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Abstract: Water Scarcity Attribution in the Western U.S. using Interpretable Machine Learning Emulators of Process-Based Hydrologic Models (AGU25)

Water Scarcity Attribution in the Western U.S. using Interpretable Machine Learning Emulators of Process-Based Hydrologic Models

Yifan Luo1, Danielle S Grogan2, Shan Zuidema2, Richard B. Lammers3, Jiameng Zheng4, Matt Lisk5, Karen Fisher-Vanden6, Sheila Olmstead7 and Vivek Srikrishnan8, (1)Cornell University, School of Civil and Environmental Engineering, Ithaca, NY, United States, (2)University of New Hampshire, Earth Systems Research Center, Durham, NH, United States, (3)University of New Hampshire, Earth Systems Research Center, Durham, United States, (4)Louisiana State University, Baton Rouge, United States, (5)Pennsylvania State University, University Park, United States, (6)Pennsylvania State University, Agricultural Economics, Sociology, and Education, University Park, PA, United States, (7)Cornell University, Ithaca, United States, (8)Cornell University, Ithaca, NY, United States
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