Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 18, issue 5
Articles | Volume 18, issue 5
https://doi.org/10.5194/essd-18-3109-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-3109-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 5
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

Viewed

Total article views: 3,524 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,600 715 209 3,524 504 180 244
  • HTML: 2,600
  • PDF: 715
  • XML: 209
  • Total: 3,524
  • Supplement: 504
  • BibTeX: 180
  • EndNote: 244
Views and downloads (calculated since 24 Jul 2025)
Cumulative views and downloads (calculated since 24 Jul 2025)

Viewed (geographical distribution)

Total article views: 3,524 (including HTML, PDF, and XML) Thereof 3,420 with geography defined and 104 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 03 Oct 2026
Download
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.
Read more
Share
Altmetrics
Final-revised paper
Preprint