Tidal asymmetry and mud transport in Oualidia Lagoon: Actual conditions in 2012 and rehabilitation scenarios
Bibliographic record
Abstract
Oyster aquaculture in Oualidia Lagoon, Morocco, has suffered from poor water quality and water confinement in its upstream region. Tidal asymmetry (TA) has been suggested as a possible cause, and a sediment trap was dredged in 2011 to mitigate this condition. This study addresses TA in the lagoon using field measurements and numerical modeling in the presence of the sediment trap. Results indicate that the lagoon is flood-dominated mostly in its upstream end, where frictional forces exceed inertia accelerations during the tidal cycle and where fine sediments settle on the tidal flats and inside the sediment trap. However, this study shows that a large mass of suspended sediments is exported to the ocean, which is contrary to expectations in flood-dominated lagoons. Defining the sediment trap as the rehabilitation scenario S1, the impacts of three additional scenarios on TA are examined. These are scenario S2 (dredging the upstream section of the main channel), scenario S3 (dredging the channels surrounding the flood delta near the inlets), and scenario S4 (raising the ocean level by 0.5 m following climate change predictions). Results show that none of these scenarios modify the tidal flood dominance in the lagoon, although scenarios S2 and S4 decrease its intensity in the upstream region. Nevertheless, all scenarios still contribute to a significant export of sediments to the ocean. This suggests that lagoon management activities should not rely on tidal asymmetry analyses that normally predict upstream sediment transport in flood-dominated lagoons.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".