Sediment transport and morphological changes in the Ha! Ha! River induced by the flood event of July 1996
Bibliographic record
Abstract
In July 1996, heavy torrential rainfalls caused catastrophic flooding along rivers of the Saguenay region of Quebec. On Lake Ha! Ha!, the flood lead to overtopping and failure of an earth dyke. The drainage of Ha!Ha! Lake produced discharges of 1000 m3/s, 8 times the 100-year flood. From the lake to the river mouth, a 35.7 km reach of the Ha! Ha! River bed was dramatically modified during the 48 hours flood. The geomorphic effects of the flooding ranged from erosion, locally up to 280 m of channel widening, to channel aggradation, locally up to several meters. The goal of the present study is to simulate morphological changes of the Ha! Ha! River associated with the flood event of July 1996. One Dimensional (1-D) model was selected and tested. A cross-comparison of the numerical results and field observations should allow some validation of the system of equations and hypothesis of the model used. / Les pluies des 19 et 20 juillet 1996 constituent, selon Environnement Canada, l`événement météorologique le plus important en intensité et en superficie répertorié au Québec depuis près d`un siècle. En effet, entre 150 et 280 mm de pluie sont tombés, sur une période de 48 h, sur un territoire de plusieurs milliers de kilomètres carrés, provoquant entre autres la rupture d`une digue du lac Ha !Ha !. Le drainage du lac a produit un débit de pointe de l`ordre de 1000 m3/s, 8 fois plus grand que le débit centennal. La montée des eaux dans la rivière Ha !Ha ! sous l`effet de cette rupture de digue a engendré des modifications morphologiques profondes le long de ses 35 Km de long. L`objectif de cet article est de présenter les résultats de simulation du transport solide et de l`évolution morphologique de la rivière Ha !Ha !, associés à la crue qui a eu lieu en Juillet 1996. Pour cela, le code de calcul mono-dimensionnel RubarBE a été utilisé. Les résultats de cette étude ont été analysés et comparés aux mesures de terrain ; ce qui a permis de discuter de la validité des équations et des hypothèses utilisées par le modèle RubarBE.
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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 | 0.000 |
| 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".