Subglacial sediment production and snout marginal ice uplift during the late ablation season of a temperate valley glacier
Bibliographic record
Abstract
Abstract Sediment export from glaciated basins involves complex interactions between ice flow, basal erosion and sediment transfer in subglacial and proglacial streams. In particular, we know very little about the processes associated with sediment transfer by subglacial streams. The Haut Glacier d'Arolla (VS, Switzerland) was investigated during the summer melt season of 2015. LiDAR survey revealed positive surface changes in the ablation zone, indicating glacier uplift, at the end of the morning during the period of peak ablation. Instream measures of sediment transport showed that suspended load and bedload responded differently to diurnal flow variability. Suspended load depended on the availability of fine material whereas bedload depended mainly on the competence of the flow. Interpretation of these results allowed development of a conceptual model of subglacial sediment transport dynamics. It is based upon the mechanisms of clogging (deposition) and flushing (transport/erosion) in sub‐glacial channels as forced by diurnal flow variability. Through the melt season, the glacier hydrological response evolves from being buffered by glacier snow cover with a poorly developed subglacial drainage system to being dominated by more rapid ice melt with a more hydraulically efficient subglacial channel system. The resultant changes in the shape of diurnal discharge hydrographs, and notably higher peak flows and lower base flows, causes sediment transport to become discontinuous, with overnight clogging and late morning flushing of subglacial channels. Overnight clogging may be sufficient to reduce subglacial channel size, creating temporarily pressurized flow and lateral transfer of water away from the subglacial channels, leading to the late morning glacier surface uplift. However, without further data, we cannot exclude other hypotheses for the uplift. © 2018 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".