Spatial variation of snowmelt and sublimation in a high‐elevation semi‐desert basin of western Canada
Bibliographic record
Abstract
Abstract The Okanagan Basin, a semi‐desert region of western Canada, is currently experiencing rapidly increasing pressure on its water resources from development and population increases, exacerbated by changes in climate. The major source of freshwater in the region originates from the melt of high‐elevation snowpacks, about which little is currently known, including the proportion of the peak snowpack lost to sublimation. To better understand the hydrologic regime of this snow resource, a detailed field program was conducted during the 2007 snowmelt season. Specifically, peak annual snow distribution, ablation‐season surface‐energy exchange and mass balance were measured in a forested high‐elevation catchment of the Okanagan Basin. During the snowmelt period, 1–4% of the peak annual snow‐water equivalent (SWE) was lost to sublimation in open sites—averaging 0·4 mm d−1. Melt and sublimation rates increased significantly with elevation, and were observed to be higher and more variable in the open sites than under forest canopies. The largest sublimation events (>0·25 mm d−1) were associated with low atmospheric vapour pressure, temperatures below 0 °C, and higher than average wind speeds. Condensation occurred under highly stable conditions in the boundary layer when sensible heat fluxes exceeded net radiative inputs to the snow surface. Melt rates were driven almost entirely by sensible heat fluxes and exceeded 30 mm d−1 during large‐scale advection events. The results from this study will allow water managers to better predict the amount of water available for ecological, agricultural and municipal needs. This work also provides the basis for assessing changes in snow surface energetics due to ongoing salvage cutting in forested areas affected by the current mountain pine‐beetle outbreak. Copyright © 2009 John Wiley & Sons, Ltd and Her Majesty the Queen in right of Canada.
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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 | 0.002 | 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) | 0.001 | 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".