Snow hydrology of a constructed watershed in the Athabasca oil sands region, Alberta, Canada
Bibliographic record
Abstract
Abstract Wetlands are now being integrated into oil sands mining landscape closure design plans. These wetland ecosystems will be constructed within a regional sub‐humid climate where snowfall represents ~25% of annual precipitation. However, few studies focus on the distribution of snow and, hence, the storage of winter precipitation in reclaimed oil sands landscapes. In this study, the distribution, ablation and fate of snowmelt waters are quantified within a constructed watershed in a post‐mining oil sands environment. Basin‐averaged peak SWE was 106 mm, with no significant difference between reclaimed slopes with vegetation and those that were sparsely vegetated or bare. Snow depth was greatest and more variable near the toe of slopes and became progressively shallower towards the crest. Snow ablation started first on the vegetated slope, which also exhibited the maximum observed ablation rates. This enhanced melt was attributed to increased absorption of short‐wave radiation by vegetation stems and branches. Recharge to reclaimed slopes and a constructed aquifer during the snowmelt period was minimal, as the presence of ground frost minimized infiltration. Accordingly, substantial surface run‐off was observed from all reclaimed slopes, despite being designed to reduce run‐off and increase water storage. This could result in increased flashiness of downstream watercourses during the spring freshet that receive run‐off from post‐mining landscapes where large reclaimed slopes are prolific. Run‐off ratios for the reclaimed slopes were between 0.7 and 0.9. Thus, it is essential to consider snow dynamics when designing landscape‐scale constructed ecosystems. This research demonstrates that the snowmelt period hydrology within reclaimed landscapes is fundamentally different from that reported for natural settings and represents one of the first studies on snow dynamics in constructed watershed systems in the post‐mined oil sands landscape. Copyright © 2016 John Wiley & Sons, Ltd.
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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) | 0.001 | 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 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".