Exploring local sediment erosion and deposition patterns around instream boulders: an experimental Investigation - I
Bibliographic record
Abstract
The placement of instream boulders in a rock-ramp arrangement has been commonly used in river and stream habitat restoration projects. However, the presence of these boulders can lead to localized erosion and deposition, which may either support or undermine their intended functions. This study focuses on the specific pattern and depth of localized scour and deposition in the vicinity of the boulders to identify arrangements and bed slopes yield minimal disturbance to local bed and sediment transport rates. Experiments were conducted in an ecohydraulics flume using various boulder arrangements under unsteady flow and three bed slopes. A total of 18 experimental scenarios were completed to examine the local sediment scour and deposition patterns and sediment movement, including seven different boulder arrangements with varying boulder concentrations λ = 0 (no boulder), 2.4%, 3.4%, 4.4%, 5.4%, 6.4%, and 8.3%, each tested on three different bed slopes: 0.5%, 1.0%, and 1.5%. A well-established and widely adopted method Structure-from-Motion (SfM) photogrammetry observation technique was employed to capture and estimate the local bed level changes under different bed slopes and configurations of boulders. The findings of this study suggest that lower boulder concentration and intermediate spacing between boulders result in reduced local scour depth and lowest sediment transport. Empirical relations were proposed for the profiles of streamwise scour depth downstream of a boulder and maximum scour depth, which could be instrumental in making informed decisions before the installation of a rock ramp.
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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 | 0.001 |
| 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".