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Abstract: Global calibration and locally-informed regionalization of hydrological model parameters using AI-based large-sample emulators (AGU25)

Global calibration and locally-informed regionalization of hydrological model parameters using AI-based large-sample emulators

Guoqiang Tang1, Andy Wood2, Chaopeng Shen3 and Yalan Song3, (1)Wuhan University, School of Water Resources and Hydropower Engineering, Wuhan, China, (2)NSF National Center for Atmospheric Research, Boulder, United States, (3)Pennsylvania State University Main Campus, Department of Civil and Environmental Engineering, University Park, United States
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