Effects of climate change on terrestrial water storage and basin discharge in the lancang River Basin
Bibliographic record
Abstract
Lancang River Basin (upper reaches of the Mekong River basin within China). Complex terranes and diverse climates are a bottleneck for understanding the hydrology of rivers originating from the Tibetan Plateau. This study deals with the impact of climate change on water storage in the Lancang River Basin, which is governed by the South Asian monsoon system. We evaluated the spatiotemporal distribution of multi-source precipitation, evapotranspiration, and terrestrial water storage (TWS) to understand the hydrological system in the region. We provide evidence of climate change impacts on TWS and basin discharge over an upstream region of the transboundary river system. The Five Gravity Recovery and Climate Experiment (GRACE) products and Global Land Data Assimilation System (GLDAS) TWS display analogous seasonal distribution, even though the amounts differ between them. The GRACE and GLDAS TWS exhibited a significant negative trend in the basin from 2002 to 2016. However, the Center for Space Research (CSR-M) at the University of Texas and the Jet Propulsion Laboratory (JPL-M) mascon solutions concede more severe and much wider TWS reduction than the three spherical harmonic (SH) solutions. In addition, a downward trend was observed for basin discharge over 15 years as a response to climate change (decreased precipitation and increased evapotranspiration). Furthermore, we identified a 2-month time lag between precipitation and TWS, which could be a response to climatic factors along with aquifer properties in a karst dominated region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".