Zhou et al. (2025) Nonstationary groundwater level responses to coupled human–natural drivers in the Baiyangdian Watershed

Identification

• Journal: Journal of Hydrology
• Year: 2025
• Date: 2025-11-20
• Authors: Long Zhou, Longcang Shu, Xiaoran Yin, Tianyu Zhou, Yuxi Li, Bo Liu, Chengpeng Lu, Pengnian Yang
• DOI: 10.1016/j.jhydrol.2025.134623

Research Groups

• College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, China
• College of Hydrology and Water Resources, Hohai University, Nanjing, China
• School of Water Conservancy and Environment, University of Jinan, Jinan, China
• China Water Huaihe Planning, Design and Research Co., Ltd., Hefei, China

Short Summary

This study develops an integrated framework to quantify direct and indirect effects of coupled human-natural drivers on groundwater level (GWL) variations in the Baiyangdian Basin, revealing a transition in GWL driving mechanisms from natural-anthropogenic synergy to human activity dominance and hydrological regulation over different periods.

Objective

• To develop an integrated framework combining GeoDetector, partial least squares structural equation modeling, and elasticity analysis to assess spatiotemporal groundwater level (GWL) variations and attribute them to coupled human-natural drivers, quantifying direct and indirect effects.
• To characterize the non-stationarity and multi-scale controls of groundwater fluctuations in the Baiyangdian Basin, providing a quantitative basis for regional water resource management strategies.

Study Configuration

• Spatial Scale: Baiyangdian Basin (Baiyangdian Watershed), North China Plain.
• Temporal Scale: 1980–2022, with attribution analysis divided into three stages: 1980–2000, 2001–2015, and 2016–2022.

Methodology and Data

• Models used: GeoDetector, Partial Least Squares Structural Equation Modeling (PLS-SEM), Elasticity analysis.
• Data sources: Data related to population density, farmland area, irrigation water, industrial water, precipitation, and potential evapotranspiration (specific sources not detailed in the provided text, but typically from observational records and statistical databases).

Main Results

• Population density, farmland area, irrigation water, and industrial water are identified as dominant GWL drivers, with an explanatory power up to 0.83.
• Precipitation and potential evapotranspiration exhibit lagged responses on GWL.
• Attribution analysis reveals stage-dependent shifts in GWL drivers:
  • During 1980–2000, mountain ecology factors positively influenced GWL, while climate and hydrological processes had a negative influence.
  • During 2001–2015, ecological effects turned negative, and human pressures intensified.
  • During 2016–2022, anthropogenic regulation, including the South-to-North Water Diversion and ecological replenishment, generated positive effects.
• Multi-layer aquifer responses and diverse recharge pathways contribute to short-term oscillations and long-term fluctuations in GWL.
• The study reveals a transition in GWL driving mechanisms from a natural-anthropogenic synergy to dominance by human activities and hydrological regulation.

Contributions

• Developed an integrated framework for attributing groundwater level variations by combining GeoDetector, partial least squares structural equation modeling, and elasticity analysis, effectively addressing multicollinearity among environmental factors.
• Provided a quantitative assessment of the direct and indirect effects of coupled human-natural drivers on groundwater levels.
• Characterized the non-stationarity and multi-scale controls of groundwater fluctuations in the Baiyangdian Basin.
• Revealed stage-dependent shifts in the dominant driving mechanisms of groundwater level changes over distinct periods (1980–2000, 2001–2015, 2016–2022).
• Offered a quantitative basis for understanding groundwater dynamics and developing regional water resource management strategies.

Funding

• Not explicitly mentioned in the provided text.

Citation

@article{Zhou2025Nonstationary,
  author = {Zhou, Long and Shu, Longcang and Yin, Xiaoran and Zhou, Tianyu and Li, Yuxi and Liu, Bo and Lu, Chengpeng and Yang, Pengnian},
  title = {Nonstationary groundwater level responses to coupled human–natural drivers in the Baiyangdian Watershed},
  journal = {Journal of Hydrology},
  year = {2025},
  doi = {10.1016/j.jhydrol.2025.134623},
  url = {https://doi.org/10.1016/j.jhydrol.2025.134623}
}