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

Köhler, Andreas; Weidle, Christian

doi:10.5194/esurf-2018-52

Cited by 7 publications

(7 citation statements)

References 19 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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“…Due to this sensitivity, seismic methods, including both active and passive, can be utilized to characterize and monitor subsurface permafrost systems; prior studies have leveraged coda wave interferometry techniques to track subtle daily, monthly, and seasonal changes in seismic velocity ( δv / v ) in such environments (James et al., 2017, 2021; Lindner et al., 2021; Steinmann et al., 2021). Horizontal‐to‐vertical spectral ratio (HVSR) methods, which connect time variations of the dominant (resonance) frequency with seasonal subsurface changes above and/or within permafrost, have also been explored (Köhler & Weidle, 2019; Kula et al., 2018). Compared with active seismic monitoring (Kasahara et al., 2010; Stemland et al., 2021), however, these ambient noise based (passive) seismic methods sometimes suffer from biased signal retrieval from non‐uniform noise source distribution (Harmon et al., 2010; Lin et al., 2008) and limited spatial resolution in the case of sparse networks often used in passive studies (Clarke et al., 2011; Ratdomopurbo & Poupinet, 1995).…”

Section: Introductionmentioning

confidence: 99%

Watching the Cryosphere Thaw: Seismic Monitoring of Permafrost Degradation Using Distributed Acoustic Sensing During a Controlled Heating Experiment

Cheng

Lindsey²,

Sobolevskaia

et al. 2022

Geophysical Research Letters

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Permafrost, soil or rock material that has remained at or below 0°C for 2 or more years (Muller, 1945), underlies approximately 22% of the exposed land in the Northern Hemisphere (Obu et al., 2019). With changing climate conditions and rising global temperatures, widespread permafrost thaw and active-layer (the seasonally freezing and thawing layer of soil) thickening are occurring across polar regions (

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“…Unfortunately, the H/V analysis over time is still not carried out routinely and is performed only in a few and peculiar cases. For example, temporal variations of the H/V ratios have been investigated for monitoring the permafrost active layer seasonal variability (Köhler & Weidle, 2019; Kula et al., 2018) and for monitoring the rock masses stability (Colombero et al., 2018). Lotti et al.…”

Section: Introductionmentioning

confidence: 99%

Peak Frequency Changes From HV Spectral Ratios in Central Italy: Effects of Strong Motions and Seasonality Over 12 Years of Observations

et al. 2022

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We analyzed 12 years of continuous seismic data acquired by two seismic stations in Central Apennines (Italy) with the aim to investigate the temporal variations of H/V spectral ratios. The two stations are located in the epicentral areas of the main strong motion earthquakes occurred in Central Italy in the last 12 years (L’Aquila 06 April 2009, Mw 6.1; Amatrice 24 August 2016, Mw 6.0; Visso 26 October 2016, Mw 5.9, and Norcia 30 October 2016, Mw 6.5). H/V ratios are computed both on continuous and earthquakes data recorded by the two stations. H/V ratios are subjected to abrupt changes after strong earthquakes. The results highlight that after strong shaking, there are remarkable drops of the peak frequencies (7%–10% of reduction). After this sudden decrease, the peak frequency slowly recovers to the initial value in a time ranging from a few months to a few years. We also observe a moderate frequency variation (of order of 2%–3%) linked to seasonal variations: the peak frequencies increase in the spring‐summer months and decrease during the winter. The frequency changes after strong earthquakes have been interpreted in terms of velocity variations of the shallow layers. This effect must be taken into account for microzonation, geophysical, and engineering studies that are often carried out in the epicentral areas after strong earthquakes. H/V analysis over time proved to be a useful procedure for highlighting temporal changes relating to the properties of shallow layers of the propagation medium and could provide relevant information for the site characterization of permanent seismic stations.

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

Cited by 7 publications

References 19 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

Watching the Cryosphere Thaw: Seismic Monitoring of Permafrost Degradation Using Distributed Acoustic Sensing During a Controlled Heating Experiment

Peak Frequency Changes From HV Spectral Ratios in Central Italy: Effects of Strong Motions and Seasonality Over 12 Years of Observations

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