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Global evapotranspiration (ET) through coupling a water balance (WB) model with a machine-learning algorithm (the model tree ensemble, MTE)

A satellite-based water balance method is developed to model global evapotranspiration (ET) through coupling a water balance (WB) model with a machine-learning algorithm (the model tree ensemble, MTE) (hereafter WB-MTE). The WB-MTE algorithm was firstly trained by combining monthly WB-estimated basin ET with the potential drivers (e.g., radiation, temperature, precipitation, wind speed, and vegetation index) across 95 large river basins (5824 basin-months) and then applied to establish global monthly ET maps at a spatial resolution of 0.5° from 1982 to 2009.

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