Blue Nile flow sensitivity to projected climatic change until 2100.
Bibliographic record
Abstract
The sensitivity of Blue Nile flows (which contribute the bulk of the Nile water) to changes in future rainfall during the June-September rainy season based on output from three General Circulation Models (GCMs) was determined up until 2100. The study attempted to quantify uncertainties arising from: (a) use of different GCMs; (b) different greenhouse gas emissions scenarios; and (c) downscaling coarse-scale GCM output to a finer-scale required for hydrological modelling. A multidimensional stochastic rainfall generator was developed to produce high-resolution gridded rainfall data required by the distributed hydrological model (Nile Forecast System). The assessment also incorporated future evapotranspiration changes over the basin, although in a more simplistic way. Two of the GCMs (Canadian Climate Centre's CGCM2 and UK Hadley Centre's HadCM3) led to reductions in future mean flow and Q5 (daily flow exceeded 5% of the time) during the rainy season, whilst use of the third GCM (Max Plank Institute's ECHAM4) led to general increases in future mean flow and Q5. Changes were more pronounced by the 2050s and 2080s.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".