Modelling climate change impacts in the Peace and Athabasca Catchment and delta: II—variations in flow and water levels with varying winter severity
Bibliographic record
Abstract
Abstract As freshwater ice is known to significantly affect flows and water levels within the Peace–Athabasca Delta (PAD), a winter severity sensitivity analysis using a one‐dimensional open channel hydraulic model was performed for four climate scenarios (from mild to severe), and was examined under three differing flow conditions (low, average, and high hydraulic regimes), in an effort to better understand the multiple interactions between ice cover and the hydrodynamic regime of this complex system characterized by overbank flooding and flow reversal episodes. In general, a reduction of winter severity lowered lake levels and river flows. While the winter severity effect is of relatively short duration in the rivers, the subsequent reduction in lake levels extends over the summer months. High river flows predispose flow reversal conditions, and water enters the lakes at the outlet as the water levels in the rivers feeding the PAD increase significantly over a short period of time. This flow reversal effect is suppressed during milder winters. Numerical modelling results indicate that extending the ice‐cover season (severe winter) by 14 days resulted in an increase of up to 5 cm in water level of large lakes in the PAD, while reducing it by 28 days lowered the levels by almost 10 cm. Short‐term variations in river levels reached up to 1·5 m as a result of varying the extent of the ice‐cover season. As the simulation runs did not consider ice‐jam events and neglected the effect of ice thickness on water levels, the reported quantitative results must be interpreted with prudence. Copyright © 2006 Crown in the right of Canada, and 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".