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The prevailing approaches for ET retrievals are either limited inspatiotemporal coverage or largely influenced by choice of input data orsimplified model physics, or a combination thereof. Here, using an independentmass conservation approach, we develop water balance-based ET datasets (ET-WB)for the global land and the selected 168 major river basins. We generate 4669probabilistic unique combinations of the ET-WB leveraging multi-source datasets(23 precipitation, 29 runoff, and 7 storage change datasets) from satelliteproducts, in-situ measurements, reanalysis, and hydrological simulations. Wecompare our results with the four auxiliary global ET datasets and previousregional studies, followed by a rigorous discussion of the uncertainties, theirpossible sources, and potential ways to constrain them. The seasonal cycle ofglobal ET-WB possesses a unimodal distribution with the highest (median value:65.61 mm/month) and lowest (median value: 36.11 mm/month) values in July andJanuary, respectively, with the spread range of roughly +/-10 mm/month fromdifferent subsets of the ensemble. Auxiliary ET products illustrate similarintra-annual characteristics with some over/under-estimation, which arecompletely within the range of the ET-WB ensemble. We found a gradual increasein global ET-WB from 2003 to 2010 and a subsequent decrease during 2010-2015,followed by a sharper reduction in the remaining years primarily attributed tothe varying precipitation. Multiple statistical metrics show reasonably goodaccuracy of monthly ET-WB (e.g., a relative bias of +/-20%) in most riverbasins, which ameliorates at annual scales. The long-term mean annual ET-WBvaries within 500-600 mm/yr and is consistent with the for auxiliary ETproducts (543-569 mm/yr). Observed trend estimates, though regionallydivergent, are evidence of the increasing ET in a warming climate.

ET-WB: water balance-based estimations of terrestrial evaporation over global land and major global basins