Reducing the uncertainties in the NGA-West2 ground motion models by incorporating the frequency and amplitude of the fundamental peak of the horizontal-to-vertical spectral ratio of surface ground motions

Abstract

Ground motion models (GMMs) are developed empirically to predict ground motion intensity measures. The site effects in GMMs are usually addressed using time-averaged shear-wave velocity for the upper 30 m of the site (VS30) and shear-wave isosurface depth (i.e. Z1.0 and Z2.5). However, the former does not include the effect of layered soil structure on the site’s response, and the latter is generally inferred. Many studies have shown that site fundamental frequency can be used as an additional site proxy. Using horizontal-to-vertical spectral ratio (HVSR), one can estimate the site fundamental frequency in a fast and inexpensive way. In this article, a model is developed to incorporate site fundamental frequency and its corresponding amplification factor in the Next Generation Attenuation (NGA)-West2 GMMs to reduce the uncertainties. First, a subset of the NGA-West2 database consisting of 14,636 recordings from 298 events is selected after a two-step screening procedure and used to compute the horizontal-to-vertical response spectral ratio (HVSRPSA) of recorded surface ground motions. Second, automated methodologies previously developed by the authors are used to obtain maximum likelihood estimates of site fundamental frequency (fml), its corresponding amplitude (Aml), and associated uncertainties. Third, a mixed-effect maximum likelihood approach is implemented for residual analysis and site-term residual calculation. Finally, an HVSR-based model is developed for the NGA-West2 dataset considering the relationship between site-term residual and the HVSR-based proxies (i.e. fml and Aml). In this model, Aml is as important as fml in reducing the uncertainties. Results show that using a single HVSR-based model can consistently reduce the site-to-site variability ([Formula: see text]) for all NGA-West2 GMMs, which already include the effect of VS30, Z1.0, or Z2.5. Besides, the reduction in [Formula: see text] is period-dependent, with an average of 13% reduction. As a result of the reduction in [Formula: see text], total standard deviation ( σ) decreases by 3.5% on average.