Opportunities for using Artificial Intelligence and Machine Learning to Address Hydrological Grand Challenges
Opportunities for using Artificial Intelligence and Machine Learning to Address Hydrological Grand Challenges
Charuleka Varadharajan1, Scott L Painter2, Jitendra Kumar3, Dan Lu4, Chaopeng Shen5, Xingyuan Chen6, John D Moulton7, Soumendra Nath Bhanja8, Wen-Ping Tsai5, Dapeng Feng5, Mohammed Ombadi1, Helen Weierbach9, Jared Willard10, Wei Zhi5 and Alexander Y Sun11, (1)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (2)Los Alamos National Laboratory, Los Alamos, United States, (3)Oak Ridge National Laboratory, Oak Ridge, United States, (4)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (5)Pennsylvania State University Main Campus, Department of Civil and Environmental Engineering, University Park, United States, (6)Pacific Northwest National Laboratory, Richland, WA, United States, (7)Los Alamos National Laboratory, Los Alamos, NM, United States, (8)Oak Ridge National Laboratory, Watershed Systems Modeling Group, Environmental Sciences Division, Oak Ridge, TN, United States, (9)Lawrence Berkeley National Laboratory, Earth and Environmental Sciences Area, Berkeley, United States, (10)University of Minnesota, Minneapolis, MN, United States, (11)University of Texas at Austin, Austin, TX, United States