake Early Warning System in the Lower Rhine Embayment, Germany

10.5194/egusphere-egu21-7997 ◽

2021 ◽

Author(s):

Bita Najdahmadi ◽

Marco Pilz ◽

Dino Bindi ◽

Hoby Njara Tendrisoa Razafindrakoto ◽

Adrien Oth ◽

...

Keyword(s):

Early Warning ◽

Early Warning System ◽

Warning System ◽

Earthquake Early Warning ◽

Optimization Approach ◽

Ground Acceleration ◽

Earthquake Early Warning System ◽

Scenario Earthquakes ◽

Lower Rhine Embayment ◽

Lower Rhine

<p>The Lower Rhine Embayment in western Germany is one of the most important areas of earthquake recurrence north of the Alps, facing a moderate level of seismic hazard in the European context but a significant level of risk due to a large number of important&#160;industrial infrastructures. In this context, the project ROBUST aims at designing a user-oriented hybrid earthquake early warning and rapid response system where regional seismic monitoring is combined with smart, on-site sensors, resulting in the implementation of decentralized early warning procedures.<br><br>One of the research areas of this project deals with finding an optimal regional seismic network arrangement. With the optimally compacted network, strong ground movements can be detected quickly and reliably. In this work simulated scenario earthquakes in the area are used with an optimization approach in order to densify the existing sparse network through the installation of additional decentralized measuring stations. Genetic algorithms are used to design efficient EEW networks, computing optimal station locations and trigger thresholds in recorded ground acceleration. By minimizing the cost function, a comparison of the best earthquake early warning system designs is performed and the potential usefulness of existing stations in the region is considered as&#160;will be presented in the meeting.</p>

Download Full-text

Optimizing Earthquake Early Warning Alert Distance Strategies Using the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, Earthquakes

Bulletin of the Seismological Society of America ◽

10.1785/0120200022 ◽

2020 ◽

Vol 110 (4) ◽

pp. 1872-1886 ◽

Cited By ~ 1

Author(s):

Jessie K. Saunders ◽

Brad T. Aagaard ◽

Annemarie S. Baltay ◽

Sarah E. Minson

Keyword(s):

Ground Motion ◽

Early Warning ◽

Ground Motions ◽

Protective Action ◽

Warning System ◽

Prediction Equation ◽

Earthquake Early Warning ◽

Source Characterization ◽

Earthquake Early Warning System ◽

Alert Distance

ABSTRACT The ShakeAlert earthquake early warning system aims to alert people who experience modified Mercalli intensity (MMI) IV+ shaking during an earthquake using source estimates (magnitude and location) to estimate median-expected peak ground motions with distance, then using these ground motions to determine median-expected MMI and thus the extent of MMI IV shaking. Because median ground motions are used, even if magnitude and location are correct, there will be people outside the alert region who experience MMI IV shaking but do not receive an alert (missed alerts). We use 91,000 “Did You Feel It?” survey responses to the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, earthquakes to determine which ground-motion to intensity conversion equation (GMICE) best fits median MMI with distance. We then explore how incorporating uncertainty from the ground-motion prediction equation and the GMICE in the alert distance calculation can produce more accurate MMI IV alert regions for a desired alerting strategy (e.g., aiming to alert 95% of people who experience MMI IV+ shaking), assuming accurate source characterization. Without incorporating ground-motion uncertainties, we find MMI IV alert regions using median-expected ground motions alert fewer than 20% of the population that experiences MMI IV+ shaking. In contrast, we find >94% of the people who experience MMI IV+ shaking can be included in the MMI IV alert region when two standard deviations of ground-motion uncertainty are included in the alert distance computation. The optimal alerting strategy depends on the false alert tolerance of the community due to the trade-off between minimizing missed and false alerts. This is especially the case for situations like the Mw 6.4 earthquake when alerting 95% of the 5 million people who experience MMI IV+ also results in alerting 14 million people who experience shaking below this level and do not need to take protective action.

Download Full-text

Estimation of Earthquake Early Warning Parameters for Eastern Gulf of Corinth and Western Attica Region (Greece). First Results

Sensors ◽

10.3390/s21155084 ◽

2021 ◽

Vol 21 (15) ◽

pp. 5084

Author(s):

Filippos Vallianatos ◽

Andreas Karakonstantis ◽

Nikolaos Sakelariou

Keyword(s):

Early Warning ◽

Warning System ◽

Seismic Signal ◽

Earthquake Early Warning ◽

Initial Portion ◽

P Waves ◽

Peak Displacement ◽

Earthquake Early Warning System ◽

Gulf Of Corinth ◽

Seismic Risk Management

The main goal of an Earthquake Early Warning System (EEWS) is to alert before the arrival of damaging waves using the first seismic arrival as a proxy, thus becoming an important operational tool for real-time seismic risk management on a short timescale. EEWSs are based on the use of scaling relations between parameters measured on the initial portion of the seismic signal after the arrival of the first wave. To explore the plausibility of EEWSs around the Eastern Gulf of Corinth and Western Attica, amplitude and frequency-based parameters, such as peak displacement (Pd), the integral of squared velocity (IV 2) and the characteristic period (τc), were analyzed. All parameters were estimated directly from the initial 3 s, 4 s, and 5 s signal windows (tw) after the P arrival. While further study is required on the behavior of the proxy quantities, we propose that the IV 2 parameter and the peak amplitudes of the first seconds of the P waves present significant stability and introduce the possibility of a future on-site EEWS for areas affected by earthquakes located in the Eastern Gulf of Corinth and Western Attica. Parameters related to regional-based EEWS need to be further evaluated.

Download Full-text

The Realization of an Earthquake Early Warning System for Schools and Its Performance during the 2019 ML 6.3 Hualien (Taiwan) Earthquake

Seismological Research Letters ◽

10.1785/0220190329 ◽

2020 ◽

Vol 92 (1) ◽

pp. 342-351

Author(s):

Ting-Yu Hsu ◽

Chun-Hsiang Kuo ◽

Hsiu-Hsien Wang ◽

Yu-Wen Chang ◽

Pei-Yang Lin ◽

...

Keyword(s):

Earthquake Engineering ◽

Early Warning ◽

Early Warning System ◽

Warning System ◽

Classification Performance ◽

Earthquake Early Warning ◽

Ground Acceleration ◽

Seismic Stations ◽

Earthquake Early Warning System ◽

Broadcast Stations

Abstract This article discusses the earthquake early warning system (EEWS) for schools of the National Center for Research on Earthquake Engineering, Taiwan (NCREE’s EEWS, earthquake early warning system [NEEWS]) that was recently completed. The system consists of 98 seismic stations with a complete set of system capabilities and 3514 broadcast stations with only the associated alert broadcast system capabilities. The broadcast stations receive both any on-site alerts issued by the seismic stations and any regional alerts issued by the Central Weather Bureau and then broadcast whatever alert is received earliest. Shortly after the establishment of the NEEWS, the ML 6.3 Hualien earthquake, which had a maximum measured peak ground acceleration (PGA) of 515.17 Gal, struck Taiwan on 18 April 2019. During the earthquake, the performance of both the seismic stations and the broadcast stations of the system was documented. The current study analyzes and discusses the accuracy of the PGA predictions, lead times, and classification performance at both the seismic stations and the broadcast stations of the NEEWS. The results show that the NEEWS is a cost-effective and promising system of EEW.

Download Full-text

On-Site Earthquake Early Warning Using Smartphones

Sensors ◽

10.3390/s20102928 ◽

2020 ◽

Vol 20 (10) ◽

pp. 2928

Author(s):

Ting-Yu Hsu ◽

C. P. Nieh

Keyword(s):

Early Warning ◽

Peak Ground Acceleration ◽

False Negative ◽

Warning System ◽

Earthquake Early Warning ◽

Ground Acceleration ◽

Shake Table Tests ◽

Earthquake Early Warning System ◽

Earthquake Event ◽

Earthquake Data

In this study, the measured accelerations of a single smartphone were used to provide an earthquake early warning system. In the presented system, after the smartphone is triggered, the triggering event is then classified as an earthquake event or not. Once an earthquake event is detected, the peak ground acceleration is then predicted every second until 10 s after the trigger. These predictions are made by the neural network classifier and predictor embedded in the smartphone, and an alert can be issued if a large peak ground acceleration is predicted. The proposed system is unique among approaches that use crowdsourcing ideas for earthquake early warning because the proposed system provides on-site earthquake early warning. In general, the accuracy rates of the earthquake classifications and peak ground acceleration predictions of the system were quite high according to the results of large amounts of earthquake and non-earthquake data. More specifically, according to said earthquake data, 96.9% of the issued alerts would be correct and 61.9% of the earthquakes that exceeded the threshold would have resulted in an alert being issued before the arrival of the peak ground acceleration. Among the false negative cases, approximate 97.8% would occur because of negative lead time. Using the shake table tests of worldwide and Meinong earthquake datasets, the proposed approach is confirmed to be quite promising.

Download Full-text

Feasibility study of earthquake early warning in Tehran, Iran

Journal of Seismology ◽

10.1007/s10950-021-10014-3 ◽

2021 ◽

Author(s):

S. Enferadi ◽

Z. H. Shomali ◽

A. Niksejel

Keyword(s):

Early Warning ◽

Early Warning System ◽

Warning System ◽

Earthquake Early Warning ◽

Disaster Mitigation ◽

Lead Times ◽

Worst Case ◽

Earthquake Parameters ◽

Earthquake Early Warning System ◽

Earthquake Scenarios

AbstractIn this study, we examine the scientific feasibility of an Earthquake Early Warning System in Tehran, Iran, by the integration of the Tehran Disaster Mitigation and Management Organization (TDMMO) accelerometric network and the PRobabilistic and Evolutionary early warning SysTem (PRESTo). To evaluate the performance of the TDMMO-PRESTo system in providing the reliable estimations of earthquake parameters and the available lead-times for The Metropolis of Tehran, two different approaches were analyzed in this work. The first approach was assessed by applying the PRESTo algorithms on waveforms from 11 moderate instrumental earthquakes that occurred in the vicinity of Tehran during the period 2009–2020. Moreover, we conducted a simulation analysis using synthetic waveforms of 10 large historical earthquakes that occurred in the vicinity of Tehran. We demonstrated that the six worst-case earthquake scenarios can be considered for The Metropolis of Tehran, which are mostly related to the historical and instrumental events that occurred in the southern, eastern, and western parts of Tehran. Our results indicate that the TDMMO-PRESTo system could provide reliable and sufficient lead-times of about 1 to 15s and maximum lead-times of about 20s for civil protection purposes in The Metropolis of Tehran.

Download Full-text