3D near-surface soil response from H/V ambient-noise ratios

E. W. Wollery; R. Street

doi:10.1016/s0267-7261(02)00109-4

Home/Archive/USGS

USGS · 70024321

3D near-surface soil response from H/V ambient-noise ratios

E. W. Wollery·R. Street

View original source ↗Export metadata ↓

Abstract

The applicability of the horizontal-to-vertical (H/V) ambient-noise spectral ratio for characterizing earthquake site effects caused by nearsurface topography and velocity structures was evaluated at sites underlain by thick (i.e. >100 m) sediment deposits near the southern-end of the New Madrid seismic zone in the central United States. Three-component ambient-noise and velocity models derived from seismic (shearwave) refraction/reflection surveys showed that a relatively horizontal, sharp shear-wave velocity interface in the soil column resulted in an H/V spectral ratio with a single well-defined peak. Observations at sites with more than one sharp shear-wave velocity contrast and horizontally arranged soil layers resulted in at least two well-defined H/V spectral ratio peaks. Furthermore, at sites where there were sharp shear-wave velocity contrasts in nonhorizontal, near-surface soil layers, the H/V spectra exhibited a broad-bandwidth, relatively low amplitude signal instead of a single well-defined peak.

Explore related subjects

Soil Dynamics and Earthquake Engineering Article

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

E. W. Wollery, R. Street. 2002. 3D near-surface soil response from H/V ambient-noise ratios. https://doi.org/10.1016/s0267-7261(02)00109-4

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2024

Improved computational methods for probabilistic liquefaction hazard analysis

Current procedures for analysis of and design against liquefaction hazards focus primarily on the use of probabilistic ground motions at a single ground-shaking hazard level, with the cyclic loading represented by a peak ground acceleration ( PGA ) corresponding to a target return period and a single representative moment magnitude M w . These parameters are typically used in conjunction with deterministic simplified procedures for estimating liquefaction triggering and consequences that largely neglect the considerable uncertainties inherent to liquefaction problems. Motivated by these limitations and the resulting inconsistencies in liquefaction design levels, early methods for probabilistic liquefaction hazard analysis (PLHA) were proposed that incorporate the full ground motion hazard space, integrated with probabilistic liquefaction triggering models. Such methods provide liquefaction factor of safety ( FS L ) hazard curves for standard penetration test (SPT) data. Recognizing the increased use of higher-resolution cone penetrometer test (CPT) data in engineering analysis and design and the potential computational challenges it presents, an expanded suite of probabilistic triggering models, and wider availability of more detailed seismic hazard data, an improved PLHA computational methodology is presented in this study. The methods described utilize the U.S. Geological Survey National Seismic Hazard Model directly through web services to obtain PGA hazard and disaggregation calculations for any site and average shear wave velocity in the upper 30 m of the site ( V s 30 ) in the conterminous United States, to reconstruct the PGA hazard space for use in PLHA calculations, and to employ array calculations for efficient liquefaction hazard curve estimates for the thousands of CPT measurements in a given profile. The framework presented here is modular in nature, and discussion on the use of alternative models and extension to probabilistic liquefaction consequence evaluation is presented. The importance of appropriate representation of probabilistic liquefaction model uncertainties is also highlighted, along with the impacts of different levels of uncertainty on the PLHA calculation. Finally, a potential roadmap for incorporation of the PLHA framework in seismic provisions is presented, with an illustration of how it can address current limitations and impacts in liquefaction hazard analysis and design.

Soil Dynamics and Earthquake Engineering↗

USGS2024

Application of non-stationary shear-wave velocity randomization approach to predict 1D seismic site response and its variability at two downhole array recordings

Accounting for uncertainties in seismic site response is crucial to improving the performance of one-dimensional (1D) ground response analyses (GRAs) at downhole array recording sites. In addition to site effects, uncertainties in 1D-GRAs can also be contributed from the seismic source and/or path. Though often representing not more than one percent of the distance (path) from the source, site conditions are known to have an enormous influence on ground shaking. In this study, we focus on the site shear-wave velocity ( V S ) structure, which is the main ingredient for estimating the variability of site response. As such, V S can manifest aleatory uncertainties related to the effects of small-scale spatial heterogeneities within the near surface, thus V S can substantially modify ground shaking during earthquakes. We apply a novel V S randomization approach to propagate the small-scale heterogeneities of V S to estimate seismic site response within a non-stationary probabilistic framework. The randomization approach generates samples of V S profiles that are used to perform several 1D-GRAs and obtain an averaged site response and related variability. The proposed method is implemented on data recorded at two downhole array sites with different subsurface soil conditions: a soft soil site on Treasure Island (California, United States of America) and a rock outcrop site in Cadarache (South-East France). We show that synthetic surface-to-borehole transfer functions from 1D-GRAs provide an acceptable fit to the empirical transfer functions from low-motion earthquake records and succeed in reproducing most of the site-specific seismic response variability. The remaining mismatch between transfer functions is likely due to insufficient precision on the seismic bedrock and the impedance contrast. The variability in site response is discussed with emphasis on the role of V S small-scale heterogeneities, attenuation, and input motion incidence angle in ground motion variability for the site and soil conditions at both locations.

California↗

USGS2021

A generic soil velocity model that accounts for near-surface conditions and deeper geologic structure

Near-surface soil conditions can significantly alter the amplitude and frequency content of incoming ground motions – often with profound consequences for the built environment – and are thus important inputs to any ground-motion prediction. Previous soil-velocity models (SVM) have predicted shear-wave velocity profiles based on the time-averaged shear-wave velocity in the upper 30 m ( V S30 ). This article presents a generic soil-velocity model that accounts both for near-surface conditions ( V S30 ) and deeper geologic structure, as represented to the depth at which the profile reaches a velocity of 1.0 km/s ( Z 1.0 ). To demonstrate the advantages of our new SVM, we apply it to the Cascadia Region of North America, where numerous geologic basins and glaciated landscapes give rise to a wide range of V S30 and Z 1.0 combinations. This soil velocity model yields good estimates of site response across all site conditions, and significantly improves upon a model calibrated using only V S30 data. In conjunction with existing models that describe the deep velocity structure of the region (e.g., (Stephenson et al., 2017) [27]; the proposed model is particularly suited for use in regional-scale predictions of site response, liquefaction, landslides, infrastructure damage, and loss. The proposed methodology is broadly applicable to the development of SVMs elsewhere, and with improved understanding of near-surface and deep velocity structures, can facilitate more accurate ground-motion predictions globally.

Washington↗