Gong et al. (2025) Spatiotemporal dynamics and influencing factors of precipitation and soil water use efficiency on the Chinese Loess Plateau

Identification

• Journal: Journal of Hydrology
• Year: 2025
• Date: 2025-11-14
• Authors: Enjun Gong, Jing Zhang, Tao Bai, Zhihui Wang, Hongying Bai, Jun Wang
• DOI: 10.1016/j.jhydrol.2025.134600

Research Groups

• Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China
• School of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China
• Key Laboratory of Soil and Water Conservation on the Loess Plateau, Yellow River Institute of Hydraulic Research, Yellow River Conservancy Commission, Zhengzhou 450003, China
• Shaanxi Key Laboratory for Carbon Neutral Technology, Northwest University, Xi’an 710127, China

Short Summary

This study investigated the spatiotemporal dynamics and driving mechanisms of precipitation use efficiency (PUE) and soil water use efficiency (SWUE) on the Chinese Loess Plateau from 2001 to 2023 using an improved two-leaf model, finding that both efficiencies increased, primarily influenced by human activities, precipitation, and soil moisture.

Objective

• To investigate the spatial patterns and driving mechanisms of precipitation use efficiency (PUE) and soil water use efficiency (SWUE) on the Chinese Loess Plateau, considering the roles of precipitation, soil moisture, and human activities.

Study Configuration

• Spatial Scale: Chinese Loess Plateau
• Temporal Scale: 2001 to 2023

Methodology and Data

• Models used: Improved two-leaf model (with modified environmental stress factor expressions), linear regression, Mann–Kendall tests, XGBoost, residual analysis.
• Data sources: Precipitation data, soil moisture data, Gross Primary Production (GPP) observations (for model validation).

Main Results

• The improved two-leaf model accurately simulated GPP, reducing root mean square error by 21.8% compared to observations.
• Both PUE and SWUE exhibited increasing trends, with 64.34% of the area showing simultaneous increases, and the multi-year average exhibiting a gradient shift from northwest to southeast.
• Cropland showed the highest annual mean PUE and SWUE among vegetation types, with the greatest rate of change occurring in cropland reclamation areas.
• Precipitation and the aridity index were significant factors for PUE.
• Soil moisture was the primary environmental determinant of SWUE, with its influence increasing markedly from 2001 to 2023.
• Human activities had a greater impact on both PUE and SWUE than climate change.

Contributions

• Developed and applied an improved two-leaf model for more accurate GPP simulation in water-limited regions.
• Provided a comprehensive spatiotemporal analysis of PUE and SWUE and their driving mechanisms on the Loess Plateau over a 23-year period.
• Quantified the relative impacts of climate change and human activities on PUE and SWUE, highlighting the dominant role of human activities.
• Offered scientific guidance for vegetation restoration and water-resource management in arid and semi-arid regions.

Funding

• Not explicitly mentioned in the provided text.

Citation

@article{Gong2025Spatiotemporal,
  author = {Gong, Enjun and Zhang, Jing and Bai, Tao and Wang, Zhihui and Bai, Hongying and Wang, Jun},
  title = {Spatiotemporal dynamics and influencing factors of precipitation and soil water use efficiency on the Chinese Loess Plateau},
  journal = {Journal of Hydrology},
  year = {2025},
  doi = {10.1016/j.jhydrol.2025.134600},
  url = {https://doi.org/10.1016/j.jhydrol.2025.134600}
}