Articles | Volume 30, issue 9
https://doi.org/10.5194/hess-30-2775-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-2775-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 May 2026
Research article |
| 08 May 2026
| 08 May 2026
Understanding meteorological, runoff, and agricultural drought propagation and their influencing factors in an ensemble of multiple datasets
Yuanrui Liu
School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou, Henan, China
Tingting Hu
School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou, Henan, China
Jiawen Yang
School of Ecology and Environment, North China University of Water Resources and Hydropower, Zhengzhou, Henan, China
Lei Yu
CORRESPONDING AUTHOR
School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou, Henan, China
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Short summary
Understanding drought propagation is vital for disaster preparedness and risk management. This study presents a comprehensive analysis of various drought conditions across global land areas. Interpretable machine learning technique is employed to identify the key factors influencing drought propagation. Results reveal large-scale propagation pathways of meteorological-runoff-agricultural droughts, and highlight how climatic characteristics affect these dynamics.
Understanding drought propagation is vital for disaster preparedness and risk management. This...
