Mixtures of ground-motion prediction equations as backbone models for a logic tree: an application to the subduction zone in Northern Chile
- 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 usingIn 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.…
Author details: | Annabel Händel, Sebastian von SpechtORCiDGND, Nicolas M. Kuehn, Frank ScherbaumORCiDGND |
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DOI: | https://doi.org/10.1007/s10518-014-9636-7 |
ISSN: | 1570-761X |
ISSN: | 1573-1456 |
Title of parent work (English): | Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering |
Publisher: | Springer |
Place of publishing: | Dordrecht |
Publication type: | Article |
Language: | English |
Year of first publication: | 2015 |
Publication year: | 2015 |
Release date: | 2017/03/27 |
Tag: | Backbone model; Chile subduction zone; Ground-motion prediction equation; Logic tree; Mixture model |
Volume: | 13 |
Issue: | 2 |
Number of pages: | 19 |
First page: | 483 |
Last Page: | 501 |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften |
Peer review: | Referiert |
Institution name at the time of the publication: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften |