Experimental investigation of flood energy reduction through vegetation at various angles
Bibliographic record
Abstract
Abstract The efficiency of flow energy reduction past emergent vegetation has been typically studied assuming a right angle of the vegetated corridor to the flow direction. However, in many real‐world cases the riparian zones of natural, restored, or engineered rivers and waterways, are found at an oblique angle to the flood flow direction. In the current study, the effect of vegetation angle with respect to the flow direction is investigated experimentally in an open channel rectangular flume. The experiments are conducted under a range of subcritical steady flow conditions, with varying Froude number (Fro). The vegetation cover is placed at various angles to the flow direction (90°, 45°, and 30°), for a sparse and intermediate vegetation density, defined from the ratio of spacing of each vegetation element in the cross stream direction (B), and the diameter of vegetation element (d) (B/d = 2.13 and 1.09, respectively). Detailed water surface profiles are obtained for all those cases, demonstrating a considerable backwater rise, increasing with increasing vegetation density, Froude number, and flow approach angle. The energy reduction decreased by increasing the Froude number for the perpendicular (90°) and increased for oblique vegetation (45° and 30°). For the perpendicular vegetation, the average energy reduction rate for sparse (90VS) and intermediate (90VI) vegetation densities are 25.44% and 31.44%, respectively. The range of average energy reduction for sparse vegetation at 45° (45VS) and at 30° (30VS) are 18.3–19.8% and 18.7–19.7%, respectively. Similarly, range of average energy reduction for intermediate vegetation at 45° (45VI) and at 30° (30VI) are 21.4–22% and 18.8–22%, respectively.
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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 | 0.000 |
| 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) | 0.001 | 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".