H165
Machine Learning in Hydrologic Forecasting II Posters

Tuesday, 15 December 2020: 04:00-20:59
Poster
Primary Convener:  Amir Hossein Mazrooei, National Center for Atmospheric Research, Boulder, CO, United States
Conveners:  Pierre Gentine, Columbia University, Earth and Environmental Engineering, New York, NY, United States and Andrew W Wood, National Center for Atmospheric Research, Boulder, CO, United States
Primary Liaison:  Amir Hossein Mazrooei, National Center for Atmospheric Research, Boulder, CO, United States
Chairs:  Pierre Gentine, Columbia University, Earth and Environmental Engineering, New York, NY, United States and Andrew W Wood, National Center for Atmospheric Research, Boulder, CO, United States
OSPA Liaison:  Pierre Gentine, Columbia University, Earth and Environmental Engineering, New York, NY, United States
 
Comparison between 2D-CNN a 3D-CNN for precipitation downscaling (679346)
Takeyoshi Nagasato1, Kei Ishida2, Kazuki Yokoo3, Masato Kiyama3 and Motoki Amagasaki3, (1)Kumamoto University, Department of Civil and Environmental Engineering, Kumamoto, Japan, (2)University of California Davis, Davis, United States, (3)Kumamoto University, Kumamoto, Japan
 
Improving irrigation planning and early prediction for agricultural drought in Wisconsin (759019)
Ammara Talib and Ankur R Desai, University of Wisconsin Madison, Madison, WI, United States
 
Improved Streamflow Forecasting Using Variational Mode Decomposition and Extreme Gradient Boosting (717251)
Mostafa Elkurdy1, Andrew D. Binns2 and Bahram Gharabaghi2, (1)University of Guelph, Guelph, ON, Canada, (2)University of Guelph, School of Engineering, Guelph, ON, Canada
 
Inter-comparison of statistical downscaling and machine learning based post-processors for improving Indian summer monsoon rainfall (720031)
Nibedita Samal, Indian Institute of Science Education and Research Bhopal, Bhopal, India and Sanjeev Jha, Indian Institute of Science Education and Research Bhopal, Earth and Environmental Sciences, Bhopal, India
 
Applying Deep Learning Models for Catchment Scale Streamflow Prediction (759668)
Jinyang Li1, Kuo-lin Hsu1 and Ai-Ling Jiang2, (1)University of California Irvine, Irvine, CA, United States, (2)University of California, Irvine, Civil and Environmental Engineering, Irvine, CA, United States
 
Assessment of predictability in Downscaling GEFS Precipitation Forecasts (757228)
Smit Chetan Doshi, University of Nebraska - Lincoln, Civil and Environmental Engineering, Lincoln, NE, United States and Tirthankar Roy, University of Nebraska-Lincoln, Civil and Environmental Engineering, Omaha, NE, United States
 
Machine Learning Based Prediction Model for Suspended Sediment Concentration (SSC) Under the Influence of Anthropogenic Factors in India (701773)
Mayur Shindekar, Indian Institute of Technology Delhi, New Delhi, India and Dhanya C.T, Indian Institute of Technology Delhi, Civil Engineering, New Delhi, India
 
Modeling high-resolution precipitation by means of a regional climate model coupled with a machine learning algorithms: Application to Dong Nai-Sai Gon river watershed. (710080)
Toan Q Trinh, University of California Davis, Davis, CA, United States
See more of: Hydrology
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