Evaporation (ET) is one of the crucial components of the water cycle, which serves as the nexus between global water, energy, and carbon cycles. Accurate quantification of ET is, therefore, pivotal in understanding various earth system processes and subsequent societal applications. The prevailing approaches for ET retrievals are either limited in spatiotemporal coverage or largely influenced by the choice of input data or simplified model physics, or a combination thereof. Here, using an independent mass conservation approach, we develop water-balance-based ET datasets (ET-WB) for the global land and the selected 168 major river basins. We generate 4669 probabilistic unique combinations of the ET-WB leveraging multi-source datasets (23 precipitation, 29 runoff, and 7 storage change datasets) from satellite products, in situ measurements, reanalysis, and hydrological simulations. We compare our results with the four auxiliary global ET datasets and previous regional studies, followed by a rigorous discussion of the uncertainties, their possible sources, and potential ways to constrain them. The seasonal cycle of global ET-WB possesses a unimodal distribution with the highest (median value: 65.61 mm per month) and lowest (median value: 36.11 mm per month) values in July and January, respectively, with the spread range of roughly ±10 mm per month from different subsets of the ensemble. Auxiliary ET products illustrate similar intra-annual characteristics with some over- or underestimation, which are completely within the range of the ET-WB ensemble. We found a gradual increase in 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 to the varying precipitation. Multiple statistical metrics show reasonably good accuracy of monthly ET-WB (e.g., a relative bias of ±20 %) in most river basins, which ameliorates at annual scales. The long-term mean annual ET-WB varies within 500–600 mm yr⁻¹ and is consistent with the four auxiliary ET products (543–569 mm yr⁻¹). Observed trend estimates, though regionally divergent, are evidence of the increasing ET in a warming climate. The current dataset will likely be useful for several scientific assessments centering around water resources management to benefit society at large. The dataset is publicly available in various formats (NetCDF, Mat, and Shapefile) at https://doi.org/10.5281/zenodo.8339655 (Xiong et al., 2023).

Environmental change is growingly reported as an important driver of human migration. Among all environmental variables, water crises are the most critical factors. To date, patterns of interconnections between changes in water and migration are not yet clearly understood. Here, we explore these patterns through a systematic review that combined a quantitative text‐mining approach with qualitative thematic analysis. Our results generally concur with those of previous studies, which found that water‐driven migration usually occurs internally and that the population in low‐ and middle‐income countries and in dry regions are the most vulnerable and more likely to migrate or be displaced in the face of water‐related events. However, our causal network analysis highlights that water is not the only reason for migration: Its related problems could be major triggers driving people‐at‐risk to leave their original place. Based on observed evidence, water‐driven migration can be generally divided into four patterns: variability in water quantity, damaging water hazards and extremes, physical disturbances to water systems, and water pollution. These patterns are not independent but interconnected through multifaceted factors affecting people's livelihoods and their decisions to migrate. Understanding water‐migration dynamics requires systematic thinking of the interconnections between changes in water and in migration patterns, the investigation of interactions between fast and slow water variables and their dynamic link to other socioeconomic variables, an integrated water‐migration database to help identify early‐warning signals of damaging water hazards that may result in undesirable migration, and targeted water policies that focus on building the resilience of vulnerable regions and population to climate change.This article is categorized under: Human Water > Value of Water