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Bayesian parameter estimation for space and time interacting earthquake rupture model using historical and physics-based simulated earthquake catalogs

Ceferino, Luis and Galvez, Percy and Ampuero, Jean-Paul and Kiremidjian, Anne and Deierlein, Gregory and Villegas-Lanza, Juan C. (2019) Bayesian parameter estimation for space and time interacting earthquake rupture model using historical and physics-based simulated earthquake catalogs. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20191223-125947611

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Abstract

This paper presents a robust parameter estimation technique for a probabilistic earthquake hazard model that captures time and space interactions between earthquake mainshocks. The approach addresses the existing limitations of parameter estimation techniques by developing a Bayesian formulation and leveraging physics-based simulated synthetic catalogs to expand the limited datasets of historical catalogs. The technique is based on a two-step Bayesian update that uses the synthetic catalog to perform a first parameter estimation and then uses the historical catalog to further calibrate the parameters. We applied this technique to analyze the occurrence of large-magnitude interface earthquakes along 650 km of the central subduction zone in Peru, located offshore of Lima. We built 2,000-years-long synthetic catalogs using quasi-dynamic earthquake cycle simulations based on the rate-and-state friction law. The validity of the synthetic catalogs was verified by comparing their annual magnitude exceedence rates to those of recorded seismicity and their predicted areas of high interseismic coupling to those inferred from geodetic data. We show that when the Bayesian update uses the combination of synthetic and historical data, instead of only the historical data, it reduces the uncertainty of model parameter estimates by 45% on average. Further, our results show that the time-dependent seismic hazard estimated with the both datasets is 40% smaller than the one estimated with only the historical data.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.31223/osf.io/3wfr4DOIDiscussion Paper
https://github.com/ydluo/qdynRelated ItemQDYN Software
ORCID:
AuthorORCID
Ceferino, Luis0000-0003-0322-7510
Ampuero, Jean-Paul0000-0002-4827-7987
Additional Information:Academic Free License (AFL) 3.0. Submitted April 24, 2019; Last edited: July 16, 2020. We thank Stanford University and the Stanford Research Computing Center for providing computational resources and financial support. We acknowledge Pablo Heresi from Stanford University for insightful discussions on the uncertainty of historical catalogs. We acknowledge the support by the Shah Family Fellowship and the Jhon A. Blume Fellowship from the Civil Engineering Department at Stanford University. We acknowledge the support by the French government through the UCAJEDI Investments in the Future project managed by the National Research Agency (ANR) with the reference number ANR-15-IDEX-01. Data and Resources: The QDYN software is open-source and is available at https://github.com/ydluo/qdyn.
Group:Seismological Laboratory
Funders:
Funding AgencyGrant Number
Stanford UniversityUNSPECIFIED
Agence Nationale pour la Recherche (ANR)ANR-15-IDEX-01
Subject Keywords:Bayesian update; earthquake; rate-and-state friction; seismic gap; seismic hazard; subduction; time-dependent hazard
Record Number:CaltechAUTHORS:20191223-125947611
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20191223-125947611
Official Citation:Ceferino, L., Galvez, P., Ampuero, J., Kiremidjian, A., Deierlein, G., & Villegas-Lanza, J. C. (2019, April 25). Bayesian parameter estimation for space and time interacting earthquake rupture model using historical and physics-based simulated earthquake catalogs. https://doi.org/10.31223/osf.io/3wfr4
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:100411
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:23 Dec 2019 21:36
Last Modified:20 Jul 2020 21:54

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