Sediment budget controls on foredune height: Comparing simulation model results with field data
Bibliographic record
Abstract
Abstract The form, height and volume of coastal foredunes reflects the long‐term interaction of a suite of nearshore and aeolian processes that control the amount of sand delivered to the foredune from the beach versus the amount removed or carried inland. In this paper, the morphological evolution of more than six decades is used to inform the development of a simple computer model that simulates foredune growth. The suggestion by others that increased steepness of the seaward slope will retard sediment supply from the beach to the foredune due to development of a flow stagnation zone in front of the foredune, hence limiting foredune growth, was examined. Our long‐term data demonstrate that sediment can be transferred from the beach to the foredune, even with a steep foredune stoss slope, primarily because much of the sediment transfer takes place under oblique rather than onshore winds. During such conditions, the apparent aspect ratio of the dune to the oncoming flow is less steep and conditions are not as favourable for the formation of a stagnation zone. The model shows that the rate of growth in foredune height varies as a function of sediment input from the beach and erosion due to storm events, as expected, but it also demonstrates that the rate of growth in foredune height per unit volume increase will decrease over time, which gives the perception of an equilibrium height having been reached asymptotically. As the foredune grows in size, an increasing volume of sediment is needed to yield a unit increase in height, therefore the apparent growth rate appears to slow. Copyright © 2018 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".