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    Bayesian Parameter Estimation for Space and Time Interacting Earthquake Rupture Model Using Historical and Physics-Based Simulated Earthquake Catalogs

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    Type
    Article
    Authors
    Ceferino, Luis cc
    Galvez, Percy cc
    Ampuero, Jean-Paul cc
    Kiremidjian, Anne
    Deierlein, Gregory cc
    Villegas-Lanza, Juan C. cc
    KAUST Department
    Physical Science and Engineering (PSE) Division
    Date
    2021-06-29
    Embargo End Date
    2022-06-29
    Permanent link to this record
    http://hdl.handle.net/10754/669848
    
    Metadata
    Show full item record
    Abstract
    ABSTRACT This article introduces a framework to supplement short historical catalogs with synthetic catalogs and determine large earthquakes’ recurrence. For this assessment, we developed a parameter estimation technique for a probabilistic earthquake occurrence model that captures time and space interactions between large mainshocks. The technique is based on a two-step Bayesian update that uses a synthetic catalog from physics-based simulations for initial parameter estimation and then the historical catalog for further calibration, fully characterizing parameter uncertainty. The article also provides a formulation to combine multiple synthetic catalogs according to their likelihood of representing empirical earthquake stress drops and Global Positioning System-inferred interseismic coupling. We applied this technique to analyze large-magnitude earthquakes’ recurrence along 650 km of the subduction fault’s interface located offshore Lima, Peru. We built nine 2000 yr long synthetic catalogs using quasi-dynamic earthquake cycle simulations based on the rate-and-state friction law to supplement the 450 yr long historical catalog. When the synthetic catalogs are combined with the historical catalog without propagating their uncertainty, we found average relative reductions larger than 90% in the recurrence parameters’ uncertainty. When we propagated the physics-based simulations’ uncertainty to the posterior, the reductions in uncertainty decreased to 60%–70%. In two Bayesian assessments, we then show that using synthetic catalogs results in higher parameter uncertainty reductions than using only the historical catalog (69% vs. 60% and 83% vs. 80%), demonstrating that synthetic catalogs can be effectively combined with historical data, especially in tectonic regions with short historical catalogs. Finally, we show the implications of these results for time-dependent seismic hazard.
    Citation
    Ceferino, L., Galvez, P., Ampuero, J.-P., Kiremidjian, A., Deierlein, G., & Villegas-Lanza, J. C. (2021). Bayesian Parameter Estimation for Space and Time Interacting Earthquake Rupture Model Using Historical and Physics-Based Simulated Earthquake Catalogs. Bulletin of the Seismological Society of America. doi:10.1785/0120210013
    Sponsors
    The authors thank the Stanford Research Computing Center for providing computational resources. The authors acknowledge Heresi from Stanford University for insightful discussions on the uncertainty of historical catalogs. The authors acknowledge the support by the Shah Family Fellowship, the John A. Blume Fellowship from the Civil Engineering Department at Stanford University, and the Postdoctoral Fellowship from the Andlinger Center at Princeton University. The authors acknowledge the support by the French National Research Agency (ANR) with reference number ANR-15-IDEX-01 through the Université Côte d’Azur's Joint, Excellent and Dynamic Initiative. The authors also appreciate the constructive comments and suggestions of the BSSA reviewers of the article.
    Publisher
    Seismological Society of America (SSA)
    Journal
    Bulletin of the Seismological Society of America
    DOI
    10.1785/0120210013
    Additional Links
    https://pubs.geoscienceworld.org/bssa/article/doi/10.1785/0120210013/605732/Bayesian-Parameter-Estimation-for-Space-and-Time
    ae974a485f413a2113503eed53cd6c53
    10.1785/0120210013
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division

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