Experimental Insights Into the Threshold of Motion in Alluvial Channels: Sediment Supply and Streambed State
Bibliographic record
Abstract
Abstract Flume experiments were conducted to understand the role of episodic sediment supply on the threshold of motion, streambed state, and stability in gravel bed channels. We demonstrate the importance of bed surface evolution on grain entrainment and hence channel stability. The grain‐size distribution (GSD) of the bed surface coarsened quickly under no feed conditions to develop an armored surface. Armor continued to experience particle exchange but remained intact throughout the experiment, and was relatively insensitive to subsequent sediment supply pulses. Bed surface structures (coarse‐grain clusters, stone cells, and imbrication) developed during the experiments and continued to respond dynamically to sediment pulses. Thresholds of motion estimated by various methods increased during the experiment and fluctuated in response to changes in sediment supply, though they were poorly predicted either by surface grain‐size changes or by surface structure. This reinforces the idea that the threshold for motion is not constant in poorly sorted gravel‐bed streams, and it confirms that the critical Shields number in transport models represents a bed state parameter, not a grain mobility number. Changes are controlled by a variety of factors including sediment supply regime, the degree of bed structuring, and the history of bed evolution. Our results highlight the importance of sediment supply regime as a 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".