Three-Dimensional Numerical Modeling of Mixing at River Confluences
Bibliographic record
Abstract
Lateral mixing of a pollutant is considered as a slow process that is usually complete within 100–300 river widths. Recent studies on flow dynamics at river confluences revealed that lateral mixing can be markedly enhanced when the tributary channel is shallower than the main channel. This study uses a three-dimensional model to examine mixing processes immediately downstream of confluences as well as further downstream in the mainstream. Simulations are presented for a concordant and discordant laboratory junction and a field confluence for a low and a high flow condition. The decrease in standard deviation at a cross section of a tracer over a distance of 5 channel widths is 30% for discordant beds but only 10% for concordant beds in the laboratory simulation. At the natural site, bed discordance is more important at the low flow than at the high flow with corresponding decreases in the standard deviation of 31 and 18% over 3.5 channel widths. Mixing is completed after a distance of 25 and 37 channel widths for the low and high flow conditions, respectively. Further downstream, mixing is mainly affected by planform curvature of the channel.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".