Non-monotonic changes in Asian Water Towers’ streamflow at increasing warming levels
Bibliographic record
Abstract
Previous projections show consistent increases in river flows of Asian Water Towers under future climate change. Here we find non-monotonic changes in river flows for seven major rivers originating from the Tibetan Plateau at the warming levels of 1.5 °C, 2.0 °C, and 3.0 °C based on an observation-constrained hydrological model. The annual mean streamflow for seven rivers at 1.5 °C warming level decreases by 0.1-3.2% relative to the present-day climate condition, and increases by 1.5-12% at 3.0 °C warming level. The shifting river flows for the Yellow, Yangtze, Brahmaputra, and Ganges are mostly influenced by projected increases in rainfall, but those for the Mekong, Salween, and Indus are dictated by the relative changes in rainfall, snowmelt and glacier melt. Reduced river flows in a moderately warmed climate threaten water security in riparian countries, while elevated flood risks are expected with further temperature increases over the Tibetan Plateau.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".