Ergodic site amplification models for active tectonic regions are conditioned on the time-averaged shear wave velocity in the upper 30 m ( VS30) and the depth to a shear wave velocity isosurface ( zx). The depth components of such models are derived using data from sites within many geomorphic domains. We provide a site amplification model utilizing VS30 and depth, with the depth component conditioned on type of geomorphic province: basins, valleys, and mountain/hills. As with current models, the depth component of our model is centered with respect to the VS30-scaling model using differential depth δzx, taken as the difference between a site-specific depth and a VS30 -conditioned average depth. Using data from southern California, we find that long-period site response for all sites combined exhibits relative de-amplification and amplification for negative and positive differential depths, respectively. Individual provinces exhibit broadly similar trends with depth, but amplification levels are on average stronger in basins such that little relative de-amplification occurs at negative differential depths. Valley and mountain/hill sites have, on average, weaker amplification levels but stronger scaling with δzx. Site-to-site standard deviations vary appreciably across geomorphic provinces, with basins having lower dispersions than mountain/hill sites and the reference ergodic model.

Peaks in horizontal-to-vertical spectral ratios (HVSRs) of Fourier amplitudes from three-component recordings of ground vibrations without undue local anthropogenic influence are used to identify site resonances, which are an important component of site response. We address two topics: (1) how should HVSR peaks be identified and (2) are there appreciable differences in HVSR derived using different instruments recording microtremors and seismic strong ground motions? We propose identifying peaks by considering peak amplitudes relative to neighboring ordinates and peak width. The procedure incorporates a regression tree algorithm that can be tuned to conform with user preferences toward relatively “conservative” or “liberal” peak identification (producing few or many sites with peaks, respectively). We then investigate the consistency of microtremor-based HVSRs (mHVSRs) derived from seismometers and accelerometers, which show a high rate of false negatives (missed peaks) from accelerometers with a full scale of ± 2g or greater. In contrast, mHVSRs derived from collocated temporary and permanent seismometers (optimized to record teleseismic signals) have about 60%–80% consistency (with no apparent bias in peak attributes). This indicates that mHVSRs from accelerometers having a broad full scale are unreliable but that mHVSRs can be reliably obtained from temporary or permanent seismometers. Finally, we compare seismometer-based HVSR from microtremor and earthquake (eHVSRs) sources. Results are consistent for 60%–70% of sites (i.e., both either do or do not have significant peaks, and when peaks are present, they occur at similar frequencies, <20% change). For sites with an mHVSR peak, the rate of corresponding eHVSR peaks is nearly 50%, whereas for sites without an mHVSR peak the eHVSR peak rate is low (about 20%). The mismatch rate for mHVSR peak sites is sufficiently high that the use of eHVSR to derive site response models is likely too optimistic (overestimates model effectiveness); mHVSR is preferred for consistency with information available in forward applications.

Ground-motion models (GMMs) typically include a source-to-site path model that describes the attenuation of ground motion with distance due to geometric spreading and anelastic attenuation. In contemporary GMMs, the anelastic component is typically derived for use in one or more broad geographical regions such as California or Japan, which necessarily averages spatially variable path effects within those regions. We extend that path modeling framework to account for systematic variations of anelastic attenuation for ten physiographic subregions in California that are defined in consideration of geological differences. Using a large database that is approximately doubled in size for California relative to Next Generation Attenuation (NGA)-West2, we find relatively high attenuation in Coast Range areas (North Coast, Bay area, and Central Coast), relatively low attenuation in eastern California (Sierra Nevada, eastern California shear zone), and state-average attenuation elsewhere, including southern California. As part of these analyses, we find for the North Coast region relatively weak ground motions on average from induced events (from the Geysers), similar attenuation rates for induced and tectonic events, and higher levels of ground-motion dispersion than other portions of the state. The proposed subregional path model appreciably reduces within-event and single-station variability relative to an NGA-West2 GMM for ground motions at large distance (RJB>100  km). The approach presented here can readily be adapted for other GMMs and regions.

We develop a site amplification model for a regional geologic condition that includes surficial deposits of peaty organic soils in Hokkaido, Japan. We use ground motion data from national Japanese networks along with local data from the study region. We apply a non-reference site approach to infer site effects from misfits of reference ground motion models to data from 10 subduction zone earthquakes. Application of this approach requires removal of source-specific biases and careful consideration of source-to-site path effects. These considerations are essential to avoid mapping source- or path-related model misfits into estimates of site response. We consider three subduction ground motion models as reference models. By paying special attention to the conditions for which the path models are effective, and making adjustments for between-island path misfits (Hokkaido to Honshu and vice versa), we identify regional site effects that are insensitive to the ground motion models used in their derivation. Observed site responses are characterized by strong resonances at first-mode site frequencies, and as a result the regional model is conditioned on peak frequency from horizontal-to-vertical spectral ratios.

This paper presents a model for distributing zones of liquefaction and nonliquefaction for use in regional liquefaction risk analysis. There are two broad methodologies that have been used to evaluate liquefaction risk on the regional scale: (a) application of site-specific procedures using soil properties inferred from geology, or (b) application of geospatial proxies for liquefaction. The first approach will tend to predict similar liquefaction probabilities across broad areas with similar geology, water table depths, and shaking intensities. The second approach yields the probability of liquefaction, which can be interpreted as the portion of the area affected by liquefaction ([Formula: see text]). Neither approach, however, gives an informed prediction of the spatial distribution of liquefaction and the resulting displacements, which are particularly important for assessments of seismic risk for spatially distributed infrastructure systems. We propose a methodology for incorporating spatial correlation into a geospatial proxy for liquefaction to create maps of liquefaction and nonliquefaction for a given earthquake scenario. First, we describe a latent Gaussian process that is assumed to govern the spatial distribution of liquefaction. Next, a database of empirical observations of liquefaction is used to obtain the coefficients that describe that latent Gaussian process. The proposed model yields random realizations of maps of liquefaction and nonliquefaction conditioned on a map of [Formula: see text]. Such maps can be used to constrain the area over which displacements are estimated using soil properties inferred from geology and are therefore a critical component in reducing bias in assessments of liquefaction risk at the regional scale.