Hydroclimatic and channel snowpack controls over suspended sediment and grain size transport in a High Arctic catchment
Bibliographic record
Abstract
Abstract Temporal variability in suspended sediment delivery processes was studied during three seasons in a 7·9 km2 catchment at Cape Bounty, Melville Island, Nunavut in the Canadian High Arctic. Discharge was controlled primarily by the magnitude of snowmelt, with limited inputs from ground ice melt and precipitation. Years with greater snowpack non‐linearly increased sediment yield and resulted in seasonal counter‐clockwise hysteresis, while a year with low snowpack resulted in reduced sediment yield and clockwise hysteresis, and indicates that sediment was increasingly available after the onset of streamflow. In addition to the event‐scale hysteresis observed during the nival discharge peak, diurnal clockwise hysteresis was observed during all three seasons and suggests daily exhaustion of sediment supplies. These results indicate that the channel snowpack plays a primary role over sediment accessibility during the nival discharge peak. Similarly, grain size analysis of suspended material in the river showed that the coarsest mean grain size was transported during the early phase of peak nival discharge and indicates that isolated sources of coarse material were being accessed by high velocity flow. Snowpack is present through the peak nival period and conditions sediment availability by isolating channel sediments from high‐energy flow. These results indicate sediment delivery characteristics in small High Arctic catchments reflect complex interactions with channel snowpack and disproportionate responses to flow conditions that differ from glacial and temperate settings. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".