Modélisation de la qualité de l’eau et bilan des nutriments azote et phosphore dans le bassin versant de la rivière des Hurons.
Bibliographic record
Abstract
Depuis 2006, le lac St-Charles, principal réservoir d’eau potable de la Ville de Québec, est sujet à des nuisances de cyanobactéries et de fleurs d’algues contribuant à la dégradation de son état trophique. La rivière des Hurons en tant que principal affluent du lac St-Charles joue un rôle dans l’apport en nutriments et conséquemment dans la qualité de l’eau du lac. Afin de comprendre l’ensemble des processus de transport et de transformation des nutriments (N et P), de l’amont de la rivière des Hurons jusqu’au lac, nous avons recours à la modélisation mathématique et la résolution numérique des équations directrices. Plus précisément, on utilise le modèle hydrologique HYDROTEL pour simuler les débits en rivière et le modèle de qualité de l’eau EFDC (Environmental Fluid Dynamic Code) pour simuler les principaux paramètres de la qualité de l’eau. Les métriques de performance basées sur plusieurs études de modélisation montrent que le modèle EFDC simule bien tant l’hydrodynamique que la dynamique des concentrations de N et P dans le bassin versant de la rivière des Hurons. Il ressort de l’étude que l’occupation du bassin versant (source diffuse de contaminants incluant le parc d’installations septiques autonomes) et l’usine de traitement des eaux usées (UTEU, source ponctuelle de contaminants) de Stoneham contribuent pour une charge totale moyenne d’environ 1.54 T/an de phosphore soit 0.11 kg P/ha/an et de 43.8 T/an d’azote soit 3.19 kg N/ha/an en sortie de la rivière des Hurons vers le Lac St-Charles. Ces charges se répartissent respectivement aux proportions de 83.54% et 85.33% pour l’occupation du bassin versant et 16.46% et 14.66% pour l’UTEU de Stoneham. Over the past decade, Lake St. Charles, the primary drinking water reservoir of Québec City, has experienced several harmful algal blooms episodes contributing to the deterioration of the trophic state and water quality of this strategic water body. The Des Hurons River, the main tributary of Lake St. Charles plays a role in the supply of nutrients and consequently in the general water quality conditions of the lake. To further our understanding of the transport and transformation processes of nutrients (N and P), from the upstream portions of the Des Hurons River to the lake, we used mathematical and numerical modeling. More specifically, we used the HYDROTEL hydrological model to simulate river flows and the EFDC (Environmental Fluid Dynamic Code) water quality model to simulate the major water quality parameters within the river. Performance metrics based on several water quality studies showed that the EFDC model simulates well the hydrodynamics and dynamics of N and P concentrations in the Des Hurons River watershed. It emerges from the study that land use (diffuse source of contaminants including several onsite wastewater treatment plants distributed throughout the watershed) as well as the Stoneham wastewater treatment plant (WWTP, point source of contaminants) contribute to an average total load of approximately 1.54 T / year of P or 0.11 kg P/ha/an and 43.81 T / year of N or 3.19 kg N/ha/an. More specifically, these loads account respectively for 83.54% and 85.33% for the land use and 16.46%, 14.66% for the Stoneham WWTP.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".