Channel stability in steep gravel–cobble streams is controlled by the coarse tail of the bed material distribution
Bibliographic record
Abstract
Summary Researchers have associated channel‐forming flows with reach‐average shear stresses close to the entrainment threshold for the surface D50. We conducted experiments using a model of a generic steep, gravel–cobble stream to test this association. Our results suggest that channel‐forming flows fully mobilize the D50, and produce shear stresses close to the entrainment threshold for the largest grains in the bed. The channel dimensions were set by flows capable of mobilizing between 85% and 90% of the bed surface, which produced a brief period of lateral instability lasting about 1 h, followed by a prolonged period of relative stability during which modest adjustments occurred, but during which the reach‐average hydraulics remained about the same. The adjustments during the unstable phase of the experiments are characterized by rapid bank erosion, extensive deposits on the channel bed and a restructuring of the major morphologic elements of the stream. The adjustments during the stable phase of the experiments involved barform migration and bed surface coarsening but did not appreciably modify the physical template established by the end of the unstable phase. The behaviour we observed is not consistent with the concept of a dynamic equilibrium associated with a formative flow that is just capable of entraining the bed surface D50. Instead, it suggests that rapid adjustments occur once a stability threshold is exceeded, which creates a template that constrains channel activity until another event drives the system across the stability threshold, and re‐sets the template. While we believe that it is probably too simplistic to associate a channel‐forming discharge with the entrainment threshold for a single grain size, our results suggest that the D95 is a more logical choice than the D50 © 2020 John Wiley & Sons, Ltd.
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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".