Runoff Projection from an Alpine Watershed in Western Canada: Application of a Snowmelt Runoff Model
Bibliographic record
Abstract
The rising global temperature is shifting the runoff patterns of snowmelt-dominated alpine watersheds, resulting in increased cold season flows, earlier spring peak flows, and reduced summer runoff. Projections of future runoff are beneficial in preparing for the anticipated changes in streamflow regimes. This study applied the degree–day Snowmelt Runoff Model (SRM) in combination with the MODIS to remotely sense snow cover observations for modeling the snowmelt runoff response of the Upper Athabasca River Basin in western Canada. After assessing its ability to simulate the observed historical flows, the SRM was applied for projecting future runoff in the basin. The inclusion of a spatial and temporal variation in the degree–day factor (DDF) and separation of the DDF for glaciated and non-glaciated areas were found to be important for improved simulation of varying snow conditions over multiple years. The SRM simulations, driven by an ensemble of six statistically downscaled GCM runs under the RCP8.5 scenario for the future period (2070–2080), show a consistent pattern in projected runoff change, with substantial increases in May runoff, smaller increases over the winter months, and decreased runoff in the summer months (June–August). Despite the SRM’s relative simplicity and requirement of only a few input variables, the model performed well in simulating historical flows, and provides runoff projections consistent with historical trends and previous modeling studies.
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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) | 0.000 | 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".