Empirical site response of Mexico City through regionalization of global subduction GMMs
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Empirical site response of Mexico City through regionalization of global subduction GMMs

Abstract

We assemble a dataset which enhances existing Central America and Mexico data for the NGASubduction (NGA-Sub) project, including now additional earthquake ground motions and site parameters from Mexico. This data has been used to provide regional customization of NGA-Sub global Ground Motion Models (GMMs) for application in Mexico, paying particular attention to the site response of Mexico City (CDMX). The expanded database for Mexico incorporates smaller magnitude earthquakes (M < 6) and three significant events (M 7.2-8.3) that occurred in 2017 and 2018. These latter events are particularly important, because they are well recorded over a broad distance range and apply for hazard-critical conditions. Our focus here is on presenting the observed site response in CDMX, which we model based on the time-averaged shear wave velocity in the upper 30 meters (VS30) and the Peak Ground Acceleration at a reference rock site (PGAr). The empirical model we propose is different from previous work in several ways. First, it is properly centered with respect to GMMs. Second, it is referenced to VS30 = 760 m/s, which is significantly firmer than the reference site previously used in practice, taken from a location on the UNAM campus with VS30 ~ 300 m/s. Third, we identify site amplification as nonlinear, whereas linear response has been assumed in prior models. The extent of this nonlinearity is characterized using an established seismic zonation for CDMX, being more pronounced in softer sites (Zone III) compared to stiffer ones (Zone I). This nonlinear effect is prominent at short periods and disappears at long periods. The advantages of the provided model include a unified framework for both within and outside CDMX (contrasting current practices) and the integration of applicable features from global models with necessary local customization.

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