Prévision par modélisation numérique de la zone de risque bordant un tronçon de rivière subissant une crue exceptionnelle
Bibliographic record
Abstract
The direct impacts of floods are often considered as limited to the maximum downstream area exposed to the flooding. Considering the size of exceptional floods, the river bed could undergo deep changes. Pairing the GSTARS sediment transport model to a slope stability model (modified Bishop method) that we developed, this paper presents a methodology leading to the definition of a true safety zone along the shores as it takes into account the risk of floods and soil movements: each section of this river undergoes changes due to sediment-fluvial hydraulics ( erosion-deposit) and then eventual landslides modify the profiles. To analyze this, we had first to determine the hydraulic and geotechnical characteristics then use them to test the slope stability of the various legs of the watercourse before and during flooding. The application of this method to a tributary of the Saguenay River for the 1996 "downpour" shows a very good correlation of results with those collected in situ. The method can be directly applied to define the anticipated evacuation zone in case of dam failure.Key words: flooding, evacuation zone, numerical simulations, slope stability, transportation of solids.[Journal Translation]
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".