Seasonal Subglacial Hydrological Evolution and Impact on Ice Dynamics in a High Arctic Glacier
Bibliographic record
Abstract
An improved understanding of the response of Arctic glaciers to climate change is required in order to provide inputs for models of global sea-level change. Currently, our knowledge of subglacial hydrological processes in polar regions, and how they impact upon patterns of ice dynamics, remains poor. However, recent research has shown that subglacial hydrology is a crucial determinant of ice dynamics and ice profiles in temperate regions - could this also be the case for polythermal ice masses? During summer 2000, intensive field investigations were undertaken at John Evans Glacier, a polythermal valley glacier situated on eastern Ellesmere Island in the Canadian High Arctic, in order to: i) determine the subglacial drainage system structure, and whether it evolves over the course of the melt season; and ii) investigate whether variations in subglacial hydrology affected rates of glacier motion. Known quantities of fluorescent dye were periodically injected into the englacial system via moulins, and dye emergence was detected in a single stream emerging from the base of the glacier at the snout 5 km downstream. In early June, dye return curves were highly dispersed and dye velocities were low (0.14 m/s), implying that inefficient distributed drainage was taking place. By late July, little dispersion of dye was observed, and dye velocities reached 0.69 m/s. These results suggest that the subglacial drainage system evolved over the course of the melt season. Frequent survey measurements made during the season reveal that much of the surface of the lower sector of the glacier was uplifted and experienced highest horizontal velocities during late June. This period of increased motion may be a direct result of large supraglacial inputs entering a still-inefficient distributed subglacial drainage system at this time. We emphasise the importance of understanding these processes further in order to provide realistic data for future models of Arctic glacier response to climate change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 source (direct Gemma or distilled Codex), 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".