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Microtremor horizontal-to-vertical spectral ratios (mHVSR) are frequency-dependent ratios of Fourier amplitude spectra of the horizontal to vertical components of a 3-component recording of ambient ground motions from microtremors. Results from mHVSR tests can identify the frequencies associated with site resonances at sites with large impedance contrasts, and hence have potential to provide useful parameters for predicting seismic site response. Site measurements are made by recording ground vibrations either from a temporarily deployed seismometer, typically recording for a relatively short period of time (~1-2 hrs.), or from a permanently-installed broadband seismometer. In this paper, we discuss ongoing work investigating the reliability of low frequency (< ∼0.1 Hz) mHVSR ordinates. Such low frequency ordinates are potentially useful for sites that are known to have deep basins (e.g., LA Basin, Imperial Valley, Great Salt Lake basin), where fundamental frequencies may fall in this range and direct measurements of depth to bedrock are difficult to make. We have found that low-frequency mHVSR ordinates (< ∼0.1-0.2 Hz) are for practical purposes not reliable in most cases, even when measured by high-quality temporary or permanent broadband sensors. In this paper, we discuss sensor drift and its limited impact on the reliability of mHVSR ordinates. We document the low frequency problem for multiple sites, although we do not have a solution as of this writing for how to improve the reliability of low-frequency results.

Distributed acoustic sensing (DAS) is a relatively new technology for recording the propagation of seismic waves, with promising applications in both engineering and geophysics. DAS's ability to simultaneously collect high spatial resolution waveforms over long arrays suggests that it is well-suited for near-surface imaging applications such as 2-D multichannel analysis of surface waves (MASWs), which require, at a minimum, long, linear arrays of single-component receivers. The 2-D MASW method uses a large number of sensor subarrays deployed along a linear alignment to produce 1-D shear-wave velocity (VS) profiles beneath each subarray. The 1-D VS profiles are then combined to form a pseudo-2-D VS image beneath the entire linear alignment that can be used for the purpose of identifying and characterizing lateral variations in subsurface layering. Traditionally, 2-D MASW is conducted using arrays consisting of either 24 or 48 geophones. While additional receivers could easily be incorporated into the testing configuration, it is rare for researchers and practitioners to have access to greater numbers of seismographs and geophones. When a limited number of geophones are available for deployment, there is a need to pre-determine the geophone spacing and subarray length prior to field data acquisition. Studies examining how the choice of subarray geometry impacts the resulting pseudo-2-D VS cross-sections have been largely limited to synthetic data. In response, this study utilizes DAS data to examine the effects of using various subarray lengths by comparing pseudo-2-D VS cross-sections derived from active-source waveforms collected at a well-characterized field site. DAS is particularly useful for 2-D MASW applications because the subarray geometry does not need to be determined prior to field data acquisition. We organize the DAS waveforms into multiple sets of overlapping MASW subarrays of differing lengths, ranging from 11 to 47 m, along the same alignment, allowing for direct comparison of the derived pseudo-2-D VS results at the site. We show that the length of the individual MASW subarrays has a significant effect on the resulting VS cross-sections, including the resolved location of a strong impedance contrasts at our study site, and evaluate the results relative to ground truth from invasive testing. Our results suggest that the choice of subarray length is important and should be carefully chosen to meet project-specific goals. Furthermore, analysts may consider using multiple subarray geometries during the data processing stage, as is made possible by DAS, to properly evaluate the uncertainty of 2-D MASW results. This study demonstrates the potential of using DAS to collect data for 2-D MASW in a manner that is efficient and flexible, and can be easily scaled up for use with very long arrays. [ABSTRACT FROM AUTHOR]

There is a growing need to characterize the engineering material properties of the shallow subsurface in three dimensions for advanced engineering analyses. However, imaging the near-surface in three dimensions at spatial resolutions required for such purposes remains in its infancy and requires further study before it can be adopted into practice. To enable and accelerate research in this area, we present a large subsurface imaging data set acquired using a dense network of three-component (3C) nodal stations acquired in 2019 at the Garner Valley Downhole Array (GVDA) site. Acquisition of this data set involved the deployment of 196 stations positioned on a 14 × 14 grid with a 5 m spacing. The array was used to acquire active-source data generated by a vibroseis truck and an instrumented sledgehammer, and passive-wavefield data containing ambient noise. The active-source acquisition included 66 vibroseis and 209 instrumented sledgehammer source locations. Multiple source impacts were recorded at each source location to enable stacking of the recorded signals. The active-source recordings are provided in terms of both raw, uncorrected units of counts and corrected engineering units of meters per second. For each source impact, the force output from the vibroseis or instrumented sledgehammer was recorded and is provided in both raw counts and engineering units of kilonewtons. The passive-wavefield data include 28 h of ambient noise recorded over two nighttime deployments. The data set is shown to be useful for active-source and passive-wavefield three-dimensional imaging and other subsurface characterization techniques, which include horizontal-to-vertical spectral ratios (HVSRs), multichannel analysis of surface waves (MASW), and microtremor array measurements (MAM). [ABSTRACT FROM AUTHOR]