Articles | Volume 29, issue 2
https://doi.org/10.5194/hess-29-427-2025
© 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-29-427-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jan 2025
Research article |
| 22 Jan 2025
| 22 Jan 2025
Combined impacts of climate change and human activities on blue and green water resources in a high-intensity development watershed
Xuejin Tan
School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510006, PR China
Bingjun Liu
CORRESPONDING AUTHOR
Center of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
Center of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai, 519082, PR China
Zeqin Huang
Center of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
Jianyu Fu
Center of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, 510275, PR China
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Le Ni, Weiguang Wang, Jianyu Fu, and Mingzhu Cao
EGUsphere, https://doi.org/10.5194/egusphere-2025-4782, https://doi.org/10.5194/egusphere-2025-4782, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Existing global evapotranspiration algorithms rely on in situ observations and each comes with its own strengths and weaknesses. Here, we proposed an ensemble framework that employed a multi-scale data-based machine learning model to dynamically select the most appropriate algorithm to be used across spatial and temporal scales, thus fully utilizing their distinct strengths. In multi-scale validations, our framework exhibited enhanced extrapolation performance, stability, and interpretability.
Hailong Wang, Kai Duan, Bingjun Liu, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 25, 4741–4758, https://doi.org/10.5194/hess-25-4741-2021, https://doi.org/10.5194/hess-25-4741-2021, 2021
Short summary
Short summary
Using remote sensing and reanalysis data, we examined the relationships between vegetation development and water resource availability in a humid subtropical basin. We found overall increases in total water storage and surface greenness and vegetation production, and the changes were particularly profound in cropland-dominated regions. Correlation analysis implies water availability leads the variations in greenness and production, and irrigation may improve production during dry periods.
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Short summary
We assess changes in blue and green water scarcity in an anthropogenic highly impacted watershed and their association with climate change and land use change, using the multi-water-flux validated Soil and Water Assessment Tool. Observed streamflow, evapotranspiration, and soil moisture are integrated into model calibration and validation. Results show that both climate change and land use change decrease blue water, while land use change increases green water.
We assess changes in blue and green water scarcity in an anthropogenic highly impacted watershed...
