TY  - JOUR
A1  - Händel, Annabel
A1  - von Specht, Sebastian
A1  - Kuehn, Nicolas M.
A1  - Scherbaum, Frank
T1  - Mixtures of ground-motion prediction equations as backbone models for a logic tree: an application to the subduction zone in Northern Chile
JF  - Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering
N2  - 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.
KW  - Mixture model
KW  - Backbone model
KW  - Ground-motion prediction equation
KW  - Logic tree
KW  - Chile subduction zone
Y1  - 2015
U6  - https://doi.org/10.1007/s10518-014-9636-7
SN  - 1570-761X
SN  - 1573-1456
VL  - 13
IS  - 2
SP  - 483
EP  - 501
PB  - Springer
CY  - Dordrecht
ER  -