Differential Bank Migration Limits the Lifespan and Width of Braided Channel Threads
Bibliographic record
Abstract
Abstract Successful management of flooding and erosion hazards on floodplains depends on our ability to predict a river channel's shape and the lifespan during which it will continue to flow. Recent progress has improved our understanding of what sets the lifespan and width of single‐thread channels; the next challenge is to extend this knowledge to braided channels and their interwoven sub‐channels (threads). In this study, we investigate the lifespan and width of braided channel threads in a large experimental data set, coupled with particle‐image velocimetry‐derived measurements of riverbank erosion and accretion. We find that, unlike single‐thread channels, braided channels in the experiment do not exhibit an equilibrium between bank erosion and accretion. Instead, bank erosion outpaces lateral accretion, causing individual threads to widen and infill until they are abandoned. Thread lifespan is limited to the time it takes for threads to triple their width: tripling of the width yields enough bank material to aggrade more than half the channel depth, at which point flow is rerouted to a narrower thread. In consequence the width of active threads is limited to three times their initial width. Threshold channel theory accurately predicts the median thread width, which is roughly double the initial width and two‐thirds the limiting width. The results are consistent with existing field data and suggest that differential bank migration is sufficient to explain why braided channels show greater width variability and higher width‐to‐depth ratios than their single‐thread counterparts.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".