The high-frequency decay term of the acceleration spectrum κ is a commonly used parameter in engineering seismology. In recent years, the assumption of a linearly decaying spectrum in log–linear space has been recognized to not always be valid as the value of κ depends on the analyzed frequency band. We present an alternative model for the spectral falloff in which the frequency dependence is explicitly taken into account. This is motivated by observations that the quality factor Q has a power-law dependence on frequency at high frequencies. The new model describes the spectral decay with the help of two variables, opposite to the single parameter κ. The approach is applied to borehole data of the EUROSEISTEST site in Greece. The misfit between modeled and observed spectra is reduced with the new approach compared with the classical kappa model. The new estimates compare well with κ estimates if the same frequency interval is considered but additionally allows for the capture of the frequency dependence of the spectral shape.

Earthquake site responses or site effects are the modifications of surface geology to seismic waves. How well can we predict the site effects (average over many earthquakes) at individual sites so far? To address this question, we tested and compared the effectiveness of different estimation techniques in predicting the outcrop Fourier site responses separated using the general inversion technique (GIT) from recordings. Techniques being evaluated are (a) the empirical correction to the horizontal-to-vertical spectral ratio of earthquakes (c-HVSR), (b) one-dimensional ground response analysis (GRA), and (c) the square-root-impedance (SRI) method (also called the quarter-wavelength approach). Our results show that c-HVSR can capture significantly more site-specific features in site responses than both GRA and SRI in the aggregate, especially at relatively high frequencies. c-HVSR achieves a “good match” in spectral shape at ∼80%–90% of 145 testing sites, whereas GRA and SRI fail at most sites. GRA and SRI results have a high level of parametric and/or modeling errors which can be constrained, to some extent, by collecting on-site recordings.

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