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River Flow Simulation Under Climate Change: Qu’Appelle River, Saskatchewan, Canada
https://orcid.org/http://orcid.org/0000-0003-1473-4147
https://orcid.org/http://orcid.org/0000-0002-9281-8998
https://orcid.org/http://orcid.org/0000-0003-1074-6167
In this paper, the river flow regime of the Qu’Appelle River in Saskatchewan, Canada, was evaluated using the artificial neural network under the impacts of climate change. In this regard, this study took advantage of the CanESM2 model to determine future climate of the region. The SDSM model was then adopted to perform downscaling the data produced by the CanESM2. The historical data (climate and hydrometric) were utilized to train networks to determine the amount of snowfall from precipitation as well as the flow regime based on the air temperature, snowfall, and rainfall data. The generated climate data were inputted into the neural network to determine how the changing climate would impact the flow of the Qu’Appelle River. Comparison of the results obtained under climate change and historical scenarios demonstrated that climate change is expected to result in heterogeneous alteration in precipitation and air temperature patterns causing substantial adverse impacts on the flow regime of the Qu’Appelle River.
River Flow Simulation Under Climate Change: Qu’Appelle River, Saskatchewan, Canada
https://orcid.org/http://orcid.org/0000-0003-1473-4147
https://orcid.org/http://orcid.org/0000-0002-9281-8998
https://orcid.org/http://orcid.org/0000-0003-1074-6167
In this paper, the river flow regime of the Qu’Appelle River in Saskatchewan, Canada, was evaluated using the artificial neural network under the impacts of climate change. In this regard, this study took advantage of the CanESM2 model to determine future climate of the region. The SDSM model was then adopted to perform downscaling the data produced by the CanESM2. The historical data (climate and hydrometric) were utilized to train networks to determine the amount of snowfall from precipitation as well as the flow regime based on the air temperature, snowfall, and rainfall data. The generated climate data were inputted into the neural network to determine how the changing climate would impact the flow of the Qu’Appelle River. Comparison of the results obtained under climate change and historical scenarios demonstrated that climate change is expected to result in heterogeneous alteration in precipitation and air temperature patterns causing substantial adverse impacts on the flow regime of the Qu’Appelle River.
River Flow Simulation Under Climate Change: Qu’Appelle River, Saskatchewan, Canada
https://orcid.org/http://orcid.org/0000-0003-1473-4147
https://orcid.org/http://orcid.org/0000-0002-9281-8998
https://orcid.org/http://orcid.org/0000-0003-1074-6167
In this paper, the river flow regime of the Qu’Appelle River in Saskatchewan, Canada, was evaluated using the artificial neural network under the impacts of climate change. In this regard, this study took advantage of the CanESM2 model to determine future climate of the region. The SDSM model was then adopted to perform downscaling the data produced by the CanESM2. The historical data (climate and hydrometric) were utilized to train networks to determine the amount of snowfall from precipitation as well as the flow regime based on the air temperature, snowfall, and rainfall data. The generated climate data were inputted into the neural network to determine how the changing climate would impact the flow of the Qu’Appelle River. Comparison of the results obtained under climate change and historical scenarios demonstrated that climate change is expected to result in heterogeneous alteration in precipitation and air temperature patterns causing substantial adverse impacts on the flow regime of the Qu’Appelle River.
River Flow Simulation Under Climate Change: Qu’Appelle River, Saskatchewan, Canada
Lecture Notes in Civil Engineering
Desjardins, Serge (Herausgeber:in) / Azimi, Amir Hossein (Herausgeber:in) / Poitras, Gérard J. (Herausgeber:in) / Hassanjabbar, Amin (Autor:in) / Nezaratian, Hosein (Autor:in) / Wu, Peng (Autor:in)
Canadian Society of Civil Engineering Annual Conference ; 2023 ; Moncton, NB, Canada
Proceedings of the Canadian Society for Civil Engineering Annual Conference 2023, Volume 9 ; Kapitel: 18 ; 251-260
10.10.2024
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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