Horizontal-to-vertical spectral ratio variability in the presence of permafrost

Kula, Damian; Olszewska, Dorota; Dobiński, Wojciech; Glazer, Michał

doi:10.1093/gji/ggy118

Cited by 16 publications

(13 citation statements)

References 31 publications

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“…Lastly, arrays of multiple seismic stations could provide insights into the spatial variations of subsurface properties and alterations. Recent studies have demonstrated the opportunities and challenges for passive seismic monitoring of permafrost environments through horizontal‐to‐vertical spectral ratios (Abbott et al, ; Köhler & Weidle, ; Kula et al, ; Overduin et al, ). To date, using ambient noise for seismic interferometry has yet to be fully investigated for spatiotemporal monitoring of permafrost and active‐layer processes.…”

Section: Introductionmentioning

confidence: 99%

Insights Into Permafrost and Seasonal Active‐Layer Dynamics From Ambient Seismic Noise Monitoring

et al. 2019

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Widespread permafrost thaw in response to changing climate conditions has the potential to dramatically impact ecosystems, infrastructure, and the global carbon budget. Ambient seismic noise techniques allow passive subsurface monitoring that could provide new insights into permafrost vulnerability and active-layer processes. Using nearly 2 years of continuous seismic data recorded near Fairbanks, Alaska, we measured relative velocity variations that showed a clear seasonal cycle reflecting active-layer freeze and thaw. Relative to January 2014, velocities increased up to 3% through late spring, decreased to −8% by late August, and then gradually returned to the initial values by the following winter. Velocities responded rapidly (over~2 to 7 days) to discrete hydrologic events and temperature forcing and indicated that spring snowmelt and infiltration events from summer rainfall were particularly influential in propagating thaw across the site. Velocity increases during the fall zero-curtain captured the refreezing process and incremental ice formation. Looking across multiple frequency bands (3-30 Hz), negative relative velocities began at higher frequencies earlier in the summer and then shifted lower when active-layer thaw deepened, suggesting a potential relationship between frequency and thaw depth; however, this response was dependent on interstation distance. Bayesian tomography returned 2-D time-lapse images identifying zones of greatest velocity reduction concentrated in the western side of the array, providing insight into the spatial variability of thaw progression, soil moisture, and drainage. This study demonstrates the potential of passive seismic monitoring as a new tool for studying site-scale active-layer and permafrost thaw processes at high temporal and spatial resolution.Plain Language Summary Seismic vibrations in the ground generated by background sources of noise (vehicle traffic, wind, ocean waves, etc.) occur continuously and provide a way to monitor environmental changes with time. We used 2 years of noise data to study belowground changes in Alaska, where the upper layer of soil freezes and thaws seasonally and deeper soil (permafrost) remains frozen year-round. Warming temperatures may alter the depth of thaw each summer and degrade permafrost, which could significantly impact ecosystems and infrastructure. Our results show a clear seasonal pattern corresponding with the timing of soil freeze/thaw. Vibrations traveled at the fastest speeds during early spring, indicating frozen soil with ice. Speeds became slower following snowmelt and warmer temperatures in late spring and early summer. Strong decreases in seismic-wave speeds corresponded with heavy rains and warm temperatures, suggesting warm water percolating downward through the soil induced more thaw. Speeds gradually increased again through the fall during ice formation. We also mapped where soil changes occurred most strongly and thereby revealed spatial differences in thaw depth and soil moisture across the site. This work dem...

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Section: Introductionmentioning

confidence: 99%

Insights Into Permafrost and Seasonal Active‐Layer Dynamics From Ambient Seismic Noise Monitoring

et al. 2019

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“…Seasonal effects of the permafrost active layer on HVSRs have been reported previously by Abbott et al (2016) and Kula et al (2018). Instead of geophones, Abbott et al (2016) (same experiment as James et al, 2017) used Posthole sensors buried 20 in the active layer since these instruments are less sensitive to tilt.…”

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confidence: 79%

“…Furthermore, the authors observed emerging HVSR peaks between 10 and 30 Hz in summer, which, however, could not be explained by the relative shallow active layer thickness of 68 cm at their study site. Kula et al (2018) described seasonal HVSR variability at a seismic station in southern Svalbard. Since a permanent station was used with 100 Hz sampling, higher frequencies were being resolved than possible at KBS and instrument coupling was not an 25 issues.…”

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confidence: 99%

Potentials and pitfalls of permafrost active layer monitoring using the HVSR method: A case study in Svalbard

Köhler¹,

Weidle²

2018

Preprint

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Abstract. Time-lapse monitoring of the sub-surface using ambient seismic noise is a popular method in environmental seismology. We assess the reliability of the Horizontal-to-Vertical Spectral Ratio (HVSR) method for monitoring seasonal permafrost active layer variability in northwest Svalbard. We observe complex HVSR variability between 1 and 50 Hz in the record of a temporary seismic deployment covering frozen and thawn soil conditions between April and August 2016. While strong variations are due to changing noise conditions, mainly affected by wind speed and degrading coupling of instruments during 5 melt season, a seasonal trend is observed at some stations that has most likely a sub-surface structural cause. A HVSR peak emerges close to the Nyquist frequency (50 Hz) in beginning of June which is then gradually gliding down, reaching frequencies of about 15-25 Hz in the end of August. This observation is consistent with HVSR forward-modeling for a set of structural models that simulate different stages of active layer thawing. Our results reveal a number of potential pitfalls when interpreting HVSRs and suggest a careful analysis of temporal variations since HVSR seasonality is not necessarily related to changes in 10 the sub-surface. We compile a list of recommendations for future experiments, including comments on network layouts suitable for array beamforming and waveform correlation methods that can provide essential information on noise source variability. In addition, we investigate if effects of changing noise sources on HVSRs can be avoided by utilizing a directional, narrow-band (4.5 Hz) repeating seismic tremor which is observed at the permanent seismic broadband station KBS in the study area. A significant change of the radial component HVSR shape during summer months is observed for all tremors. We show that a 15 thawn active layer with very low seismic velocities would affect Rayleigh wave ellipticities in the tremor frequency band.

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“…We use the temporary KBS and BRA arrays to locate tremors which occurred during the deployment period in 2016 by means of frequency-wavenumber analysis (FK; Kvaerna and Ringdal, 1986;Ohrnberger et al, 2004) and the spatial mapping by multi-array beamforming method (SMAB, in the Supplement of Köhler et al, 2016). Figure 1c shows that the tremor source is spatially stationary and very localized at the shoreline in the area of the harbor of Ny-Ålesund.…”

Section: The Tremormentioning

confidence: 99%

Potentials and pitfalls of permafrost active layer monitoring using the HVSR method: a case study in Svalbard

Köhler

Weidle

2019

Earth Surf. Dynam.

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Abstract. Time-lapse monitoring of the subsurface using ambient seismic noise is a popular method in environmental seismology. We assess the reliability of the horizontal-to-vertical spectral ratio (HVSR) method for monitoring seasonal permafrost active layer variability in northwest Svalbard. We observe complex HVSR variability between 1 and 50 Hz in the record of a temporary seismic deployment covering frozen and thawed soil conditions between April and August 2016. While strong variations are due to changing noise conditions, mainly affected by wind speed and degrading coupling of instruments during melt season, a seasonal trend is observed at some stations that has most likely a subsurface structural cause. A HVSR peak emerges close to the Nyquist frequency (50 Hz) in beginning of June which is then gradually gliding down, reaching frequencies of about 15–25 Hz in the end of August. This observation is consistent with HVSR forward modeling for a set of structural models that simulate different stages of active layer thawing. Our results reveal a number of potential pitfalls when interpreting HVSRs and suggest a careful analysis of temporal variations since HVSR seasonality is not necessarily related to changes in the subsurface. In addition, we investigate if effects of changing noise sources on HVSRs can be avoided by utilizing a directional, narrowband (4.5 Hz) repeating seismic tremor which is observed at the permanent seismic broadband station in the study area. A significant change of the radial component HVSR shape during summer months is observed for all tremors. We show that a thawed active layer with very low seismic velocities would affect Rayleigh wave ellipticities in the tremor frequency band. We compile a list of recommendations for future experiments, including comments on network layouts suitable for array beamforming and waveform correlation methods that can provide essential information on noise source variability.

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Horizontal-to-vertical spectral ratio variability in the presence of permafrost

Cited by 16 publications

References 31 publications

Insights Into Permafrost and Seasonal Active‐Layer Dynamics From Ambient Seismic Noise Monitoring

Insights Into Permafrost and Seasonal Active‐Layer Dynamics From Ambient Seismic Noise Monitoring

Potentials and pitfalls of permafrost active layer monitoring using the HVSR method: A case study in Svalbard

Potentials and pitfalls of permafrost active layer monitoring using the HVSR method: a case study in Svalbard

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