Xu et al. (2025) Balancing agricultural expansion and groundwater sustainability: Insights from GRACE and hydrological models

Identification

• Journal: Agricultural Water Management
• Year: 2025
• Date: 2025-12-01
• Authors: Chi Xu, Hao Chen, Wanchang Zhang, Shuhang Wang, Zhenghui Fu
• DOI: 10.1016/j.agwat.2025.110039

Research Groups

• State Key Laboratory of Environment Criteria and Risk Assessment, National Engineering Laboratory for Lake Pollution Control and Ecological Restoration, State Environmental Protection Key Laboratory for Lake Pollution Control, Chinese Research Academy of Environmental Sciences, Beijing, China
• School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, China
• Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
• International Research Center of Big Data for Sustainable Development Goals, Beijing, China

Short Summary

This study developed an integrated downscaling framework using GRACE observations and hydrological models to generate high-resolution groundwater storage anomaly (GWSA) estimates for the Sanjiang Plain. It found that while regional dry-wet conditions are the dominant drivers of GWSA dynamics, agricultural cropping pattern shifts, particularly paddy expansion in the eastern region, increasingly exert negative impacts on groundwater sustainability, with a critical threshold identified for maize-to-rice conversion.

Objective

• To develop a physically consistent downscaling approach to derive high-resolution groundwater storage anomaly (GWSA).
• To quantitatively assess the relationships among GWSA variations, climate change, and agricultural pattern shifts, with a focus on spatially explicit linkages between paddy field expansion and groundwater consumption.
• To determine quantitative thresholds for adjusting cropping structures to ensure groundwater sustainability.
• To propose recommendations for optimizing cropping patterns to balance food production and sustainable groundwater management.

Study Configuration

• Spatial Scale: Sanjiang Plain (SJP), Northeastern China, approximately 108,800 km². GRACE data at 0.5° resolution, downscaled GWSA at 1 km resolution. Other datasets at 0.1°, 500 m, and 1 km resolutions.
• Temporal Scale: January 2003 to December 2016 (14 years) for GRACE observations and groundwater-related data. Hydrological model simulations from 1982 to 2018.

Methodology and Data

• Models used:
  • Hydrological Model: Infiltration Excess and Saturation Excess Soil-Water Integration model (ESSI-3).
  • Downscaling Model: Geographically Weighted Regression (GWR).
  • Statistical/Attribution Models: Theil-Sen median slope estimator, Mann-Kendall (MK) test, Bayesian Estimator of Abrupt Change, Seasonality, and Trend (BEAST) algorithm, Partial Least Squares Structural Equation Modeling (PLS-SEM), Partial Least Squares Regression (PLSR).
  • Groundwater Sustainability Indices: GRACE Groundwater Drought Index (GGDI), Sustainability Index (SI).
  • Comparison Models: Noah and VIC models (from GLDAS), GLOBGM v1.0 (PCR-GLOBWB-MODFLOW global-scale groundwater model).
• Data sources:
  • Satellite Observations: GRACE Mascon datasets (JPL, CSR, GSFC) for Terrestrial Water Storage Anomaly (TWSA).
  • Reanalysis/Gridded Data: China Meteorological Forcing Dataset (CMFD) for meteorological variables (precipitation, temperature, etc.), GLOBMAP product for Leaf Area Index (LAI).
  • Land Use/Crop Data: Resource and Environment Data Center of the Chinese Academy of Sciences for land cover, ChinaCropArea1km for crop distribution, Heilongjiang Statistical Yearbook for crop planting areas.
  • Groundwater Data: Comprehensive Water Resources Investigation, Groundwater Level Almanac (China Geological Environment Monitoring Institute), Information Center of the Ministry of Water Resources, Water Resources Bulletin for groundwater levels, abstraction volumes, and depth records.
  • Model Outputs (for comparison/input): GLDAS (Noah, VIC) for soil moisture and snow water equivalent, GLOBGM v1.0 for groundwater table depth.

Main Results

• The integrated downscaling framework, driven by physically consistent ESSI-3 model data, generated high-resolution GWSA estimates with superior performance (correlation coefficient of 0.76, Nash-Sutcliffe Efficiency of 0.54) compared to GLDAS models and GLOBGM when validated against in-situ observations.
• Regional groundwater storage and sustainability in the SJP experienced an overall decline followed by a marked recovery, with an average upward trend of 1.50 ± 0.62 mm/year (p < 0.05) over the study period, but with distinct phase-specific dynamics.
• Shifts in regional dry-wet conditions (Standardized Precipitation Evapotranspiration Index, SPEI) were identified as the dominant driver of GWSA variability at the region-wide scale, with climatic factors shifting from a negative to a positive influence over time.
• Cropping pattern shifts, particularly the widespread conversion of dryland to paddy fields, exerted increasingly negative impacts on GWSA at the spatial scale, dominating 33.6 % of agricultural grids. This influence was most pronounced in the eastern SJP, driving sustained deterioration in local groundwater sustainability.
• Scenario simulations identified critical ecological thresholds for agricultural expansion:
  • Maize-only expansion: Sustainable groundwater balance (GWSA slope > 0) maintained if expansion remains below 4150 ± 1700 km².
  • Rice-only expansion: Sustainability threshold limited to below 1200 ± 500 km².
  • Concurrent expansion of both rice and maize: Total expansion of each crop must be limited to below 950 ± 380 km².
  • Crop substitution (maize to rice): A sustainable groundwater balance could be maintained if the net increase in rice cultivation remains below 1700 ± 700 km².

Contributions

• Developed a novel integrated downscaling framework that leverages physically consistent hydrological model data (ESSI-3) to enhance the spatial resolution and reliability of GRACE-derived GWSA, effectively minimizing cross-source integration errors.
• Provided a quantitative, spatially explicit assessment of the complex interactions and shifting pathways of influence between climatic variability, agricultural intensification (paddy expansion), and groundwater storage dynamics.
• Identified critical quantitative ecological thresholds for different cropping structure adjustments, offering actionable guidance for sustainable agricultural land-use planning.
• Offered solution-oriented insights and scientifically grounded recommendations for balancing regional food production goals with sustainable groundwater management, particularly emphasizing spatially differentiated strategies and water-saving irrigation techniques.

Funding

• Basic Scientific Research Fund of the Chinese Research Academy of Environmental Sciences (Grant No. 2024YSKY-15)
• National Natural Science Foundation of China (42101034)

Citation

@article{Xu2025Balancing,
  author = {Xu, Chi and Chen, Hao and Zhang, Wanchang and Wang, Shuhang and Fu, Zhenghui},
  title = {Balancing agricultural expansion and groundwater sustainability: Insights from GRACE and hydrological models},
  journal = {Agricultural Water Management},
  year = {2025},
  doi = {10.1016/j.agwat.2025.110039},
  url = {https://doi.org/10.1016/j.agwat.2025.110039}
}