Articles | Volume 29, issue 14
https://doi.org/10.5194/hess-29-3379-2025
© Author(s) 2025. 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-29-3379-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evapotranspiration stress intensifies with enhanced sensitivity to soil moisture deficits in a rapidly greening China
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Yong Wang
CORRESPONDING AUTHOR
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Key Laboratory of Water Safety for Beijing-Tianjin-Hebei Region of Ministry of Water Resources, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Yong Zhao
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Key Laboratory of Water Safety for Beijing-Tianjin-Hebei Region of Ministry of Water Resources, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Shouzhi Chen
College of Water Sciences, Beijing Normal University, Beijing, 100875, China
Longhao Wang
Key Laboratory of Water Cycle and Related Land Surface Processes, Chinese Academy of Sciences, Beijing, 100101, China
Institute of Geographic Sciences and Natural Resources Research, University of Chinese Academy of Sciences, Beijing, 100049, China
Wenjing Yang
National Centre for Groundwater Research and Training, Flinders University, Adelaide, SA 5001, Australia
Xing Li
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Xinxi Li
PowerChina Asia & Pacific, Power Construction Corporation of China, Beijing, 100038, China
Huimin Lei
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing, 100084, China
Huanyu Chang
Academy of Eco-civilization Development for Jing-Jin-Ji Megalopolis, Tianjin Normal University, Tianjin, 300387, China
Jiaqi Zhai
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Key Laboratory of Water Safety for Beijing-Tianjin-Hebei Region of Ministry of Water Resources, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Yongnan Zhu
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Key Laboratory of Water Safety for Beijing-Tianjin-Hebei Region of Ministry of Water Resources, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Qingming Wang
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Key Laboratory of Water Safety for Beijing-Tianjin-Hebei Region of Ministry of Water Resources, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Ting Ye
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China
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Cited
9 citations as recorded by crossref.
- A 20-year assessment of AGBD accumulation and its drivers in China's broad-leaved forests across temperature zones S. Ma et al.
- Mapping stability and instability hotspots in Jiangsu’s vegetation: an explainable machine learning approach to climatic and anthropogenic drivers F. Jiao et al.
- Bidirectional correlations between landscape patterns and hydrological processes: a systematic review across multi-level interactions X. Wang et al.
- Soil moisture measurements: a review E. Eishoeei et al.
- Mechanisms by which irrigation regimes influence soil water deep percolation J. Cui et al.
- Subsurface-fed transpiration drives surface energy partitioning in soil-limited karst systems D. Yang et al.
- Sustainability Assessment and Risk Zone Identification of Irrigation-Driven Regional Greening in Northwest China J. Song et al.
- Daily-scale gridded analysis of spatiotemporal characteristics in agricultural drought events across winter wheat growth stages in the Huang–Huai–Hai Plain, China Y. Wang et al.
- A novel hybrid model for actual evapotranspiration estimation in data-scarce arid regions: Integrating modified Budyko and machine learning models using deep learning M. Mohammadnezhad et al.
9 citations as recorded by crossref.
- A 20-year assessment of AGBD accumulation and its drivers in China's broad-leaved forests across temperature zones S. Ma et al.
- Mapping stability and instability hotspots in Jiangsu’s vegetation: an explainable machine learning approach to climatic and anthropogenic drivers F. Jiao et al.
- Bidirectional correlations between landscape patterns and hydrological processes: a systematic review across multi-level interactions X. Wang et al.
- Soil moisture measurements: a review E. Eishoeei et al.
- Mechanisms by which irrigation regimes influence soil water deep percolation J. Cui et al.
- Subsurface-fed transpiration drives surface energy partitioning in soil-limited karst systems D. Yang et al.
- Sustainability Assessment and Risk Zone Identification of Irrigation-Driven Regional Greening in Northwest China J. Song et al.
- Daily-scale gridded analysis of spatiotemporal characteristics in agricultural drought events across winter wheat growth stages in the Huang–Huai–Hai Plain, China Y. Wang et al.
- A novel hybrid model for actual evapotranspiration estimation in data-scarce arid regions: Integrating modified Budyko and machine learning models using deep learning M. Mohammadnezhad et al.
Saved (final revised paper)
Latest update: 02 May 2026
Short summary
In the real hydrological Earth system, the relationships between variables are not constant. This study employed advanced statistical models, incorporating physical mechanisms to examine how evaporation stress responds to key factors over time. We found that stronger soil drought effects can be expected in areas undergoing rapid greening. This study may enhance the comprehension of evaporation stress, help optimize parameters in Earth system models, and promote greening initiatives.
In the real hydrological Earth system, the relationships between variables are not constant....