DOI 10.1007/s11269-009-9500-8 Behaviour and Performance of a Water Resource System in Québec (Canada) Under Adapted Operating Policies in a Climate Change Context
Bibliographic record
Abstract
Abstract The behaviour of the water resource system of the Peribonka River (Quebec, Canada) exploited for hydropower is evaluated under various hydrological regimes, using different climate change scenarios. The hydrological regime of the recent past and the regimes of 30 climate projections are considered. The potential hydrological regimes are simulated for climate projections from five general circula-tion models (GCM) for two greenhouse gas emission scenarios and three temporal horizons (2020, 2050 and 2080). For each hydrological regime, weekly reservoir operating rules are calculated with a dynamic and stochastic optimization model. Simulations of the water resource system with adapted operating rules in these climate change contexts are compared with the management of the water resource system at the control period (1961–1990). For the majority of climate projections, the analysis of simulations in the context of climate change shows an increase in hydropower and in annual unproductive spills. These increases reach 22 % and 300%, respectively, compared to the control period. Also, the reliability of a reservoir is compromised for half of the climate projections, with annual probabilities reaching above the maximum operating levels, up to 0.3%, whereas these probabilities were null for the control period. Despite the rise in production, the annual efficiency of the
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.692 | 0.455 |
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".