Li et al. (2026) Spatiotemporal evolution and attribution analysis of groundwater drought in the North China Plain: GGDI constructed based on downscaled GRACE GWSA

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2026
• Date: 2026-01-07
• Authors: Yijun Li, Xueting Zhong, Huili Gong, Beibei Chen, Chaofan Zhou, Hao Li, Xincheng Wang, Lewei Xu
• DOI: 10.1016/j.ejrh.2026.103103

Research Groups

• Key Laboratory of the Ministry of Education Land Subsidence Mechanism and Prevention, Capital Normal University, Beijing, China.
• College of Resource Environment and Tourism, Capital Normal University, Beijing, China.
• Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing, China.
• School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, China.

Short Summary

This study develops a high-resolution (0.05°) groundwater drought assessment framework for the North China Plain by downscaling GRACE satellite data, revealing a significant storage decline of -17.81 mm/yr and identifying anthropogenic extraction as the primary driver of drought.

Objective

• To enhance the spatial resolution of GRACE-derived Groundwater Storage Anomalies (GWSA) using Geographically Weighted Regression (GWR) for precise regional drought identification.
• To quantitatively characterize the spatiotemporal evolution of groundwater drought and attribute its causes to natural and anthropogenic factors.

Study Configuration

• Spatial Scale: North China Plain (NCP), China (approximately 140,000 km²).
• Temporal Scale: 2002–2023 for spatiotemporal evolution; 2003–2022 for attribution analysis.

Methodology and Data

• Models used: Geographically Weighted Regression (GWR) for spatial downscaling (from 0.25° to 0.05°); Water balance equation for GWSA extraction; Random Forest (RF) and Geographic Detector (GD) for attribution; Singular Spectrum Analysis (SSA) and Theil-Sen for trend analysis; Multi-threshold run theory for drought event identification.
• Data sources: GRACE/GRACE-FO Mascon products (CSR, JPL, GSFC); GLDAS land surface models (NOAH, CLSM, VIC); CHIRPS precipitation data; MODIS products (LST, NDVI, ETa); WaterGAP hydrological model; Provincial Water Resources Bulletins; Ground-based monitoring well data for validation.

Main Results

• Storage Trends: The downscaled 0.05° GWSA revealed a significant decline rate of -17.81 ± 3.31 mm/yr between 2002 and 2023, showing higher accuracy (r = 0.83) than original coarse-resolution data.
• Drought Characteristics: 15 distinct groundwater drought events were identified, exhibiting increasing frequency and intensity over the study period. Drought was generally mild in the northeast and severe in the southwest.
• Localized Recovery: High-resolution data detected drought relief in approximately 4% of the region (e.g., northern Beijing and northwestern Cangzhou) following 2016, attributed to the South-to-North Water Diversion Project (SNWDP) and groundwater-withdrawal restrictions.
• Attribution: Groundwater extraction was the dominant driver of drought (45% contribution). The interaction between extraction and precipitation significantly amplified drought risk (q-value = 0.83), particularly in fine-grained aquifer zones.

Contributions

• Methodological Advancement: Overcomes the spatial limitations of GRACE data by providing a 0.05° high-resolution framework for regional groundwater drought monitoring.
• Mechanistic Interpretation: Quantitatively separates the impacts of human activities from natural climate variability, highlighting how policy interventions (like the SNWDP) and extraction controls influence regional water recovery.
• Precision Monitoring: Identifies localized "drought relief" zones that were previously obscured by coarse-resolution datasets, providing a scientific basis for zoned groundwater management.

Funding

• National Natural Science Foundation of China (Reference codes: U24A20433, 42371081/D0104, 42371089/D0104, 42201081/D0104).

Citation

@article{Li2026Spatiotemporal,
  author = {Li, Yijun and Zhong, Xueting and Gong, Huili and Chen, Beibei and Zhou, Chaofan and Li, Hao and Wang, Xincheng and Xu, Lewei},
  title = {Spatiotemporal evolution and attribution analysis of groundwater drought in the North China Plain: GGDI constructed based on downscaled GRACE GWSA},
  journal = {Journal of Hydrology Regional Studies},
  year = {2026},
  doi = {10.1016/j.ejrh.2026.103103},
  url = {https://doi.org/10.1016/j.ejrh.2026.103103}
}

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