Shear wave velocity versus quality factor: results from seismic noise recordings

Boxberger, Tobias; Pilz, Marco; Parolai, Stefano

doi:10.1093/gji/ggx161

Cited by 5 publications

(3 citation statements)

References 48 publications

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“…The best fit combinations (i.e., parameters yielding the smallest deviations and spectral shapes of combined water level and bedload models for multiple seismic stations and time slices of environmental conditions) for the unknown parameters were ground quality factor q 0 = 11 and Rayleigh wave phase velocity v 0 = 700 m/s. These results are in the range of expected values (e.g., Boxberger et al, 2017) for the sand‐ to cobble‐till deposits and finer alluvial sediment present in the study area. The variation exponent of Rayleigh wave velocities p 0 was 0.79, and Greens function displacement amplitude coefficients, n 0 a = 0.6 and n 0 b = 0.8 (Figure 2b).…”

Section: Resultssupporting

confidence: 87%

Seismic Monitoring of a Subarctic River: Seasonal Variations in Hydraulics, Sediment Transport, and Ice Dynamics

et al. 2020

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High-latitude rivers are commonly covered by ice for up to one third of the year. Our understanding of the effects of ice on channel morphodynamics and bedload transport is hindered by the difficulties of sensing through the ice and dangers of field work on thin ice or during ice break-up. To avoid this drawback, we used seismic signals to interpret processes and quantify water and sediment fluxes. Our objective was to determine seasonal differences in hydraulics and bedload sediment transport under ice-covered versus open-channel flow conditions using a small seismic network and to provide a first-order estimation of sediment flux in a Fennoscandian river. Our study reach was on a straight, low-gradient section of the Sävar River in northern Sweden. Interpretations of seismic signals, from a station 40 m away from the river, and inverted physical models of river stage and bedload flux indicate clear seasonal differences between ice-covered and open-channel flow conditions. Diurnal cycles in seismic signals reflecting turbulence and sediment transport are evident directly after ice break-up. Analysis of seismic signals of ice-cracking support our visual interpretation of ice break-up timing and the main ice break-up mechanism as thermal rather than mechanical. Assuming the bulk of sediment moves during ice break-up and the snowmelt flood, we calculate a minimum annual sediment flux of 56.2 ± 0.7 t/km 2 , which drastically reduces the uncertainty from previous estimates (0-50 t/km 2) that exclude ice-covered or ice break-up periods. Plain Language Summary With changing ice dynamics under climate change, we must understand how river dynamics including sediment flux differ under ice-covered versus open-channel flow conditions and during ice break-up. However, it is nearly impossible to study sediment transport using common techniques, as we cannot see geomorphic processes below the ice. Field measurements are dangerous to carry out on unstable ice and during ice-break up, which may be the most dynamic period for sediment transport and bank erosion. To overcome this problem, we employed a relatively new approach of environmental seismology to collect continuous data on instream processes. We measured ice dynamics and break-up along the Sävar River in northern Sweden and found distinct differences in water flow patterns and sediment transport between ice-covered and open-channel flow conditions. Seismic signals of ice cracking agree with visual observations that ice break-up was due to ice slowly melting instead of more sudden mechanical fracturing. We also calculated a minimum annual sediment flux of~55 t/km 2-one of the first for this region and for ice-covered rivers-that is much more precise than previous estimates (0-50 t/km 2) without ice-covered or ice break-up periods.

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Section: Resultssupporting

confidence: 87%

Seismic Monitoring of a Subarctic River: Seasonal Variations in Hydraulics, Sediment Transport, and Ice Dynamics

et al. 2020

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“…In addition, the idea to derive both velocity and attenuation model of the Ischia island by a single analysis is based on a recent study by Boxberger et al (2017), who presented a method for calculating the effective attenuation structure at a site by adding a few and successive calculation steps to the SPAC description. Still, the anelasticity of a volcanic medium causes considerable wave-energy loss during propagation due to seismic scattering and absorption.…”

Section: Introductionmentioning

confidence: 99%

“…Generally, the effective attenuation Q eff can be thought of as the sum of these two components: Q eff -1 =Q int -1 +Q scatt -1 . Therefore, even if the attenuation below a site could be considered as an independent parameter from the velocity structure, both parameters can be obtained by a single analysis (Boxberger et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Shear wave velocity and attenuation structure of Ischia island using broad band seismic noise records

Nardone

Manzo²,

Galluzzo

et al. 2020

Journal of Volcanology and Geothermal Research

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In volcanic areas, accurate localization of earthquakes requires detailed velocity and, possibly, attenuation models, taking into account wide lithological variability and high geothermal gradients. Ischia island (Campania region, Italy) is a seismically-active volcano recently affected by a Mw 3.9 event (Casamicciola, August 21, 2017, 1 km depth). Due to the lack of a specific velocity model, the earthquakes occurred on the island were localized using the one developed for the nearby Campi Flegrei caldera. The aim of this work is the definition of a mean representative 1D shear-wave velocity (Vs) and attenuation (Q) model of the shallower crust (up to 2 km depth) of Ischia. Seismic noise array and spectral ratios techniques were applied to broad band seismic signals recorded by temporary and permanent networks updated after the August 2017 earthquake. The values of both shear-wave velocity (Vs) and quality factor (Q) are realistic, with Q values comparable with those obtained for Campi Flegrei and Stromboli volcanic areas. By taking into account stratigraphic information from deep wells and ultrasonic measurements of velocity on granite and trachytic lava samples, a geological interpretation of the resulting velocity model is provided. Such a model can have significant implications for understanding the dynamics of a volcano, mainly those leading to seismic activity.

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A review of near-surface QS estimation methods using active and passive sources

et al. 2022

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Seismic attenuation and the associated quality factor (Q) have long been studied in various sub-disciplines of seismology, ranging from observational and engineering seismology to near-surface geophysics and soil/rock dynamics with particular emphasis on geotechnical earthquake engineering and engineering seismology. Within the broader framework of seismic site characterization, various experimental techniques have been adopted over the years to measure the near-surface shear-wave quality factor (QS). Common methods include active- and passive-source recording techniques performed at the free surface of soil deposits and within boreholes, as well as laboratory tests. This paper intends to provide an in-depth review of what Q is and, in particular, how QS is estimated in the current practice. After motivating the importance of this parameter in seismology, we proceed by recalling various theoretical definitions of Q and its measurement through laboratory tests, considering various deformation modes, most notably QP and QS. We next provide a review of the literature on QS estimation methods that use data from surface and borehole sensor recordings. We distinguish between active- and passive-source approaches, along with their pros and cons, as well as the state-of-the-practice and state-of-the-art. Finally, we summarize the phenomena associated with the high-frequency shear-wave attenuation factor (kappa) and its relation to Q, as well as other lesser-known attenuation parameters.

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Shear wave velocity versus quality factor: results from seismic noise recordings

Cited by 5 publications

References 48 publications

Seismic Monitoring of a Subarctic River: Seasonal Variations in Hydraulics, Sediment Transport, and Ice Dynamics

Seismic Monitoring of a Subarctic River: Seasonal Variations in Hydraulics, Sediment Transport, and Ice Dynamics

Shear wave velocity and attenuation structure of Ischia island using broad band seismic noise records

A review of near-surface QS estimation methods using active and passive sources

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