Influence of headwater reservoirs on climate change impacts and flood frequency in the Kabul River Basin
Bibliographic record
Abstract
Although climate change impacts vary globally, for the Kabul River Basin (KRB), concerns are primarily associated with frequent flooding. This research describes the influence of headwater reservoirs on projections of climate change impacts and flood frequency, and how riparian countries can benefit from storing of floodwaters for use during dry seasons. Six climate change scenarios and two Representative Concentration Pathways (RCPs) are used in three periods of a quarter-century each. The Soil and Water Assessment Tool (SWAT) is used to assess how the proposed reservoirs will reduce flooding by ∼38% during the wet season, reduce the flood frequency from five to 25 years return period, and increase low flows by ∼110% during the dry season, which reflect an ∼17.5% reduction in the glacier-covered area by the end of the century. The risks and benefits of reservoirs are highlighted in light of the developmental goals of Afghanistan and Pakistan.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".