The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Machine Learning Emulation of a Hyper-resolution Physical Snow Model to Assess Landscape-scale Forest Management Outcomes (AGU25)

Machine Learning Emulation of a Hyper-resolution Physical Snow Model to Assess Landscape-scale Forest Management Outcomes

Dr. Joel A Biederman, PhD1, Ravindra Dwivedi2, Patrick D Broxton3, Travis Woolley4, Jackson Leonard5, Jessie K. Pearl6, Bohumil Svoma7, Charles Devine8 and Marcos Robles4, (1)Southwest Watershed Research Center, Tucson, AZ, United States, (2)University of Arizona, School of Natural Resources and the Environment, Tucson, United States, (3)University of Arizona, School of Natural Resources and the Environment, Tucson, AZ, United States, (4)The Nature Conservancy, Center for Science and Public Policy, Tucson, AZ, United States, (5)USDA Forest Service, Rocky Mountain Research Station, Flagstaff, AZ, United States, (6)The Nature Conservancy, Tucson, United States, (7)Salt River Project, Tempe, United States, (8)University of Arizona, Tucson, AZ, United States
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