Tidal plume fronts, internal waves and sediment resuspension in a near field river plume
Bibliographic record
Abstract
Internal waves are known to be an important source of mixing in the coastal ocean. Measurements from the Columbia River Plume were some of the first to demonstrate the generation of large amplitude internal waves released by a newly formed tidal plume front. Here we explore internal waves generated by multiple tidal plume fronts and their trapping in the mid-field plume of the Rhine river plume. The internal waves are released into a shallow frictional system, and their role on mixing, near shore sediment resuspension is examined. We use data collected off the Dutch coast near the Sand Engine, during the STRAINS field campaigns at a location 10 km north of the river mouth. An ADCP measured current velocity with a frequency of 1 Hz and a resolution of 0.25 m. Temperature, salinity, velocity, sediment concentration measurements, as well as turbulent stresses were measured at the 12 m site at 0.25, 0.5 and 0.75 m above the bed. The field-data and radar images show tidal plume fronts propagating towards the Dutch coast and the generation of high frequency internal waves ahead of the fronts. As the fronts propagate onshore they increase turbulence and mixing and can also increase sediment resuspension. Using an idealised non-hydrostatic model we show that the fronts can generate high frequency internal waves as they propagate towards the coast, and that these waves can break inshore. We introduce a frontal sediment pumping mechanism, and show how this is a new mechanism for sediment resuspension and offshore transport.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".