Progress in permafrost hydrology in the new millennium
Bibliographic record
Abstract
Abstract Increased attention directed at the permafrost region has been prompted by resource development and climate change. This review surveys advances in permafrost hydrology since 2000. Data shortage and data quality remain serious concerns. Yet, there has been much progress in understanding fundamental hydrologic processes operating in a wide range of environments, from steep mountainous catchments, to the Precambrian Shield with moderate relief, to the low‐gradient terrain of plains, plateaus and wetlands. Much of the recent research has focused on surface water, although springs and groundwater contribution to streamflow have also been studied. A compendium of water‐balance research from 39 high‐latitude catchments reveals the strengths and limitations of the available results, most of which are restricted to only a few years of study at the small watershed scale. The response of streamflow to climate receives continued if not increasing attention, from the occurrence of extreme hydrologic events to the changing regimes of river flow at a regional scale. The effect of climate change and the role of permafrost on the changing discharge of large boreal rivers are major topics for further investigation. Extended field and modelling research on physical processes will improve knowledge of permafrost hydrology and enhance its relevance to societal needs. 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".