Accuracy and Uncertainty Analysis of Selected Methodological Approaches to Earthquake Early Warning in Europe

Author(s):  
Gemma Cremen ◽  
Elisa Zuccolo ◽  
Carmine Galasso

Abstract Earthquake early warning (EEW) is becoming an increasingly attractive real-time strategy for mitigating the threats posed by potentially devastating incoming seismic events. As efforts accelerate to develop practical EEW-based solutions for earthquake-prone countries in Europe, it is important to understand and quantify the level of performance that can be achieved by the underlying seismological algorithms. We conduct a conceptual study on EEW performance in Europe, which explicitly focuses on the accuracy and associated uncertainties of selected methodological approaches. Twenty-three events from four diverse European testbeds are used to compare the quality of EEW predictions produced by the Virtual Seismologist and PRobabilistic and Evolutionary early warning SysTem algorithms. We first examine the location and magnitude estimates of the algorithms, accounting for both bias and uncertainty in the resulting predictions. We then investigate the ground-shaking prediction capabilities of the source-parameter estimates, using an error metric that can explicitly capture the propagation of uncertainties in these estimates. Our work highlights the importance of accounting for EEW parameter uncertainties, which are often neglected in studies of EEW performance. Our findings can be used to inform current and future implementations of EEW systems in Europe. In addition, the evaluation metrics presented in this work can be used to determine EEW accuracy in any worldwide setting.

2020 ◽  
Vol 91 (3) ◽  
pp. 1763-1775 ◽  
Author(s):  
Monica D. Kohler ◽  
Deborah E. Smith ◽  
Jennifer Andrews ◽  
Angela I. Chung ◽  
Renate Hartog ◽  
...  

Abstract The ShakeAlert earthquake early warning system is designed to automatically identify and characterize the initiation and rupture evolution of large earthquakes, estimate the intensity of ground shaking that will result, and deliver alerts to people and systems that may experience shaking, prior to the occurrence of shaking at their location. It is configured to issue alerts to locations within the West Coast of the United States. In 2018, ShakeAlert 2.0 went live in a regional public test in the first phase of a general public rollout. The ShakeAlert system is now providing alerts to more than 60 institutional partners in the three states of the western United States where most of the nation’s earthquake risk is concentrated: California, Oregon, and Washington. The ShakeAlert 2.0 product for public alerting is a message containing a polygon enclosing a region predicted to experience modified Mercalli intensity (MMI) threshold levels that depend on the delivery method. Wireless Emergency Alerts are delivered for M 5+ earthquakes with expected shaking of MMI≥IV. For cell phone apps, the thresholds are M 4.5+ and MMI≥III. A polygon format alert is the easiest description for selective rebroadcasting mechanisms (e.g., cell towers) and is a requirement for some mass notification systems such as the Federal Emergency Management Agency’s Integrated Public Alert and Warning System. ShakeAlert 2.0 was tested using historic waveform data consisting of 60 M 3.5+ and 25 M 5.0+ earthquakes, in addition to other anomalous waveforms such as calibration signals. For the historic event test, the average M 5+ false alert and missed event rates for ShakeAlert 2.0 are 8% and 16%. The M 3.5+ false alert and missed event rates are 10% and 36.7%. Real-time performance metrics are also presented to assess how the system behaves in regions that are well-instrumented, sparsely instrumented, and for offshore earthquakes.


2020 ◽  
Vol 20 (4) ◽  
pp. 921-931
Author(s):  
Simona Colombelli ◽  
Francesco Carotenuto ◽  
Luca Elia ◽  
Aldo Zollo

Abstract. A fundamental feature of any earthquake early warning system is the ability of rapidly broadcast earthquake information to reach a wide audience of potential end users and stakeholders, in an intuitive, customizable way. Smartphones and other mobile devices are nowadays continuously connected to the Internet and represent the ideal tools for earthquake alerts dissemination to inform a large number of users about the potential damaging shaking of an impending earthquake. Here we present a mobile app (named ISNet EWApp or simply EWApp) for Android devices which can receive the alerts generated by a network-based Early Warning system. Specifically, the app receives the earthquake alerts generated by the PRESTo EEWS, which is currently running on the accelerometric stations of the Irpinia Seismic Network (ISNet) in southern Italy. In the absence of alerts, EWApp displays the standard bulletin of seismic events that have occurred within the network. In the event of a relevant earthquake, the app has a dedicated module to predict the expected ground-shaking intensity and the available lead time at the user's position and to provide customized messages to inform the user about the proper reaction to adopt during the alert. We first present the architecture of both the network-based system and EWApp and then describe its essential operational modes. The app is designed in a way that is easily exportable to any other network-based early warning system.


2021 ◽  
Vol 9 ◽  
Author(s):  
Elisa Zuccolo ◽  
Gemma Cremen ◽  
Carmine Galasso

Several earthquake early warning (EEW) algorithms have been developed worldwide for rapidly estimating real-time information (i.e., location, magnitude, ground shaking, and/or potential consequences) about ongoing seismic events. This study quantitatively compares the operational performance of two popular regional EEW algorithms for European conditions of seismicity and network configurations. We specifically test PRobabilistic and Evolutionary early warning SysTem (PRESTo) and the implementation of the Virtual Seismologist magnitude component within SeisComP, VS(SC), which we use jointly with the SeisComP scanloc module for locating events. We first evaluate the timeliness and accuracy of the location and magnitude estimates computed by both algorithms in real-time simulation mode, accounting for the continuous streaming of data and effective processing times. Then, we focus on the alert-triggering (decision-making) phase of EEW and investigate both algorithms’ ability to yield accurate ground-motion predictions at the various temporal instances that provide a range of warning times at target sites. We find that the two algorithms show comparable performances in terms of source parameters. In addition, PRESTo produces better rapid estimates of ground motion (i.e., those that facilitate the largest lead times); therefore, we conclude that PRESTo may have a greater risk-mitigation potential than VS(SC) in general. However, VS(SC) is the optimal choice of EEW algorithm if shorter warning times are permissible. The findings of this study can be used to inform current and future implementations of EEW systems in Europe.


Author(s):  
Sahar Nazeri ◽  
Zaher Hossein Shomali

ABSTRACT The estimation of epicentral distance is a critical step in earthquake early warning systems (EEWSs) that is necessary to characterize the level of expected ground shaking. In this study, two rapid methodologies, that is, B‐Δ and C‐Δ, are evaluated to estimate the epicentral distance for use in the EEWSs around the Tehran region. Traditionally, the B and C coefficients are computed using acceleration records, however, in this study, we utilize both acceleration and velocity waveforms for obtaining a suitable B‐Δ and C‐Δ relationships for the Tehran region. In comparison with observations from Japan, our measurements fall within the range of scatter. However, our results show a lower trend, which can strongly depend on the few numbers of events and range of magnitude (small‐to‐moderate) of earthquakes used in the current research. To improve our result, we include some large earthquakes from Iran, Italy, and Japan with magnitude larger than 5.9. Although the optimal trend is finally obtained by fitting a line to the distance‐averaged points, we conclude that the same trend and relationship as Japan can be used in Tehran early warning system. We also found that B and C parameters are strongly compatible to each other. As time windows of 3.0 and 0.5 s after the P onset are chosen respectively to compute the B and C values, so by selecting the C parameter as a proxy of B parameter to estimate the epicentral distance, we may save significant time in order of about 2.5 s in any earthquake early warning applications.


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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