Mobilization of coarse surface layers in gravel‐bedded rivers by finer gravel bed load
Bibliographic record
Abstract
Additions of sand to gravel beds greatly increase the mobility and flux of gravel. However, it is not known how additions of finer gravel to coarser gravel beds will affect the mobility of bed material. Here we examine the effect of fine gravel pulses on gravel bed material transport and near‐bed flow dynamics in a series of flume experiments. Bed material refers exclusively to sediment in the channel prior to the pulse introduction. The observations indicate that fine sediment pulses tend to migrate downstream in low‐amplitude waves. As the waves pass over the gravel bed, the interstitial pockets in the bed material surface fill and coarse gravel particles are entrained. This increases bed material transport rates and causes a distinct shift from a selective mobility transport regime where particles coarser than the bed material median (8 mm) make up <30% of the load to an equal mobility transport regime where bed materials coarser than 8 mm and finer than 8 mm are transported in equal proportions. The only possible source for this coarser bed load material is the sediment bed, suggesting that portions of the coarse surface layer are being mobilized. Observations of near‐bed velocity and turbulence suggest that fine gravel pulses cause fluid acceleration in the near‐bed region associated with a reduction in the level of turbulence produced at the sediment boundary. This accelerated fluid at the bed increases drag exerted on coarse surface layer particles, promoting their mobilization. Our findings suggest that, in general, finer bed sediment (not just sand) can mobilize coarser sediment and that expressions for the influence of sand on bed mobility need to be generalized on the basis of grain ratios.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".