Runoff Simulation Under Future Climate Change Conditions: Performance Comparison of Data-Mining Algorithms and Conceptual Models

Water resources in arid and semi-arid regions are susceptible to alteration in hydro-climatic variables, especially under climate change which makes runoff simulations more challenging. This study aims to simulate input runoff to a dam reservoir in an arid region under changing climatic conditions u...

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Veröffentlicht in:	Water resources management Jg. 36; H. 4; S. 1191 - 1215
Hauptverfasser:	Yoosefdoost, Icen, Khashei-Siuki, Abbas, Tabari, Hossein, Mohammadrezapour, Omolbani
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.03.2022 Springer Nature B.V
Schlagworte:	administrative management Algorithms Arid regions Arid zones Artificial neural networks Atmospheric Sciences basins Civil Engineering Climate change Climate models Climatic conditions Computer simulation Dams Data analysis Data mining Earth and Environmental Science Earth Sciences Environment Geotechnical Engineering & Applied Earth Sciences Global climate Global climate models Hydrogeology Hydrology/Water Resources Infinite series Intercomparison Neural networks Parameter identification Parameters Reservoirs Runoff Semi arid areas Semiarid zones Support vector machines temperature variance Water resources Artificial intelligence techniques Climate change LARS Rainfall-runoff forecasting model Gamma and M tests
ISSN:	0920-4741, 1573-1650
Online-Zugang:	Volltext
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