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Basal Seismicity Forced by Surface-Water Supply on a Stepped-Bed Glacier: Saskatchewan Glacier, Alberta, Canada

2020· article· en· W3093721671 on OpenAlexaboutno aff
Nathan T. Stevens, Collin J. Roland, Dougal Hansen, Emily Schwans, Lucas Zoet

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsInduced seismicityGlacierGeologyGeomorphologySeismologyHydrology (agriculture)Geotechnical engineering

Abstract

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Parameterization of glacier sliding-laws remains a large source of uncertainty in modeling glacier and ice-sheet flow, requiring validation with experimental and observational data. In the case of ice flowing over a till-free, step-shaped bed, theory predicts bed resistance is independent of glacier sliding speed – a “rate neutral” sliding-law (e.g., Iken, 1981). However, experimental simulation of this system resulted in a notable anti-correlation between sliding speeds and bed resistance – a “rate weakening” sliding-law – that may give rise to basal seismicity (Zoet & Iverson, 2016). To investigate this discrepancy, we conducted a seismic field campaign on Saskatchewan Glacier, which is thought to have a stepped bed like those observed in adjacent glacier forefields. The campaign included a dense, 32 seismometer deployment during the middle of the 2019 melt season, complemented by continuous meteorologic, hydrologic, and GPS observations. Visual and automated characterization of collected seismic data indicate abundant seismicity near the glacier’s bed. Basal seismicity clusters down-flow from an active moulin and a crevassed region likely connected to the bed. Rates of basal seismicity show a strong diurnal signal, consistently occurring 0.5-4 hours after peak surface melting and subglacial discharge, and continuous GPS data indicate temporary ice-flow acceleration during at least two diurnal seismic cycles. Spikes in seismic rate are also observed during most rain events with shorter response-times than diurnal cycles. The diurnal basal seismic cycle was interrupted by two periods of relative quiescence. The first lasted six days, initiating as mean air temperatures and peak daily subglacial discharge rose, and concluding after mean air temperatures and peak discharge declined. The second lasted one day following an abrupt drop in air temperature and was concurrent with reduced subglacial discharge. We postulate that rapid surface water delivery to the bed strongly influences basal water pressure near delivery points, triggering bursts of seismicity on parts of Saskatchewan Glacier’s bed. Elevated rates of basal seismicity follow peak hydrologic flux through the subglacial drainage system, indicating that stick-slip motion likely occurs as water pressures fall from a transient. Some seismicity is accompanied by temporary acceleration of the glacier, consistent with results from Zoet & Iverson (2016). The six day period of relative quiescence may reflect reorganization of the subglacial hydrologic system into a more efficient drainage network in seismogenic regions, thus damping water pressure transients. Conversely, the one day quiescent period was likely the result of limited surface-water supply. We propose that temporary transitions from stable to stick-slip sliding occurred when basal water pressure exceed a critical threshold on parts of the bed, as modulated by surface-water supply and subglacial drainage efficiency. Iken, A. (1981). The Effect of the Subglacial Water Pressure on the Sliding of a Glacier in an Idealized Numerical Model. Journal of Glaciology, 27(97). Zoet, L. K., & Iverson, N. R. (2016). Rate-weakening drag during glacier sliding. Journal of Geophysical Research: Earth Surface, 121, 1328–1350. https://doi.org/10.1002/2016JF003909

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.177
Teacher spread0.166 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes1
Has abstractyes

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