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Record W4321996377 · doi:10.5194/egusphere-egu23-10266

Are rock glaciers preferential meltwater pathways to alpine aquifers?

2023· preprint· en· W4321996377 on OpenAlexaffabout
Bastien Charonnat, Michel Baraër, Jeffrey M. McKenzie, Eole Valence, Janie Masse-Dufresne

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsMcGill UniversityÉcole de Technologie Supérieure
Fundersnot available
KeywordsGlacierMeltwaterGeologyRock glacierHydrology (agriculture)HydrogeologyGroundwaterClimate changeContext (archaeology)Glacier mass balanceSurface runoffTidewater glacier cycleAquiferTributaryGeomorphologyGeographyOceanographyEcologyPaleontology

Abstract

fetched live from OpenAlex

A limitation in generating reliable projections of the impact of climate change on subarctic glacierized watersheds is a lack of understanding of the involved processes. While glaciers are often the targets of glacierized watershed research, glaciers are only one of the many features controlling headwater hydrology. Recent studies suggest that the contribution and evolution of other hydrological components under climate change conditions, as well as their interactions with groundwater and surface runoff, must be considered to fully predict future climate change impacts. For example, rock glaciers are recognized for their hydrogeological significance, but their hydrologic processes remain understudied. We present a research program focused on a 5 km2 glacier and rock glacier continuum in the upper section of Shar Ta Gà’ (Grizzly Creek) in the Kluane First Nation territory, Yukon, Canada. The continuum is characterized by the absence of an apparent surface hydrology outlet and no substantial groundwater exfiltration has been detected in the Shar Ta Gà’ River situated directly downstream of the rock glacier. Some diffuse groundwater seepages have been mapped but their yield represent a fraction only of the volumes that are expected from the glacier drainage area.We apply a multimethod approach (including geophysics, hydrochemistry, and UAV based surveying) to characterize the hydrological and hydrogeological behavior of the Shar Ta Gà’ rock glacier in a context where drilling is prohibited. Here we present results from a distributed hydrologic monitoring network of extreme precipitation events that occurred between 2018 and 2022. The network records water pressure, electrical conductivity, water temperature, hydrometeorological data and time lapse images. The results depict the rock glacier as a complex, multi-channel, evolutive hydrogeological system that collects water from upstream channels and from a porous surface. The water is distributed among different reservoirs and/or preferential channels. The rock glacier appears being a node in the hydrological and hydrogeological system, collecting the waters from the continuum and allowing their transfer to granular aquifers and possibly fractured aquifers.

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 score0.093
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.092
GPT teacher head0.247
Teacher spread0.155 · 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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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