Analysis of runoff variations in an arid catchment based on multi-model ensemble- a case study in the Tarim River Basin in Central Asia
Bibliographic record
Abstract
Runoff variation is of significant importance to the current and future water availability of a region, particularly in arid regions, and plays a crucial role in economic and social development. The Tarim River Basin, spanning an area of approximately 102 × 104 km2, is the largest inland river basin in China. Due to the basin’s extremely dry climate, water shortage is the most critical natural factor restricting socio-economic development in the region. This study focuses on analyzing the historical and future runoff changes of the four headstreams (the Kaidu, Aksu, Yarkand, and Hotan rivers) in the Tarim River Basin with historical observations and multiple-model projections. The results indicate that the runoff of the Tarim’s four headstreams showed an increasing trend during 1957–2022, with a remarkable increment of 40.70 × 108 m3, or 18% in percentage. Rising temperatures and precipitation are the main reasons for the runoff’s increase. Higher temperature accelerates the melting of glaciers, leading to enhanced recharge of meltwater, while more precipitation also boosts the increase in river runoff. Based on the modelling results from the extended SWAT (Soil and Water Assessment Tool), the runoff in the Kaidu, Aksu, Yarkand, and Hotan rivers will remain at a high level in the near future (−2035), with an average increase of 3.2%–7.55%. In the mid 21st century (2036–2065), the runoff of the Yarkand and Hotan River originated from the Kunlun and Karakoram mountains is expected to continue increasing by around 6.25%–15.2%. Under SSP126, the tipping point of glacier melt runoff in the basin may happen by 2058, while under SSP370 and SSP585 scenarios, it may be around 2080. The timing of peak water aligns with projections in the mountainous Asia, but is later compared to the tropical Andes, Western Canada, and the Swiss Alps, whose peak water has already been reached. The results of this study can provide a scientific basis for the allocation and efficient utilization of water resources in the Tarim River Basin and offer valuable insights into the forthcoming runoff changes in mountainous regions.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".