Site-Response Characterization

c-HVSR Method

Horizontal-to-vertical spectral ratio (HVSR) technique is a cost-effective approach to extract certain site-specific information, e.g., site fundamental frequency (f0), but HVSR values cannot be directly used to approximate the levels of S-wave amplifications. We propose a procedure to correct earthquake HVSR amplitudes for direct amplification estimations. The empirical correction compensates HVSR (i.e., c-HVSR) by generic vertical amplification spectra categorized by the vertical fundamental frequency (f0v) via k-means clustering. Compared to observations, c-HVSR is highly effective and achieves a “good match” with observed site response in both spectral shape and amplitude at the majority of the examined sites, as opposed to less than one-third for the 1DSH modeling.

Zhu, C., M. Pilz, F. Cotton (2020). Evaluation of a Novel Application of Earthquake HVSR in Site-Specific Amplification Estimation. Soil Dynamics and Earthquake Engineering 139, 106301. https://doi.org/10.1016/j.soildyn.2020.106301 

How Well Can We Predict Site Response?

In site response assessments, observation-based site-specific approaches requiring a target-reference recording pair or a recording network cannot be implemented at many sites of interest. Thus, various estimation techniques have to be utilized. How effective are these techniques in predicting site-specific site responses (average over many earthquakes)? To address this question, we (Zhu et al., 2021 and 2022) conducted a systematic comparison using a large dataset that consists of detailed site metadata and Fourier outcrop linear site responses based on observations at 1725 K-NET and KiK-net sites. The comparisons show that proxies/parameters-based site response models have a wide range of levels of performance. The machine learning amplification model using a few predictor variables, surface roughness, peak frequency fP,HV, VS30, and depth Z2.5, achieves better performance than 1D physics-based modeling using detailed 1D velocity profiles.

Zhu, C., F. Cotton, H. Kawase, A. Händel, M. Pilz, K. Nakano (2021). How Well Can We Predict Earthquake Site Response So Far? Site-Specific Approaches. Earthquake Spectra, https://doi.org/10.1177/87552930211060859  

Zhu, C., F. Cotton, H. Kawase, K. Nakano (2022). How Well Can We Predict Earthquake Site Response So Far? Machine Learning vs. Physics-Based Modeling. Preprint.  https://doi.org/10.13140/RG.2.2.34933.91365 

With-Site Variability in Site Response

The within-site variability in site response is the randomness in site response at a given site from different earthquakes and is treated as aleatory variability in current seismic hazard/risk analyses. In this study, we investigate the single-station variability in linear site response at KNET and KiK-net stations in Japan using a large number of earthquake recordings. We found that the standard deviation of the horizontal-to-vertical Fourier spectral ratio at individual sites, that is single-station horizontal-to-vertical spectral ratio (HVSR) sigma σHV,s, approximates the within-site variability in site response quantified using surface-to-borehole spectral ratios (for oscillator frequencies higher than the site fundamental frequency) or empirical ground-motion models. Based on this finding, we then utilize the single-station HVSR sigma as a convenient tool to study the site-response variability at 697 KiK-net and 1169 K-NET sites. Our results show that at certain frequencies, stiff, rough and shallow sites, as well as small and local events tend to have a higher σHV,s. However, when being averaged over different sites, the single-station HVSR sigma, that is σHV, increases gradually with decreasing frequency.