Diagnosing the causal relationships between groundwater resource characteristics and socio-economic factors in the Heihe river basin, China

Groundwater systems interact closely with socio-economic processes in arid basins. Quantifying these interactions requires spatial indicators that describe groundwater response and control mechanisms. This study maps high-resolution Groundwater Response Time (GRT) and Water Table Ratio (WTR) across the Heihe River Basin (HRB) using multi-source data. Results show an average GRT of 2.4 × 10 8 years. About 62% of the HRB is recharge-controlled (WTR < 1) and 38% is topography-controlled (WTR > 1). Both GRT and WTR increase with water table depth. Causal analysis using Geographical Convergent Cross Mapping (GCCM) identifies strong one-way causality from GRT to overall human modification (ρ = 0.88) and ranching (ρ = 0.80), and from WTR to both human modification (ρ = 0.78) and ranching (ρ = 0.68). Agriculture shows reverse causality with GRT (ρ = 0.61), indicating irrigation-induced changes in groundwater response. Population correlates moderately with both GRT and WTR (ρ = 0.55–0.56), while GDP exhibits weaker links. Comparison with global GRT/WTR maps shows that local hydrological variability is higher, reflecting finer-scale responses to land use and climate. The results demonstrate that groundwater regimes constrain socio-economic spatial organization, while agriculture can actively reshape groundwater memory in recharge-responsive zones. The framework provides a transferable approach for diagnosing socio-hydrological coupling and informing risk-stratified groundwater management across arid and semi-arid regions. • Groundwater response time (GRT) and water table ratio (WTR) mapped over Heihe Basin. • GRT–WTR co-variation links groundwater inertia with climate and water table depth. • Robust unidirectional causality found from groundwater properties to human modifications. • Local GRT/WTR maps show higher variability than global datasets. • GCCM provides a novel tool for diagnosing socio-hydrological causal relationships.