Hydrodynamic Modelling of Great Slave Lake Using NEMO
Notice bibliographique
Résumé
The subarctic region of northern Canada, including the Mackenzie River basin is deeply impacted by the changing climate. Unprecedented rates of warming in Canada’s North, up to four times the global average, have been observed in the region over the past few decades. This brings significant implications for regional hydrology, ecosystems, and human activities. A major controlling feature in the Mackenzie River Basin is Great Slave Lake, which is the second largest lake in the Northwest Territories of Canada and the deepest lake in North America. With over 60% of the population of Northwest Territories living along its shores, Great Slave Lake is a vital ecological and societal asset in the region. This study aims to further our understanding of water circulation and stratification patterns in Great Slave Lake through numerical simulation. Despite the status of Great Slave Lake as one of the largest and deepest lakes in North America, comprehensive numerical modelling has proven difficult due to lack of accurate bathymetric data. To address this gap, we collaborated with the Department of Fisheries and Oceans to develop the first complete bathymetric map of Great Slave Lake. Historical naval charts and field sheets were integrated with additional sounding data to produce a simulation domain tailored to the Nucleus for European Modelling of the Ocean (NEMO) at a horizontal resolution of 1km with 30 vertical layers. The NEMO model was chosen for application in this large lake for consistency with the existing model setup being used by Environment and Climate Change Canada (ECCC) for its operational forecasting system in the Laurentian Great Lakes. Atmospheric reanalysis is provided by ECCC’S Regional Deterministic Reanalysis System (RDRS), while surface runoff entering the lake is driven by the Community Environmental Modelling System – Surface & Hydrology (MESH) outputs from the Global Water Futures reanalysis efforts. The resulting NEMO model shows good capability of simulating lake processes with preliminary results indicating that the lake exhibits seasonal thermal stratification, consistent with dimictic behaviour, where full vertical mixing occurs twice annually. Our results also show that wind-induced mixing appears to also play a significant role in lake circulation, and a counterclockwise circulation pattern is observed, with prominent gyres in the main basin of the lake. Ongoing work focuses on further validation of the temperature profiles at select locations and sensitivity analysis to improve the overall simulation capabilities of the model for future water resource management needs.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».