SEDIMENT TRANSPORT AND FLOW DYNAMICS AROUND A RESTORED POOL IN A FISH HABITAT REHABILITATION PROJECT: FIELD AND 3D NUMERICAL MODELLING EXPERIMENTS
Bibliographic record
Abstract
ABSTRACT Few studies have examined sediment transport patterns around in‐stream structures used to enhance fish habitat despite the importance of this variable in the successful design of stream restoration schemes. The objective of this study is to examine interactions between the (excavated) pool morphology, flow and sediment transport in a restored reach of the Nicolet River (Quebec, Canada). Bedload transport was investigated using passive integrated transponder (PIT) tagged particles that were followed from positions upstream of a pair of current deflectors which were designed to maintain the excavated pool downstream. Three‐dimensional numerical simulations of the flow field at various flow stages (with emerged or submerged deflectors) were used to relate near‐bed velocity and bed shear stress to transport patterns and to assess the impact of varying the pool location and geometry on the flow field and water surface profiles. Results show that from 2005 to 2008, of the 117 pit‐tagged particles that fell in the pool, only 27 are known to have exited. None of the 30 largest rocks entering the pool escaped. Bed shear stress values simulated at high and peak flow (slightly above bankfull level) are not sufficient to move the largest rocks in the pool exit zone. Simulations also reveal a complex water surface topography when flow is above the height of deflectors, with negative water surface slope in the pool zone. When modifying the pool geometry so that the deepest zones are close to the apex of the in‐stream structures instead of in the centre of the channel, both water surface slope and near‐bed velocity patterns are greatly modified. Understanding the interactions between excavated pools, bedload and 3D velocity patterns around in‐stream structures is essential for long‐term success of fish habitat restoration projects, and using 3D models to test various designs of artificial pools is a promising approach. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".