A Laboratory Earthquake-Based Stochastic Seismic Source Generation Algorithm for Strike-Slip Faults and its Application to the Southern San Andreas Fault

Abstract
There is a sparse number of credible source models available from largemagnitude past earthquakes. A stochastic source-model-generation algorithm thus becomes necessary for robust risk quantification using scenario earthquakes. We present an algorithm that combines the physics of fault ruptures as imaged in laboratory earthquakes with stress estimates on the fault constrained by field observations to generate stochastic source models for large-magnitude (Mw 6.0-8.0) strike-slip earthquakes. The algorithm is validated through a statistical comparison of synthetic groundmotion histories from a stochastically generated source model for a magnitude 7.90 earthquake and a kinematic finite-source inversion of an equivalent magnitude past earthquake on a geometrically similar fault. The synthetic dataset comprises threecomponent ground-motion waveforms, computed at 636 sites in southern California, for 10 hypothetical rupture scenarios (five hypocenters, each with two rupture directions) on the southern San Andreas fault. A similar validation exercise is conducted for a magnitude 6.0 earthquake, the lower magnitude limit for the algorithm. Additionally, ground motions from the Mw 7.9 earthquake simulations are compared against predictions by the Campbell-Bozorgnia Next Generation Attenuation relation, as well as the ShakeOut scenario earthquake. The algorithm is then applied to generate 50 source models for a hypothetical magnitude 7.9 earthquake originating at Parkfield, California, with rupture propagating from north to south (toward Wrightwood), similar to the 1857 Fort Tejon earthquake. Using the spectral element method, three-component ground-motion waveforms are computed in the Los Angeles basin for each scenario earthquake and the sensitivity of ground-shaking intensity to seismic source parameters (such as the percentage of asperity area relative to the fault area, rupture speed, and rise time) is studied.

Citation
Siriki, H., Bhat, H. S., Lu, X., & Krishnan, S. (2015). A Laboratory Earthquake-Based Stochastic Seismic Source Generation Algorithm for Strike-Slip Faults and its Application to the Southern San Andreas Fault. Bulletin of the Seismological Society of America, 105(4), 2250–2273. doi:10.1785/0120140110

Acknowledgements
We acknowledge the financial support from the U.S. National Science Foundation-Civil, Mechanical and Manufacturing Innovation (NSF-CMMI Award Number 0926962) and the U.S. Geological Survey (USGS) National Earthquake Hazards Reduction Program (NEHRP Award Number G09AP00063). We thank Thomas Heaton (Caltech), Jean Paul Ampuero (Caltech), Dimitri Komatitsch (Centre National de la Recherche Scientifique/University of Aix-Marseille), Martin Mai (King Abdullah University of Science and Technology [KAUST]), Rob Graves (USGS), and Chen Ji (University of California Santa Barbara) for offering valuable insights into various aspects of source physics and seismic-wave propagation. We thank Chen Ji and Martin Mai for providing us with finite-source inversion models of past earthquakes. We thank Ares Rosakis and Nadia Lapusta for providing us with data from laboratory earthquakes. We are grateful to members of the Tromp research groups at Princeton (current) and Caltech, the Shaw Research Group at Harvard for the continued development of SPECFEM3D, and Southern California Earthquake Center (SCEC) Community Velocity Model-Harvard (CVM-H) for free use by the research community at large. We thank the reviewers and Associate Editor Luis Angel Dalguer for their valuable insights. The authors would also like to acknowledge the central role of the SCEC in advancing earth system science in southern California, directly benefiting many elements of this study.

Publisher
Seismological Society of America (SSA)

Journal
BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA

DOI
10.1785/0120140110

Additional Links
http://www.crossref.org/iPage?doi=10.1785%2F0120140110

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