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Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets

Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets

Abstract. Regional rainfall–runoff modeling is an old but still mostly outstanding problem in the hydrological sciences. The problem currently is that traditional hydrological models degrade significantly in performance when calibrated for multiple basins together instead of for a single basin alone. In this paper, we propose a novel, data-driven approach …