Liang et al. (2025) Quantifying anthropogenic drivers of water storage decline to support sustainable water management in a coal-mining semi-arid region

Identification

• Journal: Agricultural Water Management
• Year: 2025
• Date: 2025-11-20
• Authors: Wei Liang, Ning Chen, Fen Gou, Yonghui Wang, Yingying Yao, Yihe Lü, Long‐Hai Wang, Jianwu Yan, Shuai Li
• DOI: 10.1016/j.agwat.2025.109993

Research Groups

• School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
• Institute of Global Environmental Change, Xi’an Jiaotong University, Xi’an, China
• Xinjiang Laboratory of Lake Environment and Resources in Arid Zone, Xinjiang Normal University, Urumqi, China
• State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
• Xi’an Surveying and Mapping Center, Xi’an, China

Short Summary

This study quantifies the anthropogenic drivers of terrestrial and groundwater storage decline in China's Mu Us Sandyland from 2003 to 2020 using a water balance framework, finding that ecological restoration and irrigation are the primary drivers, with coal mining also significant in energy-intensive areas, and proposes spatially differentiated management strategies for future sustainability.

Objective

• Quantify the spatiotemporal changes in terrestrial water storage (TWS) and groundwater storage (GWS) across Mu Us Sandyland (MUS) subregions for 2003–2020 by integrating GRACE satellite observations with a water-balance framework and local hydrological and statistical data.
• Attribute these changes to key anthropogenic drivers, including ecological restoration, socio-economic water use, and coal-mining.
• Project future groundwater supply–demand under multiple climate and socio-economic scenarios to develop sustainable groundwater management strategies that balance ecological restoration with water resource constraints.

Study Configuration

• Spatial Scale: Mu Us Sandyland (MUS) in northwestern China, covering Shaanxi (SX), Inner Mongolia (IM), and Ningxia (NX) provinces, including prefecture-level cities of Yulin, Ordos, Wuzhong, and Lingwu. Analysis conducted at regional and sub-regional scales.
• Temporal Scale: Historical period: 2003–2020 (216 months). Future projections: 2021–2050 (referred to as the 2030s).

Methodology and Data

• Models used:
  • Water balance framework
  • Singular spectrum analysis (for GRACE data gap reconstruction)
  • Improved water storage fluctuation method (for groundwater recharge estimation)
  • Eckhardt digital filter method (for baseflow estimation)
  • Monte Carlo simulation (for uncertainty assessment)
  • Lund–Potsdam–Jena managed land model (LPJmL) (for irrigation demand and future groundwater discharge projections)
  • Multiplicative adjustment method (for bias correction of LPJmL simulations)
• Data sources:
  • GRACE/GRACE-FO mascon solutions (JPL-M, CSR-M, GSFC-M) for TWS anomalies.
  • ERA5-Land reanalysis data for soil moisture storage anomalies and runoff.
  • Statistical Yearbooks of prefecture-level cities for coal transportation data.
  • Municipal water resources planning reports and previous studies for coal drainage coefficients.
  • Peng et al. (2019) dataset for annual precipitation (1 km spatial resolution).
  • Previous simulations (Liang et al., 2020a; Gao et al., 2024) and land use dataset (Xu et al., 2025b) for natural vegetation evapotranspiration.
  • Water resources bulletins of various regions for net consumptive water use (irrigation, industrial, domestic, Yellow River diversion).
  • Yellow River Water Resources Bulletin for validation of GRACE-derived groundwater storage changes.
  • Bias-corrected climate models under RCP scenarios (RCP2.6, 6.0, 8.5) from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) portal.
  • Zhang et al. (2025a) dataset for industrial and domestic water use projections under Shared Socioeconomic Pathways (SSPs: SSP1–2.6, SSP2–6.0, SSP5–8.5).
  • MODIS Normalized Difference Vegetation Index (NDVI).

Main Results

• Terrestrial Water Storage (TWS) and Groundwater Storage (GWS) in the MUS declined at annual rates of 5.5 mm yr⁻¹ and 3.9 mm yr⁻¹, respectively, from 2003 to 2020.
• Neglecting coal mass loss in GRACE-based assessments leads to overestimations of TWS and GWS declines by 37.2 % and 44.3 %, respectively.
• Ecological restoration and agricultural irrigation jointly account for approximately 80 % of the observed water loss.
• In energy-intensive zones, mine dewatering was a significant anthropogenic driver of GWS declines (4.1 mm yr⁻¹), with an impact greater than that of irrigation (3 mm yr⁻¹).
• The estimated annual average groundwater recharge was 35.1 mm yr⁻¹, representing about 10 % of the mean annual precipitation.
• Ecological restoration caused an average groundwater depletion of 26.9 mm yr⁻¹ (95 % confidence interval: 12.5–41.2 mm yr⁻¹).
• Future projections (2021–2050) indicate that regional groundwater recharge increases (12.8 %–17.1 %) are expected to outpace total groundwater demand growth (2.2 %–7.6 %).
• This regional balance suggests potential for an additional 13.8 %–18.6 % expansion of ecological restoration.
• However, spatial heterogeneity necessitates differentiated strategies: some sub-areas (e.g., Shaanxi) may require a 2.8 %–13.7 % reduction in ecological restoration, while others (e.g., Inner Mongolia under SSP1–2.6) could expand by up to 19.1 %.

Contributions

• First study to systematically correct GRACE-derived TWS and GWS for coal mass loss, preventing significant overestimation of water storage declines (37.2 % for TWS, 44.3 % for GWS).
• Incorporated administrative-scale mine dewatering estimates, improving the accuracy of spatial heterogeneity in mining impacts compared to previous uniform coefficient approaches.
• Provided a comprehensive, multi-factor attribution of TWS and GWS changes, quantitatively assessing the individual contributions of ecological restoration, socio-economic water use, and coal mining.
• Integrated coal development plans into multi-scenario simulations of future groundwater supply-demand dynamics, yielding spatially differentiated, management-ready insights for adaptive ecological restoration strategies.
• Offers a transferable framework for integrated land- and water-use planning to support sustainable water management in other semi-arid, resource-intensive regions globally.

Funding

• National Natural Science Foundation of China (Grant No. 42571148)
• National Key Research and Development Program of China (2023YFF1305100)
• Key Research and Development Program of Shaanxi (2024SF-YBXM-589)

Citation

@article{Liang2025Quantifying,
  author = {Liang, Wei and Chen, Ning and Gou, Fen and Wang, Yonghui and Yao, Yingying and Lü, Yihe and Wang, Long‐Hai and Yan, Jianwu and Li, Shuai},
  title = {Quantifying anthropogenic drivers of water storage decline to support sustainable water management in a coal-mining semi-arid region},
  journal = {Agricultural Water Management},
  year = {2025},
  doi = {10.1016/j.agwat.2025.109993},
  url = {https://doi.org/10.1016/j.agwat.2025.109993}
}