The impact of hydrograph variability and frequency on sediment transport dynamics in a gravel‐bed flume
Bibliographic record
Abstract
Abstract A laboratory study was undertaken to investigate how changes in flow regime and hydrograph shape (number of cycled hydrographs and duration of each hydrograph) together impact bedload transport and resulting bed morphology. Three hydrologic conditions (experiments) representing different levels of urbanization, or analogously different flow regimes, were derived from measured hydrometric field data. Each experiment consisted of a series of hydrographs with equal peak discharge and varying frequency, duration and flashiness. Bedload transport was measured throughout each hydrograph and measurements of bed topography and surface texture were recorded after each hydrograph. The results revealed hysteresis loops in both the total and fractional transport, with more pronounced loops for longer duration hydrographs, corresponding to lower rate of unsteadiness until reaching the peak discharge (pre‐urbanization conditions). Shorter duration hydrographs (urban conditions) displayed more time above critical shear stress thresholds leading to higher bedload transport rates and ultimately to more variable hysteresis patterns. Surface textures from photographic methods revealed surface armoring in all experiments, with larger armor ratios for longer duration hydrographs, speculated to be due to vertical sorting and more time for bed rearrangements to occur. The direction of bed surface adjustment was linked to bedload hysteresis, more precisely with clockwise hysteresis (longer hydrographs) typically resulting in bed coarsening. More frequent and shorter duration hydrographs result in greater relative channel adjustments in slope, topographic variability and surface texture. © 2019 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".