Uncertainty in intraevent spatial correlation of elastic pseudo-acceleration spectral ordinates
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The probabilistic nature of seismic ground motion intensity measures such as peak ground acceleration and spectral acceleration ordinates has been extensively studied during the last decades. However, their spatial correlation is mostly considered without any event-to-event variability, using a mean estimate from a number of seismic events. The present study quantitatively evaluates the event-to-event uncertainty of intraevent spatial correlations, using 39 well-recorded earthquakes. Results indicate a high event-to-event variability in the correlation model parameters, which if taken explicitly into account, would improve regional hazard and risk analyses. Event magnitude was found to be a statistically significant predictor variable of the model parameter, however it explains less than 20% of the total event-to-event variability. Moreover, clustering of site conditions, tectonic region, and fault mechanism are not statistically significant as predictor variables of the spatial correlation model parameter. Finally, this paper proposes a simple Monte Carlo approach for considering the high event-to-event variability of spatial correlation models, taking advantage of the Markov dependence of residuals for reducing the number of correlated variables to be simulated. This approach can be used with different intraevent spatial correlation models, as long as proper estimates of the dispersion of their parameters are considered.
KeywordsSpatial correlation Uncertainty Ground motion intensity measure Regional risk assessment
The authors would like to acknowledge CONICYT—Becas Chile, the Nancy Grant Chamberlain Fellowship, the Charles H. Leavell Fellowship, the Shah Graduate Student Fellowship, and the John A. Blume Fellowship for their financial support to the first author for conducting his doctoral studies under the supervision of the second author. Records used in this investigation were obtained from the PEER NGA-West2 ground motion database. The authors are grateful to the various government agencies responsible for the installation and maintenance of seismic instrumentation and for making their data publicly available, and to PEER for collecting, processing, and distributing these records. The authors would also like to thank the two anonymous reviewers, whose comments helped improve the quality of this paper.
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