Performance of On-Site Earthquake Early Warning System Using Strong-Motion Records from Recent Earthquakes

2019 ◽  
Vol 20 (1) ◽  
pp. 04018030 ◽  
Author(s):  
Duruo Huang ◽  
Gang Wang ◽  
Feng Jin
2015 ◽  
Vol 40 ◽  
pp. 51-61 ◽  
Author(s):  
M. Picozzi ◽  
L. Elia ◽  
D. Pesaresi ◽  
A. Zollo ◽  
M. Mucciarelli ◽  
...  

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.


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>


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