Effects of climate variability and change on surface water storage within the hydroclimatic regime of the Athabasca River, Alberta, Canada
Bibliographic record
Abstract
Warmer air temperatures projected for the mid-21st century under climate change are expected to translate to increased evaporation and a re-distribution of precipitation around the world, including in the mid-latitude, continental Athabasca River region in northern Alberta, Canada. This study examines how these projected changes will affect the water balance of various lake sizes. A thermodynamic lake model, MyLake, is used to determine evaporation over three theoretical lake basins – a shallow lake, representative of perched basins in the Peace-Athabasca Delta near Fort Chipewyan; an intermediate-depth lake representative of industrial water storage near Fort McMurray; and a deep lake representative of future off-stream storage of water by industry, also near Fort McMurray. Bias-corrected climate data from an ensemble of Regional Climate Models are incorporated in MyLake, and the water balance is completed by calculating the change in storage as the difference between precipitation and evaporation. Results indicate that evaporation and precipitation are projected to increase in the future by similar magnitudes, thus not significantly changing the long-term water balance of the lakes. However, intra-annual precipitation and evaporation patterns are projected to shift within the year, changing seasonal water level cycles, and the magnitudes and frequencies of extreme 1-, 3- and 5-day weather events are projected to increase. These results demonstrate that future climate change adaptation and mitigation strategies should take into account increases in intra-annual variability and extreme events on water levels of lakes in mid-latitude, interior hydroclimatic regimes.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".