Gravel-bed river morphodynamic processes throughout a large flood with an 80-year return period from numerical modeling: Implications for flood regulation strategies
Bibliographic record
Abstract
Due in part to the lack of continuous-in-space-and-time flow and sediment transport data, the river morphodynamic processes during large floods are not fully understood. This study developed a two-dimensional (2-D) morphodynamic model to study the morphodynamic process of a gravel-bed river during a flood event with a return period of 80 years in Calgary, Canada. The model was calibrated against post-flood velocimetry data and post-flood bathymetry data. Temporal and spatial distributions of flow velocity, bedload transport rate, surface sediment sizes, and cumulative morphological changes throughout the flood are presented and analyzed. The results show that the timings of morphological changes during the flood differ for different morphodynamic units (MUs). It is demonstrated that, with the same flood peak and duration, a regulated flood event with a brief rising period, rather than a long-lasting rising period, might result in less bank erosion and bar growth. We also found that bedload transport rates are more sensitive to flow velocities than bed sediment sizes in the Bow River case, due to the greater spatial and temporal variance of velocities during the flood.
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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) | 0.000 | 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 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".