Articles | Volume 18, issue 5
https://doi.org/10.5194/essd-18-3109-2026
https://doi.org/10.5194/essd-18-3109-2026
Data review article
 | 
11 May 2026
Data review article |  | 11 May 2026

State-of-the-art hydrological datasets exhibit low water balance consistency globally

Hao Huang, Junguo Liu, Aifang Chen, Melissa Ruiz-Vásquez, and René Orth

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Short summary
Hydrological research benefits from a growing number and diversity of datasets. However, the consistency across the increasing suite of datasets is unclear, limiting the comparability of findings derived from different datasets and variables. We find overall low consistency of numerous state-of-the-art precipitation, evapotranspiration, runoff, and soil moisture datasets in terms of the water balance. Meanwhile, the water balance consistency varies across space, sources, variables, and time.
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