Lü et al. (2026) Diagnosing the Causal Relationships between Groundwater Resource Characteristics and Socio-economic Factors in the Heihe River Basin, China

Identification

• Journal: Water Cycle
• Year: 2026
• Date: 2026-01-01
• Authors: Zheng Lü, Dehui Ning, Chunying Shen, Juan Bai, Yanghua Zhang, Xiaokang Kou, Shasha Meng
• DOI: 10.1016/j.watcyc.2026.01.004

Research Groups

• Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming, China
• China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, China Geological Survey, Beijing, China
• School of Architecture and Urban Planning, Shandong Jianzhu University, Jinan, China
• School of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang, China
• School of Geography, Faculty of Geographical Science, Beijing Normal University, Beijing, China

Short Summary

This study maps high-resolution Groundwater Response Time (GRT) and Water Table Ratio (WTR) in the Heihe River Basin to diagnose causal relationships with socio-economic factors, revealing that groundwater characteristics largely constrain human activities, while agriculture uniquely reshapes groundwater response.

Objective

• To develop a novel framework integrating Groundwater Response Time (GRT) and Water Table Ratio (WTR) with Geographical Convergent Cross Mapping (GCCM) to diagnose causal relationships between groundwater resource characteristics and socio-economic factors in the Heihe River Basin, China.

Study Configuration

• Spatial Scale: Heihe River Basin (HRB), China, with all data standardized to a 0.005° grid resolution.
• Temporal Scale: Data ranges from 1965 to 2020 for some socio-economic variables (e.g., industrial water withdrawal, irrigated cropland), with analysis focusing on long-term cause-and-effect correlations and processes occurring over short to centennial time scales.

Methodology and Data

• Models used:
  • Groundwater Response Time (GRT) calculation.
  • Water Table Ratio (WTR) calculation (nonlinearized form).
  • Geographical Convergent Cross Mapping (GCCM) for causal inference.
• Data sources:
  • Digital Elevation Models (DEMs): Qilian Mountain Area dataset (30 m resolution).
  • River network: Aliyun DataV-GeoAtlas dataset.
  • Porosity and Hydraulic conductivity: Global HYdrogeology MaPS (GLHYMPS) dataset.
  • Precipitation: Monthly air temperature and precipitation dataset for China (0.025° resolution).
  • Aridity index: Global ET0 and Aridity Index Database v3 (30 arc-seconds, ~0.0083° resolution).
  • Vadose zone thickness: Global 1-km Gridded Thickness of Soil, Regolith and Sedimentary Deposit Layers (30 arc-seconds, ~1 km resolution).
  • Köppen-Geiger climate classifications.
  • Water table depth data.
  • Human modification data: Global Human Modification Gradient Map.
  • Agricultural data: CIrrMap250 (annual map of irrigated cropland in China from 2000 to 2020).
  • Ranching data: Anthropogenic Land-Use Estimates for the Holocene (HYDE 3.2).
  • Industry data: High-Resolution Mapping of Monthly Industrial Water Withdrawal in China (1965-2020).
  • Population density: WorldPop Hub.
  • GDP: Resource and Environmental Science Data Platform.
  • All datasets reprojected to EPSG:4326 (WGS 84) and resampled to a 0.005° grid resolution.

Main Results

• The average Groundwater Response Time (GRT) in the Heihe River Basin (HRB) is approximately 2.4 × 10^8 years, with 84.34% of the basin exhibiting response times exceeding 1000 years.
• The HRB is predominantly recharge-controlled (62% with Water Table Ratio (WTR) < 1), meaning groundwater behavior is primarily driven by climatic factors, while 38% is topography-controlled (WTR > 1).
• Both GRT and WTR show a co-increasing trend with water table depth; shallow water table areas (<1 meter) are mainly recharge-controlled, whereas deeper water table areas (>10 meters) are more topography-controlled.
• Robust unidirectional causal relationships were identified from groundwater properties to human activities: GRT influences overall human modification (ρ = 0.88) and ranching (ρ = 0.80), and WTR influences overall human modification (ρ = 0.78) and ranching (ρ = 0.68).
• Agriculture uniquely exhibits a reverse unidirectional causality, driving changes in GRT (Agriculture → GRT, ρ = 0.61), likely due to irrigation practices altering aquifer response.
• Population density correlates moderately with GRT (ρ = 0.55) and WTR (ρ = 0.56), with groundwater characteristics influencing population distribution more significantly than vice versa. GDP shows weaker causal links with both GRT and WTR.
• Local GRT/WTR maps for the HRB exhibit higher variability and more pronounced extremes compared to global datasets, highlighting the importance of localized hydrological conditions and human activities.

Contributions

• Provides a novel framework integrating Groundwater Response Time (GRT), Water Table Ratio (WTR), and Geographical Convergent Cross Mapping (GCCM) for diagnosing socio-hydrological coupling.
• Quantifies asymmetric causal feedbacks between groundwater systems and anthropogenic factors, offering a robust template for understanding human-water interactions in complex basin systems.
• Demonstrates that groundwater regimes act as structural constraints on socio-economic spatial organization, while agriculture can actively reshape groundwater memory.
• Proposes a transferable, risk-stratified groundwater management framework based on GRT/WTR hydro-response regimes, distinguishing between recharge-responsive zones (adaptive management) and topography-controlled zones (restrictive zoning).
• Highlights the importance of causal inference for designing sustainable, regionally tailored groundwater policies in arid and semi-arid basins.

Funding

• National Natural Science Foundation of China (52069009)
• Science and Technology Innovation Team for Integrated Management of Highland Rivers and Lakes in Intra-basin Water Diversion and Transfer Project of Yunnan Provincial Department of Education (202304003)

Citation

@article{Lü2026Diagnosing,
  author = {Lü, Zheng and Ning, Dehui and Shen, Chunying and Bai, Juan and Zhang, Yanghua and Kou, Xiaokang and Meng, Shasha},
  title = {Diagnosing the Causal Relationships between Groundwater Resource Characteristics and Socio-economic Factors in the Heihe River Basin, China},
  journal = {Water Cycle},
  year = {2026},
  doi = {10.1016/j.watcyc.2026.01.004},
  url = {https://doi.org/10.1016/j.watcyc.2026.01.004}
}