Dune geometry and the associated hydraulic roughness at the transition from a fluvial to tidal regime at low river discharge
Bibliographic record
Abstract
In deltas and estuaries throughout the world, a fluvial-to-tidal transition zone (FTTZ) exists where both the river discharge and the tidal motion drive the flow. It is unclear how bedform characteristics are impacted by changes in tidal flow strength, and how this is reflected in the hydraulic roughness. To understand bedform geometry and variability in the FTTZ and possible impacts on hydraulic roughness, we assess dune variability from multibeam bathymetric surveys, and we use a calibrated 2D hydrodynamic model (Delft3D-FM) of a sand-bedded lowland river (Fraser River, Canada). We focus on a period of low river discharge during which tidal impact is strong. We find that the fluvial-tidal to tidal regime change is not directly reflected in dune height, but local patterns of increasing and decreasing dune height are present. The calibrated model is able to predict local patterns of dune heights using tidally-averaged values of bed shear stress. However, the spatially variable dune morphology hampers local dune height predictions. The fluvial-to-tidal regime change is reflected in dune shape, where dunes have lower leeside angles and are more symmetrical in the tidal regime. Those tidal effects do not significantly impact the reach-scale roughness, and predicted dune roughness using dune height and length is similar to the dune roughness inferred from model calibration. Hydraulic model performance with a calibrated, constant roughness is not improved by implementing dune-derived bed roughness. Instead, large-scale river morphology may explain differences in model roughness and corresponding estimates from dune predictors.
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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 | 0.000 |
| 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".