A New Set of Automated Methodologies for Estimating Site Fundamental Frequency and Its Uncertainty Using Horizontal-to-Vertical Spectral Ratio Curves

Abstract This study proposes a new set of methodologies to estimate the site fundamental frequency using the horizontal-to-vertical spectral ratio (HVSR) of recorded surface ground motions. Because of the lack of consensus in HVSR calculation among researchers, a wide range of methods are practiced in this area, yielding different site fundamental frequencies at a given site due to analyst subjectivity. In this study, current practices for combining horizontal components—geometric mean and RotD50—are examined first, and results show that both methods provide comparable HVSR curves. However, RotD50 has the advantage of being orientation independent. Second, the application of Fourier amplitude spectrum (FAS) and 5% damped pseudospectral acceleration (PSA) in computing HVSR is studied, and results are presented for one case study in which PSA-based HVSR seems to suffer from scenario dependency, whereas the FAS-based results appear stable. Different values for Konno–Ohmachi smoothing parameter b were evaluated, and its effect on estimating the site fundamental frequency was considered; using b = 40 is our preference. In previous studies, average HVSR curves were used to estimate a single number representing the site fundamental frequency without incorporating uncertainty. This study proposes four methodologies that use events’ individual HVSR curves to estimate the site fundamental frequency and its associated uncertainty in a completely automated manner. Methods 1–3 use individual HVSR curves to find the maximum-likelihood estimate of the site fundamental frequency (fml), whereas method 4 uses both individual and average HVSR curves to estimate the first resonance frequency (f0). To evaluate the automated methods, a subset of the Next Generation Attenuation-West2 dataset is used to study 50 stations, and the results are compared with an independent study demonstrating good consistency. The proposed methods are further illustrated using data from the Garner Valley Downhole Array (GVDA), which highlights the pros and cons of the presented methods.