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Published September 2014 | Published
Journal Article Open

CyberShake-derived ground-motion prediction models for the Los Angeles region with application to earthquake early warning

Abstract

Real-time applications such as earthquake early warning (EEW) typically use empirical ground-motion prediction equations (GMPEs) along with event magnitude and source-to-site distances to estimate expected shaking levels. In this simplified approach, effects due to finite-fault geometry, directivity and site and basin response are often generalized, which may lead to a significant under- or overestimation of shaking from large earthquakes (M > 6.5) in some locations. For enhanced site-specific ground-motion predictions considering 3-D wave-propagation effects, we develop support vector regression (SVR) models from the SCEC CyberShake low-frequency (<0.5 Hz) and broad-band (0–10 Hz) data sets. CyberShake encompasses 3-D wave-propagation simulations of >415 000 finite-fault rupture scenarios (6.5 ≤ M ≤ 8.5) for southern California defined in UCERF 2.0. We use CyberShake to demonstrate the application of synthetic waveform data to EEW as a 'proof of concept', being aware that these simulations are not yet fully validated and might not appropriately sample the range of rupture uncertainty. Our regression models predict the maximum and the temporal evolution of instrumental intensity (MMI) at 71 selected test sites using only the hypocentre, magnitude and rupture ratio, which characterizes uni- and bilateral rupture propagation. Our regression approach is completely data-driven (where here the CyberShake simulations are considered data) and does not enforce pre-defined functional forms or dependencies among input parameters. The models were established from a subset (∼20 per cent) of CyberShake simulations, but can explain MMI values of all >400 k rupture scenarios with a standard deviation of about 0.4 intensity units. We apply our models to determine threshold magnitudes (and warning times) for various active faults in southern California that earthquakes need to exceed to cause at least 'moderate', 'strong' or 'very strong' shaking in the Los Angeles (LA) basin. These thresholds are used to construct a simple and robust EEW algorithm: to declare a warning, the algorithm only needs to locate the earthquake and to verify that the corresponding magnitude threshold is exceeded. The models predict that a relatively moderate M6.5–7 earthquake along the Palos Verdes, Newport-Inglewood/Rose Canyon, Elsinore or San Jacinto faults with a rupture propagating towards LA could cause 'very strong' to 'severe' shaking in the LA basin; however, warning times for these events could exceed 30 s.

Additional Information

© The Authors 2014. Published by Oxford University Press on behalf of The Royal Astronomical Society. Accepted 2014 May 28. Received 2014 May 26; in original form 2013 August 28. To train and test SVR models in this study, we used LIBSVM (Chang & Lin 2011), a free library for Support Vector Machines and Regression. Maps in this paper were made with Generic Mapping Tools version 4.2.1(www.soest.hawaii.edu/gmt; Wessel & Smith 1998).We would like to thank J. Hardebeck, E. Hauksson, T. Heaton, two anonymous reviewers and editor E. Fukuyama for constructive comments that helped to improve this paper. This work is funded through contract G09AC00258 from USGS/ANSS to the California Institute of Technology (Caltech). Funding was also provided by the Gordon and Betty Moore Foundation through Grant GBMF #3023 to Caltech. This is contribution #10094 of the Seismological Laboratory, Geological and Planetary Sciences at Caltech. This research was also supported by the Southern California Earthquake Center (SCEC). SCEC is funded by NSF Cooperative Agreement EAR-0529922 and USGS Cooperative Agreement 07HQAG0008. The SCEC contribution number for this paper is 1799.

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August 22, 2023
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