Morphodynamics of a Width‐Variable Gravel Bed Stream: New Insights on Pool‐Riffle Formation From Physical Experiments
Bibliographic record
Abstract
Field observations, experiments, and numerical simulations suggest that pool‐riffles along gravel bed mountain streams develop due to downstream variations of channel width. Where channels narrow, pools are observed, and at locations of widening, riffles occur. Based on previous work, we hypothesize that the bed profile is coupled to downstream width variations through momentum fluxes imparted to the channel surface, which scale with downstream changes of flow velocity. We address this hypothesis with flume experiments understood through scaling theory. Our experiments produce pool‐riffle like structures across average Shields stresses τ∗ that are a factor 1.5–2 above the threshold mobility condition of the experimental grain size distribution. Local topographic responses are coupled to channel width changes, which drive flows to accelerate or decelerate on average, for narrowing and widening, respectively. We develop theory which explains the topography‐width‐velocity coupling as a ratio of two reinforcing timescales. The first timescale captures the time necessary to do work to the channel bed. The second timescale characterizes the relative time magnitude of momentum transfer from the flowing fluid to the channel bed surface. Riffle‐like structures develop where the work and momentum timescales are relatively large, and pools form where the two timescales are relatively small. We show that this result helps to explain local channel bed slopes along pool‐riffles for five data sets representing experimental, numerical, and natural cases, which span 2 orders of magnitude of reach‐averaged slope. Additional model testing is warranted.
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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 | 0.001 |
| 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".