Hydrologic Modelling of Great Lakes Basin in Southern Ontario and Climate Change Impact Assessment
Notice bibliographique
Résumé
Climate change is a growing concern across the globe, and the Provincial Government of Ontario recognizes that climate change impacts need to be considered in all decision-making. In Southern Ontario, a critical and ongoing challenge is balancing the competing water demands under changing climate for various uses to ensure prosperity and sustainability in the future. A better understanding and quantification of impacts of possible climate change on regional hydrology are necessary for sustainable water resources management and maintaining healthy ecosystems in this region. In order to study the impacts of future climate on the regional water resources, a large-scale hydrologic model was developed for Southern Ontario within the Great Lakes basin using the Soil and Water Assessment Tool (SWAT). The study area includes four basins: Eastern Georgian Bay, Eastern Lake Huron, Northern Lake Erie, and Lake Ontario and Niagara Peninsula basins, covering a total area of about 84,650 km2. The hydrologic model was calibrated and validated using monthly observed streamflow data at 40 gauging stations, and spatially validated at another 40 gauging stations across the study area. The developed model was employed to estimate water budget components for a reference period (1971-2000), and to assess climate change impacts on the hydrologic regime during the mid-century (2041-2070) and the end-century (2071-2100). Projected climate data from five GCM-RCMs simulations for RCP4.5 and RCP8.5 scenarios were obtained from the NA-CORDEX archive. After bias correction, climate data sets were used in the SWAT model for the impact assessment. Based on the model calibration and validation results, the overall performance of the model was found to be satisfactory. Its performance was better in the predominantly agricultural Northern Lake Erie and Eastern Lake Huron basins than the other two basins. The average annual precipitation, evapotranspiration (ET), surface runoff and water yields for the study area over the period 1971-2000 were estimated at 979 mm, 540 mm, 183 mm and 410 mm, respectively. The average annual precipitation in the four basins varied from 923 mm to 1049 mm, and water yields were found to vary between 377 mm and 465 mm. The projected increases in mean annual temperature are 3.0oC and 2.4oC by the mid-century, while the increases are 5.2oC and 3.2oC by the end-century for RCP8.5 and RCP4.5 scenarios, respectively. The average annual precipitation of the study area is projected to increase by 8% to 16%, depending on the scenario and time period. The possible increases in precipitation are relatively high for the RCP8.5 scenario and likely to vary between 13% and 18% in the four basins by the end of the 21st century. By the mid-century, the average annual water yields in the four basins are predicted to increase by 7% to 20%, and 5% to 13% under RCP8.5 and RCP4.5 scenarios, respectively. By the end-century, the projected increases in the annual water yields of the basins are 5% to 26% for RCP8.5 scenario and 3% to 11% for RCP4.5 scenario. In general, the average monthly water yield in the study area is likely to increase during December to February, but decrease in the months of March and April. The results are also presented spatially for the subwatersheds across the study area. The study results would help in planning and management of water resources, and in developing climate change adaptation plans and strategies.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».