A global portrait of hydrological changes at the 2050 horizon for the province of Québec
Bibliographic record
Abstract
This paper presents the methodology and results of a vast study on climate change impacts on hydrology for the province of Québec for the 2050 horizon. A climate ensemble was first built with simulations from the World Climate Research Programme (WCRP)'s Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset, the North American Regional Climate Change Assessment Program (NARCCAP) and the Canadian Regional Climate Model (CRCM) operational runs. Direct outputs and post-processed data from the climate simulations were used as input to the calibrated HSAMI hydrological model in order to produce a large ensemble of hydrological projections for 305 Québec watersheds. Simulations results indicate that increases in mean annual streamflow are projected for the whole province, with greater changes (up to 14%) in the north. The intra-annual distribution of streamflow also changes, with higher winter flows and lower summer flows as well as apparently earlier spring floods. The maximum height of the snow cover and the number of days with snow on the ground are likely to diminish for the 2050 horizon for the southern half of the province, while the northern half will see more snow, but a shorter snow season as well.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".