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Mixtures of ground-motion prediction equations as backbone models for a logic tree: an application to the subduction zone in Northern Chile

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Abstract

In probabilistic seismic hazard analysis, different ground-motion prediction equations (GMPEs) are commonly combined within a logic tree framework. The selection of appropriate GMPEs, however, is a non-trivial task, especially for regions where strong motion data are sparse and where no indigenous GMPE exists because the set of models needs to capture the whole range of ground-motion uncertainty. In this study we investigate the aggregation of GMPEs into a mixture model with the aim to infer a backbone model that is able to represent the center of the ground-motion distribution in a logic tree analysis. This central model can be scaled up and down to obtain the full range of ground-motion uncertainty. The combination of models into a mixture is inferred from observed ground-motion data. We tested the new approach for Northern Chile, a region for which no indigenous GMPE exists. Mixture models were calculated for interface and intraslab type events individually. For each source type we aggregated eight subduction zone GMPEs using mainly new strong-motion data that were recorded within the Plate Boundary Observatory Chile project and that were processed within this study. We can show that the mixture performs better than any of its component GMPEs, and that it performs comparable to a regression model that was derived for the same dataset. The mixture model seems to represent the median ground motions in that region fairly well. It is thus able to serve as a backbone model for the logic tree.

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Acknowledgments

The two first authors of this study were partially supported by the Integrated Plate Boundary Observatory Chile (IPOC). Annabel Haendel would like to thank the Helmholtz graduate research school GeoSim (http://www.geo-x.net/geosim) for providing a scholarship. We are grateful to the IPOC members and Maria C. Arango for providing the accelerograms of this study, and we are especially grateful to Ruben Boroschek and Bernd Schurr for help and background information regarding the dataset. The authors would like to thank Helmut Staedtke for the implementation of a conversion tool, Elise Delavaud for guidance regarding the horizontal component conversion and Antonia Runge for many discussions about the mixture model approach. We are grateful to the two anonymous reviewers for valuable suggestions and comments, which helped to bring the manuscript to the present form.

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Authors and Affiliations

  1. Institute of Earth and Environmental Science, University of Potsdam, Potsdam, Germany

    Annabel Haendel, Sebastian Specht & Frank Scherbaum

  2. University of California, Berkeley, Berkeley, CA, USA

    Nicolas M. Kuehn

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  1. Annabel Haendel
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  2. Sebastian Specht
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  4. Frank Scherbaum
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Correspondence to Annabel Haendel.

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Haendel, A., Specht, S., Kuehn, N.M. et al. Mixtures of ground-motion prediction equations as backbone models for a logic tree: an application to the subduction zone in Northern Chile. Bull Earthquake Eng 13, 483–501 (2015). https://doi.org/10.1007/s10518-014-9636-7

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