Earthquake Early Warning: Advances, Scientific Challenges, and Societal Needs

2019 ◽  
Vol 47 (1) ◽  
pp. 361-388 ◽  
Author(s):  
Richard M. Allen ◽  
Diego Melgar
Keyword(s):  
Ground Motion ◽  
Early Warning ◽  
The United States ◽  
Earthquake Early Warning ◽  
Ground Shaking ◽  
Motion Models ◽  
Societal Needs ◽  
Finite Fault ◽  
User Groups ◽  
Ground Motion Models

Earthquake early warning (EEW) is the delivery of ground shaking alerts or warnings. It is distinguished from earthquake prediction in that the earthquake has nucleated to provide detectable ground motion when an EEW is issued. Here we review progress in the field in the last 10 years. We begin with EEW users, synthesizing what we now know about who uses EEW and what information they need and can digest. We summarize the approaches to EEW and gather information about currently existing EEW systems implemented in various countries while providing the context and stimulus for their creation and development. We survey important advances in methods, instrumentation, and algorithms that improve the quality and timeliness of EEW alerts. We also discuss the development of new, potentially transformative ideas and methodologies that could change how we provide alerts in the future. ▪ Earthquake early warning (EEW) is the rapid detection and characterization of earthquakes and delivery of an alert so that protective actions can be taken. ▪ EEW systems now provide public alerts in Mexico, Japan, South Korea, and Taiwan and alerts to select user groups in India, Turkey, Romania, and the United States. ▪ EEW methodologies fall into three categories, point source, finite fault, and ground motion models, and we review the advantages of each of these approaches. ▪ The wealth of information about EEW uses and user needs must be employed to focus future developments and improvements in EEW systems.

Are Near-Fault Fling Effects Captured in the New NGA West2 Ground Motion Models?

2015 ◽  
Vol 31 (3) ◽  
pp. 1629-1645 ◽  
Author(s):  
Ronnie Kamai ◽  
Norman Abrahamson
Keyword(s):  
Ground Motion ◽  
Vertical Component ◽  
Strong Motion ◽  
Motion Processing ◽  
Large Set ◽  
Pass Filter ◽  
Motion Models ◽  
Finite Fault ◽  
Maximum Period ◽  
Ground Motion Models

We evaluate how much of the fling effect is removed from the NGA database and accompanying GMPEs due to standard strong motion processing. The analysis uses a large set of finite-fault simulations, processed with four different high-pass filter corners, representing the distribution within the PEER ground motion database. The effects of processing on the average horizontal component, the vertical component, and peak ground motion values are evaluated by taking the ratio between unprocessed and processed values. The results show that PGA, PGV, and other spectral values are not significantly affected by processing, partly thanks to the maximum period constraint used when developing the NGA GMPEs, but that the bias in peak ground displacement should not be ignored.

End-to-end PGA estimation for earthquake early warning using transformer networks

2020 ◽  
Author(s):  
Jannes Münchmeyer ◽  
Dino Bindi ◽  
Ulf Leser ◽  
Frederik Tilmann
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Ground Motion ◽  
Early Warning ◽  
Earthquake Early Warning ◽  
P Wave ◽  
Lead Times ◽  
Ground Shaking ◽  
Target Sites ◽  
End To End

<p>The key task of earthquake early warning is to provide timely and accurate estimates of the ground shaking at target sites. Current approaches use either source or propagation based methods. Source based methods calculate fast estimates of the earthquake source parameters and apply ground motion prediction equations to estimate shaking. They suffer from saturation effects for large events, simplified assumptions and the need for a well known hypocentral location, which usually requires arrivals at multiple stations. Propagation based methods estimate levels of shaking from the shaking at neighboring stations and therefore have short warning times and possibly large blind zones. Both methods only use specific features from the waveform. In contrast, we present a multi-station neural network method to estimate horizontal peak ground acceleration (PGA) anywhere in the target region directly from raw accelerometer waveforms in real time.</p><p>The three main components of our model are a convolutional neural network (CNN) for extracting features from the single-station three-component accelerograms, a transformer network for combining features from multiple stations and for transferring them to the target site features and a mixture density network to generate probabilistic PGA estimates. By using a transformer network, our model is able to handle a varying set and number of stations as well as target sites. We train our model end-to-end using recorded waveforms and PGAs. We use data augmentation to enable the model to provide estimations at targets without waveform recordings. Starting with the arrival of a P wave at any station of the network, our model issues real-time predictions at each new sample. The predictions are Gaussian mixtures, giving estimates of both expected value and uncertainties. The model can be used to predict PGA at specific target sites, as well as to generate ground motion maps.</p><p>We analyze the model on two strong motion data sets from Japan and Italy in terms of standard deviation and lead times. Through the probabilistic predictions we are able to give lead times for different levels of uncertainty and ground shaking. This allows to control the ratio of missed detections to false alerts. Preliminary analysis suggest that for levels between 1%g and 10%g our model achieves multi-second lead times even for the closest stations at a false-positive rate below 25%. For an example event at 50 km depth, lead times at the closest stations with epicentral distances below 20 km are 6 s and 7.5 s. This suggests that our model is able to effectively use the difference between P and S travel time and accurately assess the future level of ground shaking from the first parts of the P wave. It additionally makes effective use of the information contained in the absence of signal at other stations.</p>

scholarly journals Earthquake Early Warning ShakeAlert 2.0: Public Rollout

2020 ◽  
Vol 91 (3) ◽  
pp. 1763-1775 ◽  
Author(s):  
Monica D. Kohler ◽  
Deborah E. Smith ◽  
Jennifer Andrews ◽  
Angela I. Chung ◽  
Renate Hartog ◽  
...  
Keyword(s):  
United States ◽  
Early Warning ◽  
Performance Metrics ◽  
Warning System ◽  
The United States ◽  
Earthquake Early Warning ◽  
Earthquake Risk ◽  
Waveform Data ◽  
Ground Shaking ◽  
Event Rates

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.

scholarly journals Comparing the Performance of Regional Earthquake Early Warning Algorithms in Europe

2021 ◽  
Vol 9 ◽  
Author(s):  
Elisa Zuccolo ◽  
Gemma Cremen ◽  
Carmine Galasso
Keyword(s):  
Real Time ◽  
Ground Motion ◽  
Early Warning ◽  
Risk Mitigation ◽  
Source Parameters ◽  
Warning System ◽  
Optimal Choice ◽  
Earthquake Early Warning ◽  
Ground Shaking ◽  
Processing Times

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.

scholarly journals Regional broad-band ground-shaking modelling over extended and thick sedimentary basins: an example from the Lower Rhine Embayment (Germany)

2020 ◽  
Author(s):  
Marco Pilz ◽  
Fabrice Cotton ◽  
Hoby Njara Tendrisoa Razafindrakoto ◽  
Graeme Weatherill ◽  
Thomas Spies
Keyword(s):  
Ground Motion ◽  
Broad Band ◽  
Soft Rock ◽  
Sedimentary Basins ◽  
Response Spectra ◽  
Site Specific ◽  
Ground Shaking ◽  
Motion Models ◽  
Ground Motion Models ◽  
Lower Rhine Embayment

AbstractThe simulation of broad-band (0.1 to 10 + Hz) ground-shaking over deep and spatially extended sedimentary basins at regional scales is challenging. We evaluate the ground-shaking of a potential M 6.5 earthquake in the southern Lower Rhine Embayment, one of the most important areas of earthquake recurrence north of the Alps, close to the city of Cologne in Germany. In a first step, information from geological investigations, seismic experiments and boreholes is combined for deriving a harmonized 3D velocity and attenuation model of the sedimentary layers. Three alternative approaches are then applied and compared to evaluate the impact of the sedimentary cover on ground-motion amplification. The first approach builds on existing response spectra ground-motion models whose amplification factors empirically take into account the influence of the sedimentary layers through a standard parameterization. In the second approach, site-specific 1D amplification functions are computed from the 3D basin model. Using a random vibration theory approach, we adjust the empirical response spectra predicted for soft rock conditions by local site amplification factors: amplifications and associated ground-motions are predicted both in the Fourier and in the response spectra domain. In the third approach, hybrid physics-based ground-motion simulations are used to predict time histories for soft rock conditions which are subsequently modified using the 1D site-specific amplification functions computed in method 2. For large distances and at short periods, the differences between the three approaches become less notable due to the significant attenuation of the sedimentary layers. At intermediate and long periods, generic empirical ground-motion models provide lower levels of amplification from sedimentary soils compared to methods taking into account site-specific 1D amplification functions. In the near-source region, hybrid physics-based ground-motions models illustrate the potentially large variability of ground-motion due to finite source effects.

Ground Motion Models Used in the 2014 U.S. National Seismic Hazard Maps

2015 ◽  
Vol 31 (1_suppl) ◽  
pp. S59-S84 ◽  
Author(s):  
Sanaz Rezaeian ◽  
Mark D. Petersen ◽  
Morgan P. Moschetti
Keyword(s):  
United States ◽  
Seismic Hazard ◽  
Ground Motion ◽  
The United States ◽  
Hazard Maps ◽  
Source Characterization ◽  
Ground Acceleration ◽  
Seismic Hazard Maps ◽  
Motion Models ◽  
Ground Motion Models

The National Seismic Hazard Maps (NSHMs) are an important component of seismic design regulations in the United States. This paper compares hazard using the new suite of ground motion models (GMMs) relative to hazard using the suite of GMMs applied in the previous version of the maps. The new source characterization models are used for both cases. A previous paper ( Rezaeian et al. 2014 ) discussed the five NGA-West2 GMMs used for shallow crustal earthquakes in the Western United States (WUS), which are also summarized here. Our focus in this paper is on GMMs for earthquakes in stable continental regions in the Central and Eastern United States (CEUS), as well as subduction interface and deep intraslab earthquakes. We consider building code hazard levels for peak ground acceleration (PGA), 0.2-s, and 1.0-s spectral accelerations (SAs) on uniform firm-rock site conditions. The GMM modifications in the updated version of the maps created changes in hazard within 5% to 20% in WUS; decreases within 5% to 20% in CEUS; changes within 5% to 15% for subduction interface earthquakes; and changes involving decreases of up to 50% and increases of up to 30% for deep intraslab earthquakes for most U.S. sites. These modifications were combined with changes resulting from modifications in the source characterization models to obtain the new hazard maps.

Ground-motion models for Vrancea intermediate-depth earthquakes

2021 ◽  
pp. 875529302110329
Author(s):  
Elena Florinela Manea ◽  
Carmen Ortanza Cioflan ◽  
Laurentiu Danciu
Keyword(s):  
Ground Motion ◽  
Site Response ◽  
Seismic Station ◽  
Moment Magnitude ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Ground Shaking ◽  
Intermediate Depth ◽  
Motion Models ◽  
Ground Motion Models

A newly compiled high-quality ground-shaking dataset of 207 intermediate-depth earthquakes recorded in the Vrancea region of the south-eastern Carpathian mountains in Romania was used to develop region-specific empirical predictive equations for various intensity measures: peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral acceleration up to 10 s. Besides common predictor variables (e.g. moment magnitude, depth, hypocentral distance, and site conditions), additional distance scaling parameters were added to describe the specific attenuation pattern observed at the stations located not only on the back and fore but also along the Carpathian arc. In this model, we introduce a proxy measure for the site as the fundamental frequency of resonance to characterize the site response at each recording seismic station beside the soil classes. To additionally reduce the site-to-site variability, a non-ergodic methodology was considered, resulting in a lower standard deviation of about 25%. Statistical evaluation of the newly proposed ground-motion models indicates robust performance compared to regional observations. The model shows significant improvements in describing the spatial variability (at different spectral ordinates), particularly for the fore-arc area of the Carpathians where a deep sedimentary basin is located. Furthermore, the model presented herein improves estimates of ground shaking at longer spectral ordinates (>1 s) in agreement with the observations. The proposed ground-motion models are valid for hypocentral distances less than 500 km, depths over 70 km and within the moment magnitude range of 4.0–7.4.

scholarly journals Real-Time Prediction of Impending Ground Shaking: Review of Wavefield-Based (Ground-Motion-Based) Method for Earthquake Early Warning

2021 ◽  
Vol 9 ◽  
Author(s):  
Mitsuyuki Hoshiba
Keyword(s):  
Real Time ◽  
Ground Motion ◽  
Early Warning ◽  
Ground Motions ◽  
Source Parameters ◽  
Earthquake Early Warning ◽  
Peak Ground Velocity ◽  
Ground Shaking ◽  
Time Prediction ◽  
Seismic Waveform

Earthquake early warning (EEW) systems aim to provide advance warning of impending ground shaking, and the technique used for real-time prediction of shaking is a crucial element of EEW systems. Many EEW systems are designed to predict the strength of seismic ground motions (peak ground acceleration, peak ground velocity, or seismic intensity) based on rapidly estimated source parameters (the source-based method), such as hypocentral location, origin time, magnitude, and extent of fault rupture. Recently, however, the wavefield-based (or ground-motion-based) method has been developed to predict future ground motions based directly on the current wavefield, i.e., ground motions monitored in real-time at neighboring sites, skipping the process of estimation of the source parameters. The wavefield-based method works well even for large earthquakes with long duration and huge rupture extents, highly energetic earthquakes that deviate from standard empirical relations, and multiple simultaneous earthquakes, for which the conventional source-based method sometimes performs inadequately. The wavefield-based method also enables prediction of the ongoing seismic waveform itself using the physics of wave propagation, thus providing information on the duration, in addition to the strength of strong ground motion for various frequency bands. In this paper, I review recent developments of the wavefield-based method, from simple applications using relatively sparse observation networks to sophisticated data assimilation techniques exploiting dense networks.

Implementation of NGA-West2 Ground Motion Models in the 2014 U.S. National Seismic Hazard Maps

2014 ◽  
Vol 30 (3) ◽  
pp. 1319-1333 ◽  
Author(s):  
Sanaz Rezaeian ◽  
Mark D. Petersen ◽  
Morgan P. Moschetti ◽  
Peter Powers ◽  
Stephen C. Harmsen ◽  
...  
Keyword(s):  
United States ◽  
Seismic Hazard ◽  
Ground Motion ◽  
The United States ◽  
Hazard Maps ◽  
Seismic Hazard Maps ◽  
Motion Models ◽  
Seismic Source Models ◽  
Ground Motion Models ◽  
The U.S

The U.S. National Seismic Hazard Maps (NSHMs) have been an important component of seismic design regulations in the United States for the past several decades. These maps present earthquake ground shaking intensities at specified probabilities of being exceeded over a 50-year time period. The previous version of the NSHMs was developed in 2008; during 2012 and 2013, scientists at the U.S. Geological Survey have been updating the maps based on their assessment of the “best available science,” resulting in the 2014 NSHMs. The update includes modifications to the seismic source models and the ground motion models (GMMs) for sites across the conterminous United States. This paper focuses on updates in the Western United States (WUS) due to the use of new GMMs for shallow crustal earthquakes in active tectonic regions developed by the Next Generation Attenuation (NGA-West2) project. Individual GMMs, their weighted combination, and their impact on the hazard maps relative to 2008 are discussed. In general, the combined effects of lower medians and increased standard deviations in the new GMMs have caused only small changes, within 5–20%, in the probabilistic ground motions for most sites across the WUS compared to the 2008 NSHMs.

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

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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