Modelling Climate Change Impacts on Spring Runoff for the Rocky Mountains of Montana and Alberta II: Runoff Change Projections using Future Scenarios
Bibliographic record
Abstract
In Part I of this two-part study, the Simulated Grid microclimate model (SIMGRID) was modified and the new version validated on the St. Mary River watershed in northern Montana, using historical data. In Part II, future climate change scenarios are used to estimate spring streamflow (QS) for the 1961–2099 period. Relative to the base period (1961–1990), the model indicates median year QS decline of 3 – 8% by the 2020s, 8 – 17% by the 2050s, and 15 – 27% by the 2080s. Mean onset of the spring pulse is projected to occur in early March or late February for the 2080s, 36 to 50 days earlier than for the 1961–1990 reference period. Model results generally indicate increased precipitation, but spring runoff volumes will decrease substantially, because the higher rain:snow ratio and shorter accumulation period will decrease snowpack volume. Overall, the results of this study indicate that the increased winter temperature resulting from anthropogenically-induced climate change, will result in shorter winters, reduced snowpack volume, and earlier spring snowmelt and runoff onset, resulting in substantial reductions in spring discharge.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".