Construction of a Ground-Motion Logic Tree through Host-to-Target Region Adjustments Applied to an Adaptable Ground-Motion Prediction Model

ABSTRACT The purpose of a median ground-motion logic tree is to capture the center, body, and range of possible ground-motion amplitudes for each earthquake scenario considered in a seismic hazard analysis. For site-specific hazard analyses, the traditional approach of populating the logic tree branches with ground-motion prediction models (GMPMs) selected and weighted on the basis of vaguely defined applicability to the target region is rapidly being abandoned in favor of the backbone GMPM approach. In this approach, the selected backbone model is first adjusted to match the earthquake source and path characteristics of the target region, and then it is separately adjusted to account for the site-specific geotechnical profile. For a GMPM to be amenable to such host-to-target adjustments, the magnitude scaling of response spectral ordinates should be consistent with the theoretical scaling of Fourier amplitude spectra. In addition, the influence of individual source and path parameters should be clearly distinguished in the model to allow the adjustments to be applied individually, and reliable estimates of the source and path parameters from the host region of the GMPM should be available, as should a reference rock profile for the model. The NGA-West2 project GMPM of Chiou and Youngs (2014; hereafter, CY14) has been identified as a very suitable backbone model. Moreover, rather than adopting generic source and path parameters and a rock site profile from the host region for CY14, which is not easily defined because the data from which it was derived came from several geographical locations, recent studies have inverted the model to obtain a CY14-consistent reference rock profile and CY14-compatible source and path parameters. Using these host-region characteristics, this study illustrates the process of building a ground-motion logic tree through the sequential application of multiple host-to-target-region adjustments, each represented by a node on the logic tree to achieve a tractable model for the total epistemic uncertainty.