The summer hydrology of a small upland tundra thaw lake: implications to lake drainage
Bibliographic record
Abstract
Abstract The phenomenon of thaw lake disappearance through rapid drainage has been identified as a potential issue for many circumpolar Arctic regions. These drainage events and the associated flood waves pose a considerable danger to human and animal habitat especially in lake‐rich Arctic regions. The significance of this phenomenon is further heightened by the recent increase in human activity in Arctic regions, such as resource exploration, as well as the projected changes in climatic conditions for Arctic regions. This study is aimed at providing improved understanding of the hydrology of upland tundra thaw lakes, a type of lake that is prone to rapid drainage, by using a combination of observed and modelled data to calculate the complete summer lake water balance for a small thaw lake located to the east of the Mackenzie delta in northwestern Canada. The lake level calculation is subsequently extended to provide a 32‐year estimate of lake levels for the study lake. This long‐term dataset is used to detect patterns and trends in peak summer lake levels. Furthermore, it is used together with climate data for the same time period to look at lake levels and climatic conditions at the time of known rapid lake drainage events. The results of the study suggest that while high lake levels are considered to be a contributing factor for rapid lake drainage, climatic conditions such as above‐average summer air temperature and precipitation values also seem to be key factors. These findings are a first step in determining how projected future climate conditions might influence the rate of rapid lake drainages of Arctic tundra thaw lakes. Copyright © 2009 John Wiley & Sons, Ltd and Her Majesty the Queen in right of Canada. The contributions of P. Marsh, C. Onclin and M. Russell belong to the Crown in right of Canada and are reproduced with the permission of Environment Canada.
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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 | 0.000 | 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) | 0.003 | 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".