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Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS

Taereem Kim, Tiantian Yang, Shang Gao, Lujun Zhang, Ziyu Ding, Xin Wen, Jonathan J. Gourley, Yang Hong

2021Journal of Hydrology144 citationsDOIOpen Access PDF

Topics & Concepts

StreamflowComputer scienceHydrological modellingEnvironmental scienceSimulation modelingHydrology (agriculture)Artificial neural networkMeteorologyMachine learningGeologyClimatologyCartographyDrainage basinMathematicsGeographyPhysicsGeotechnical engineeringMathematical economicsHydrology and Watershed Management StudiesHydrological Forecasting Using AIFlood Risk Assessment and Management
Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS | Litcius