scholarly journals Performance Evaluation of an Earthquake Early Warning System in the 2019–2020 M6.0 Changning, Sichuan, China, Seismic Sequence

2021 ◽  
Vol 9 ◽  
Author(s):  
Chaoyong Peng ◽  
Peng Jiang ◽  
Qiang Ma ◽  
Peng Wu ◽  
Jingrong Su ◽  
...  

China is currently building a nationwide earthquake early warning system (EEWS) which will be completed in June 2023. Several regions have been selected as pilot areas for instrumentation, software system and dissemination verification. For these regions, their construction tasks will be completed in advance with trial runs being carried out in June 2021. Before the trial operation, we need to understand the actual processing capabilities of different EEWSs. In this work, we focus on the system deployed in Sichuan province and evaluate its real-time performance during the 2019–2020 M6.0 Changning seismic sequence. This period was divided into two stages. The first stage was the time from the occurrence of the M6.0 (Mw5.7) mainshock (June 17, 2019) to the end of October 2019 with no MEMS-based stations around the Changning seismic sequence deployed and most of the broadband and short period seismic stations not upgraded to low latency streaming, and the second one was from the beginning of November 2019 to March 2021 with deployments of more than 700 MEMS-based stations and low latency upgrades of ∼30 seismic stations. Median errors for the epicentral locations, depths and magnitude estimations were almost the same for both stages, 1.5 ± 6.0 km, 0.0 ± 3.6 km and −0.1 ± 0.46 for the first stage and 2.3 ± 3.0 km, −3.0 ± 3.6 km and −0.2 ± 0.32 for the second one. However, an obvious underestimation of the magnitude for earthquakes with M 5.0 + occurring in the first stage was observed, which would be caused by the clipped waveforms, sensors deployed in short period seismic stations and MEMS-based stations, the adopted magnitude estimation method, and the method used to computer the network magnitude. The median reporting time was significantly improved from 10.5 ± 3.0 s after origin time for the first stage to 6.3 ± 3.5 s for the second stage because of introduction of newly deployed MEMS-based stations. The results obtained from the second stage indicate that the system has entered a stable operating stage and we can officially launch the trial operation in the pilot areas for public early warning services.

2020 ◽  
Vol 92 (1) ◽  
pp. 342-351
Author(s):  
Ting-Yu Hsu ◽  
Chun-Hsiang Kuo ◽  
Hsiu-Hsien Wang ◽  
Yu-Wen Chang ◽  
Pei-Yang Lin ◽  
...  

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.


Author(s):  
S. Enferadi ◽  
Z. H. Shomali ◽  
A. Niksejel

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.


2017 ◽  
Vol 88 (6) ◽  
pp. 1491-1498 ◽  
Author(s):  
Dong‐Hoon Sheen ◽  
Jung‐Ho Park ◽  
Heon‐Cheol Chi ◽  
Eui‐Hong Hwang ◽  
In‐Seub Lim ◽  
...  

2021 ◽  
Author(s):  
Bita Najdahmadi ◽  
Marco Pilz ◽  
Dino Bindi ◽  
Hoby Njara Tendrisoa Razafindrakoto ◽  
Adrien Oth ◽  
...  

<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 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 will be presented in the meeting.</p>


2018 ◽  
Vol 89 (6) ◽  
pp. 2322-2336 ◽  
Author(s):  
J. R. Murray ◽  
B. W. Crowell ◽  
R. Grapenthin ◽  
K. Hodgkinson ◽  
J. O. Langbein ◽  
...  

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