Increasing Drought Risks Over the Past Four Centuries Amidst Projected Flood Intensification in the Kabul River Basin (Afghanistan and Pakistan)—Evidence From Tree Rings
Bibliographic record
Abstract
Abstract Increased flood risks have been projected, but with large uncertainties, in the Kabul River Basin (Afghanistan and Pakistan). To place future changes in a long‐term perspective, we produce a 382‐year precipitation reconstruction for the basin using seven tree‐ring chronologies of old‐growth conifers from the Hindu Kush Mountains, a monsoon‐shadow area. The reconstruction proves robust over rigorous cross‐validations ( R 2 = 0.60, RE = 0.60, CE = 0.53). The full reconstruction (1637–2018) reveals a steady decline in the low end of the precipitation distribution, implying increasing drought risks. We show that droughts are getting more severe, shorter, and more frequent, interspersed with more frequent pluvials in the past century. Drought risks, compounded with projected flood intensification, pose significant threats for this transboundary river. Therefore, future water management needs to account for both flood and drought risks and be informed by long‐term hydroclimatic variability.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".