Meandering Morphodynamics: Insights from Laboratory and Numerical Experiments and Beyond
Bibliographic record
Abstract
This paper, written to mark the 60th anniversary of the Journal of Hydraulic Engineering, focuses on the nature of meandering flow and its coupling to bed and bank deformation. An outline of the present understanding of the kinematics of meandering flow and how the flow shapes the bed, with a view towards the conditions in real alluvial meandering rivers, is presented. The flow and its interaction with the bed are analyzed by treating separately the effects on the flow of channel curvature and streamwise variation of channel curvature and by considering the results of numerous laboratory and numerical experiments carried out to date. The approach is used to explain essential differences in meandering bed topography exhibited by streams with varying values of sinuosity and width-to-depth ratio. The paper is also used as an opportunity to address the question of why, in the absence of geological constraints, some streams tend to remain regular in plan shape (i.e., symmetric in plan view with regard to the axis of bend) even when their loops actively expand laterally, whereas others acquire irregular plan shapes. This question is considered in view of the intrinsically different mechanics of bed deformation and bank erosion and a new experiment on bank erosion. The paper suggests that differences in the erodibility of the bed and banks may be a significant contributing factor to the planimetric fate of the stream.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".