The Impact of Sediment Deficiency on Riverbed Evolution in Major Mekong Delta Rivers
Bibliographic record
Abstract
The bed change in the Vietnamese Mekong Delta has been increasingly altered caused by natural processes and anthropogenic activities, and it becomes even more complicated under the influence of rising sea levels. At the Tan Chau and Chau Doc stations, the water volume entering the Mekong Delta did not change between 2008 and 2017, but the sediment load decreased by one-third, which caused a significant bed change in the river. This study evaluates riverbed evolution in the Mekong Delta under sediment deficiency and forecasts erosion dynamics until 2030 due to sea-level rise. Results indicate that increased riverbed erosion in 2017 is linked to a 30% drop in sediment supply compared to 2008. Simulations for 2017 indicate a 0.15% decrease in accretion rate—measured as the change in bed elevation—in the upper Tien River compared to 2008, and a 0.5% decrease in the lower reaches. Erosion rates nearly doubled in the upper reaches from Tan Chau to My Thuan, while the lower reaches showed minimal change (0.33%). By 2030, erosion will intensify, especially along the Tien River from Tan Chau to Hong Ngu, reaching 1.6 m/year. Accretion will decrease sharply, with the highest rate at 0.1 m/year near Long Khanh islet.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".