Investigation of the Long-Term Trends in the Streamflow Due to Climate Change and Urbanization for a Great Lakes Watershed
Notice bibliographique
Résumé
Climate change and rapid urbanization could possibly increase the vulnerability of the Great Lakes Basin, Canada, which is the largest surface freshwater system in the world. This study explores the joint impact of climate change and land-use changes on the hydrology of a rapidly urbanizing Credit River watershed which lets out into Lake Ontario 25 km southwest of downtown Toronto, Ontario (ON), Canada; we began by classifying the watershed into urban and rural sections. A non-parametric Mann–Kendall test and the Sen slope estimator served to detect and describe the annual-, seasonal-, and monthly-scale trends in the climate variables (temperature, precipitation, and evapotranspiration), as well as the streamflow characteristics (median annual streamflow, baseflow, Runoff Coefficients (RC), Flow Duration Curve (FDC), Center of Volume (COV), and Peak Over Threshold (POT)) since 1916 for four rural and urban sub-watersheds. The temperature, precipitation and evapotranspiration (1950–2019) showed significant increasing trends for different months and seasons. Furthermore, the results indicated that the median annual streamflow, 7-day annual minimum flow, and days above normal are increasing; meanwhile, the annual maximum streamflow is decreasing. A total of 230 datasets were tested for their trends; of these, 80% and 20% increasing and decreasing trends were obtained, respectively. Of the total, significant trends (<0.05%) of 32% and 2% increasing and decreasing, respectively, were observed. The results of the FDC analysis indicated a decline in the annual and winter 10:90 exceedance ratio over the years for the rural and urban sub-watershed gauges. The BFI results show that the BFI of the rural areas was, on average, 18% higher than that of the urban areas. In addition, the RC also showed the influence of land-use and population changes on the watershed hydrology, as the RC for the urban gauge area was 19.3% higher than that for the rural area gauge. However, the difference in the RC was the lowest (5.8%) in the summer. Overall, the findings from this study highlight the annual, seasonal, and monthly changes in the temperature, precipitation, evapotranspiration, and streamflow in the watershed under study. Based on the available monitored data, it was difficult to quantify the changes in the streamflow over the decade which were attributable to population growth and land-cover use and management changes due to municipal official planning in the watershed.
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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) | 0,000 | 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 ».