Feedbacks between sediment input, bed state and threshold for motion in gravel-bed rivers: an experimental study
Bibliographic record
Abstract
In gravel-bed rivers the relation between the magnitude and frequency of sediment input, the threshold for motion and channel stability is still not fully understood. Here we present results from a 280-hour long flume experiment, in which poorly sorted sediment was fed episodically in an 18-m long, 2.2%-steep channel. The experiment included 7 consecutive runs lasting 40 hours each characterized by a constant water discharge but different sediment supply regimes (i.e., with no feed, constant feed and sediment pulses). Several measurements of sediment transport, flow depth and bed structures were taken along the flume, to assess how changes in sediment supply influence particle mobility and channel stability. Our results show that the surface grain‐size distribution coarsened quickly, developing an armored layer that persisted throughout the entire experiment with only short-lived changes after sediment pulses. Grain clusters and other bed structures developed continuously during the experiments, changing dynamically in response to sediment pulses. We estimated the thresholds of motion with three different methods, all of which yielded consistent results. Overall, the threshold for motion increased during the experiment, fluctuating in response to changes in sediment input. Our results provide further evidence to the idea that the threshold for motion in gravel-bed rivers is not a constant, but changes as a state parameter. These changes in our experiments are controlled by (a) the sediment supply regime, (b) the degree of bed structuring, and (c) the history of bed evolution. These outcomes suggest that sediment supply regime is a primary control on bed surface evolution and the channel stabilizing function played by surface structures.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".