Hydrological and sediment yield response to summer rainfall in a small high Arctic watershed
Bibliographic record
Abstract
Abstract In cold regions, the response and related antecedent mechanisms that produce flood flows from rainfall events have received limited study. In 2007, a small watershed at Cape Bounty, Melville Island, Nunavut, was studied in detail during the melt season. Two rainfall events on June 30 and July 22, totalling 9·2 and 10·8 mm, respectively, represented significant contributions to seasonal discharge and sediment transport in a year with a low winter snowpack. The precipitation events elevated discharge and suspended sediment concentrations to twice the magnitude of the nival melt, and generated the only measurable downstream lacustrine turbidity current of the season. In two days, rainfall runoff transported 35% of the seasonal suspended sediment load, in contrast to 29% transported over the nival freshet. The magnitude and intensity of the rain events were not unusual in this setting, but the rainfall response was substantial in comparison with equivalent past events. Exceptional temperatures of July 2007 generated early, deep permafrost thaw, and ground ice melt. The resultant increase in soil moisture amplified the subsequent rainfall runoff and sediment transport response. These results demonstrate the importance of antecedent moisture conditions and the role of permafrost active layer development as an important factor in the rainfall runoff and sediment transport response to precipitation events. Copyright © 2009 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 | 0.000 |
| 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) | 0.001 | 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".