Flows and sediment dynamics in the Ganga River under present and future climate scenarios
Bibliographic record
Abstract
Identification of factors controlling sediment dynamics under natural flow regimes can establish a baseline for quantifying effects of present day hydrological alteration and future climate change on sediment delivery and associated flooding. The process-based INCA-Sediment model was used to simulate Ganga River sediment transport under baseline conditions and to quantify possible future changes using three contrasting climate scenarios. Construction of barrages and canals has significantly altered natural flow regimes, with profound consequences for sediment transport. Projected increases in future monsoonal precipitation will lead to higher peak flows, increasing flood frequency and greater water availability. Increased groundwater recharge during monsoon periods and greater rates of evaporation due to increased temperature complicate projections of water availability in non-monsoon periods. Rainfall and land surface interaction in high-relief areas drive uncertainties in Upper Ganga sediment loads. However, higher monsoonal peak flows will increase erosion and sediment delivery in western and lower reaches.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".