Impacts of boreal hydroelectric reservoirs on seasonal climate and precipitation recycling as simulated by the CRCM5: a case study of the La Grande River watershed, Canada
Bibliographic record
Abstract
Located in northern Quebec, Canada, eight hydroelectric reservoirs of a 9782-km2 maximal area cover 6.4% of the La Grande watershed. This study investigates the changes brought by the impoundment of these reservoirs on seasonal climate and precipitation recycling. Two 30-year climate simulations, corresponding to pre- and post-impoundment conditions, were used. They were generated with the fifth-generation Canadian Regional Climate Model (CRCM5), fully coupled to a 1D lake model (FLake). Seasonal temperatures and annual energy budget were generally well reproduced by the model, except in spring when a cold bias, probably related to the overestimation of snow cover, was seen. The difference in 2-m temperature shows that reservoirs induce localized warming in winter (+0.7 ± 0.02 °C) and cooling in the summer (−0.3 ± 0.02 °C). The available energy at the surface increases throughout the year, mostly due to a decrease in surface albedo. Fall latent and sensible heat fluxes are enhanced due to additional energy storage and availability in summer and spring. The changes in precipitation and runoff are within the model internal variability. At the watershed scale, reservoirs induce an additional evaporation of only 5.9 mm year−1 (2%). We use Brubaker’s precipitation recycling model to estimate how much of the precipitation is recycled within the watershed. In both simulations, the maximal precipitation recycling occurs in July (less than 6%), indicating weak land-atmosphere coupling. Reservoirs do not seem to affect this coupling, as precipitation recycling only decreased by 0.6% in July.
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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 | 0.001 |
| 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".