Past and future variability in the hydrological regime of the Koshi Basin, Nepal
Bibliographic record
Abstract
Planning adaptation strategies in response to climate change (CC) can be a daunting task, especially in regions such as the Koshi Basin in the Himalayas, where CC impacts are still uncertain. This paper recommends targeting adaptation strategies by focusing on changes in variability between the past and future climates at smaller scales. The Soil and Water Assessment Tool (SWAT) and the Indicators of Hydrologic Alteration (IHA) are used for analysis. The results show: (a) higher maximum precipitation during monsoon and post-monsoon, and lower maximum precipitation during winter; (b) increase in precipitation and flows in the Trans-mountain region during all seasons, except for flows during monsoon; (c) increase in post-monsoon precipitation and routed flow volumes; (d) decrease in precipitation during winter and routed flow volumes in all the regions, except the Trans-mountain region; and (e) increase in frequency of high peak flows and decrease in baseflows. Editor Z.W. Kundzewicz Associate editor S. Kanae;
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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 | 0.001 |
| 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 | 0.000 | 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 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".