Engineering site response analysis of Anchorage, Alaska, using site amplifications and random vibration theory

Earthquake records collected at dense arrays of strong‐motion stations are often utilized in microzonation studies to evaluate the changes in site response due to variability in site conditions across a region. These studies typically begin with calculating Fourier spectral amplification(s) and then transition to performing engineering site response analyses. It has proven difficult to utilize Fourier spectral amplification(s) to define the appropriate elastic response spectr(um)/(a) for a site or sites. This is because, first, the ground motions recorded at these strong‐motion stations have lower intensity and hence do not show the nonlinear site effects observed during higher‐intensity earthquakes and, second, Fourier and response spectral amplitudes measure different aspects of ground motions. The strong‐motion stations in Anchorage, Alaska, have been recording earthquakes in the region for the last three decades. This study utilizes a database of 95 events from 2004 to 2019 to calculate Fourier spectral amplifications at 35 stations using the generalized inversion technique (GIT). Estimated response spectra have been evaluated at each site by applying those Fourier spectral amplifications to a response spectrum of a reference station through random vibration theory (RVT). Correction factors are also applied within the approach to account for nonlinear site effects. This RVT‐based approach is tested using ground motions recorded during the M W 7.1 2018 Anchorage Earthquake, and close matches between measured and predicted response spectra are found. The method is then compared with site response analyses using a calibrated 1D equivalent linear (EQL) model of the Delaney Park Downhole Array site. Estimated spectra using the RVT‐based approach are, finally, compared with those using Next Generation Attenuation Subduction (NGA‐Sub) and NGA‐West2 ground‐motion models. The proposed method provides a coherent and straightforward way to use GIT‐derived Fourier spectral amplifications to directly estimate site‐specific response spectra, accounting for nonlinear site effects and without requiring engineering characterization of subsurface soil conditions.