Climate change impact on the hydrological balance of the Itaipu Basin
Bibliographic record
Abstract
Abstract This study aimed at carrying out an assessment of the impact of climate change on water availability for the Itaipu hydrological basin, located on the frontier between Brazil and Paraguay, with particular reference to river runoff and hydropower. Climate data for the SRES future scenario A2 were generated for the Paraná hydrological basin (which includes the Itaipu hydrological basin) and hydrological impacts were studied. Present and future rainfall data were downscaled from the Canadian General Circulation Model (CGCM) for the A2 SRES scenario (periods 2010–2040 and 2070–2100) on a local meteorological network covering the Itaipu hydrologic basin and used as driving parameters for the Sacramento hydrological model to estimate the river runoff. The results of this analysis for the first period have shown an unchanged average annual runoff as the effect of an asymmetric impact on a seasonal scale. Climate change resulted in a higher runoff in summer–spring, whilst runoff in winter–autumn was lower with respect to the baseline. The second period resulted in a general decrease in runoff on both seasonal and annual scales. Possible impacts on hydropower production are discussed. Copyright © 2010 Royal Meteorological Society
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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 | 0.000 | 0.001 |
| 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".