State-of-the-art hydrological datasets exhibit low water balance consistency globally
7 affiliations
- 1School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
- 2North China University of Water Resources and Electric Power (Zhengzhou, China)
- 3Southern University of Science and Technology (Shenzhen, China)
- 4Henan Provincial Key Laboratory of Hydrosphere and Watershed Water Security, North China University of Water Resources and Electric Power, Zhengzhou, China
- 5School of Environment and Civil Engineering, Dongguan University of Technology, Dongguan, China
- 6Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
- 7Max Planck Institute for Biogeochemistry, Jena, Germany
Abstract
The proliferation and diversification of hydrological datasets have significantly advanced hydrological research. However, the coherence across these datasets remains poorly understood, hindering the comparability of findings derived from different data sources and variables. Here, we demonstrate that state-of-the-art hydrological datasets exhibit overall low consistency when evaluated through the lens of water balance – specifically, the relationship between variations in soil moisture and the difference between precipitation, evapotranspiration, and runoff. Our analysis reveals that satellite-based precipitation datasets generally show the highest consistency, while gauge-based datasets perform better in densely monitored regions of the Northern Hemisphere. For evapotranspiration, runoff, and soil moisture, reanalysis datasets demonstrate broader areas of higher consistency compared to gauge- or satellite-based products. Spatial patterns of consistency are strongly influenced by aridity and temperature, which affect measurement and modelling accuracy, while vegetation cover further modulates the performance of soil moisture datasets. Notably, dataset consistency has improved significantly in northern mid-latitudes over recent decades, likely reflecting advancements in observational technologies and the effects of climate warming. These findings underscore the importance of continued efforts to enhance dataset coherence and reliability for robust hydrological assessments.
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BibTeX
@article{huang2026stateoftheart,
title = {{State-of-the-art hydrological datasets exhibit low water balance consistency globally}},
author = {Hao Huang and Junguo Liu and Aifang Chen and Melissa Ruiz‐Vásquez and René Orth},
journal = {Earth system science data},
year = {2026},
month = may,
doi = {10.5194/essd-18-3109-2026},
url = {https://doi.org/10.5194/essd-18-3109-2026},
note = {CC BY},
}
RIS
TY - JOUR
TI - State-of-the-art hydrological datasets exhibit low water balance consistency globally
AU - Hao Huang
AU - Junguo Liu
AU - Aifang Chen
AU - Melissa Ruiz‐Vásquez
AU - René Orth
PY - 2026
DA - 2026/05/11
JO - Earth system science data
DO - 10.5194/essd-18-3109-2026
UR - https://doi.org/10.5194/essd-18-3109-2026
AB - The proliferation and diversification of hydrological datasets have significantly advanced hydrological research. However, the coherence across these datasets remains poorly understood, hindering the comparability of findings derived from different data sources and variables. Here, we demonstrate that state-of-the-art hydrological datasets exhibit overall low consistency when evaluated through the lens of water balance – specifically, the relationship between variations in soil moisture and the difference between precipitation, evapotranspiration, and runoff. Our analysis reveals that satellite-based precipitation datasets generally show the highest consistency, while gauge-based datasets perform better in densely monitored regions of the Northern Hemisphere. For evapotranspiration, runoff, and soil moisture, reanalysis datasets demonstrate broader areas of higher consistency compared to gauge- or satellite-based products. Spatial patterns of consistency are strongly influenced by aridity and temperature, which affect measurement and modelling accuracy, while vegetation cover further modulates the performance of soil moisture datasets. Notably, dataset consistency has improved significantly in northern mid-latitudes over recent decades, likely reflecting advancements in observational technologies and the effects of climate warming. These findings underscore the importance of continued efforts to enhance dataset coherence and reliability for robust hydrological assessments.
SN - 1866-3508
SN - 1866-3516
ER -