Groundwater plays a vital role in sustaining dryland ecosystems, yet our understanding of the spatiotemporal dynamics of groundwater–vegetation interactions in endorheic river basins remains limited. In this study, the covariation between the normalized difference vegetation index (NDVI) and water table depth (WTD) in the Heihe River Basin (HRB), a representative endorheic system, is investigated via multisource data and generalized additive models (GAMs). The results indicate that the NDVI peaks in summer (July), with a corresponding decline in the WTD, indicating a basin-wide negative correlation. Spatial analysis reveals distinct upstream–downstream gradients: upstream regions exhibit strong seasonal synchronization, whereas midstream and downstream areas show weaker correlations because of mixed surface and groundwater influences. Landcover and climate significantly affect these interactions, with arid zones showing the strongest negative correlations (ρ = −0.38), particularly in wetlands, whereas humid regions show nonsignificant relationships. Geomorphological analysis highlights stronger correlations in mountainous areas than in low-relief plains. Positive correlations are the most prevalent in arid regions (54.5%), followed by hyper-arid regions (28.9%), while negative correlations also dominate arid regions (54.6%), followed by semiarid regions (27.6%). Cross-correlation analysis reveals synchronous NDVI–WTD changes at 95% of the grid points, with 5% exhibiting time lags (1–3 months), indicating localized hydrogeological feedback. Notably, 32% of the zones with negative correlations overlap with groundwater-dependent ecosystems (GDEs). GAM analysis reveals that 87.9% of the spatial variability in the NDVI–WTD correlations is attributed to environmental factors, with climate (26.6%) and hydrogeology (19.5%) as the dominant contributors. These findings provide critical insights into groundwater–vegetation interactions in arid ecosystems and offer valuable implications for sustainable water resource management.

Groundwater systems are intrinsically linked to climate, with changing conditions significantly altering recharge, storage, and discharge processes, thereby impacting water availability and ecosystem integrity. Critical knowledge gaps persist regarding groundwater equilibrium timescales, water table dynamics, and their governing factors. This study develops a novel remote sensing framework to quantify factor controls on groundwater–climate interaction characteristics in the Heihe River Basin (HRB). High-resolution (0.005° × 0.005°) maps of groundwater response time (GRT) and water table ratio (WTR) were generated using multi-source geospatial data. Employing Geographical Convergent Cross Mapping (GCCM), we established causal relationships between GRT/WTR and their drivers, identifying key influences on groundwater dynamics. Generalized Additive Models (GAM) further quantified the relative contributions of climatic (precipitation, temperature), topographic (DEM, TWI), geologic (hydraulic conductivity, porosity, vadose zone thickness), and vegetative (NDVI, root depth, soil water) factors to GRT/WTR variability. Results indicate an average GRT of ~6.5 × 10⁸ years, with 7.36% of HRB exhibiting sub-century response times and 85.23% exceeding 1000 years. Recharge control dominates shrublands, wetlands, and croplands (WTR < 1), while topography control prevails in forests and barelands (WTR > 1). Key factors collectively explain 86.7% (GRT) and 75.9% (WTR) of observed variance, with spatial GRT variability driven primarily by hydraulic conductivity (34.3%), vadose zone thickness (13.5%), and precipitation (10.8%), while WTR variation is controlled by vadose zone thickness (19.2%), topographic wetness index (16.0%), and temperature (9.6%). These findings provide a scientifically rigorous basis for prioritizing groundwater conservation zones and designing climate-resilient water management policies in arid endorheic basins, with our high-resolution causal attribution framework offering transferable methodologies for global groundwater vulnerability assessments.

Urbanization in mountainous regions alters hydrologic systems, yet the spatial patterning of residential (RA) and non-residential (NRA) areas in response to hydrologic constraints remains poorly quantified. In this study, we analyzed how such constraints shaped the distinct locational logic of RA and NRA expansion in the mountainous Kunming Core Region (KCR), Southwest China, from 1975 to 2020. Using the Global Human Settlement Layer (GHS-BUILT-S) built-up fraction data and its functionally classified RA and NRA layers at 100 m resolution, we quantified multi-decadal urban land changes via regression and centroid migration analyses. Six hydrologic factors, namely altitude, slope, surface roughness, distance to river (DTR), depth to water table (DTWT) and vegetation root depth (VRD), were derived from global terrain, groundwater, and rooting depth datasets, and harmonized to a common grid. Results show a two-phase urbanization pattern: moderate, compact growth before 1995 followed by rapid, near-exponential expansion, dominated by RA. RA consistently clustered in hydrologically favorable zones (low–moderate roughness, mid-altitudes, lower slopes, proximal rivers, shallow–moderate DTWT, moderate VRD), whereas NRA expanded into more hydrologically variable terrain (higher roughness, intermediate DTR, deeper DTWT, higher altitudes, deeper VRD). Contribution-weighting analysis revealed a temporal shift in dominant drivers: for RA, from river proximity and slope in 1975 to terrain roughness in 2020; for NRA, from vegetation root depth and moderate topography to root depth plus altitude. Geographic centroids of both RA and NRA migrated northeastward, indicating coordinated yet functionally distinct peri-urban and corridor-oriented growth. These findings provide a hierarchical, factor-based framework for integrating hydrologic constraints into risk-informed land-use planning in topographically complex basins.

Groundwater provides an essential buffer against hydroclimatic variability in monsoon-influenced regions, yet its long-term dynamics and interactions with human activities remain poorly constrained in complex hydrogeological settings such as Southwest China (SWC). This study integrates outputs from the high-resolution PCRaster Global Water Balance model (PCR-GLOBWB) with spatial statistics to examine temporal evolution, spatial heterogeneity, and anthropogenic influences on Water Table Depth (WTD) from 1958 to 2015. Results reveal a persistent long-term rise in groundwater levels (i.e., a decline in WTD) at a Sen's slope of –0.0285 m/y, with episodic drawdowns during drought years and only partial recovery in subsequent wet periods. Seasonal oscillations remain pronounced, with the shallowest water tables occurring in late summer and the deepest in spring, although long-term depletion suggests that natural recharge is insufficient to balance cumulative extraction. Shallow aquifers (5 m) are increasingly buffered and display inverse relationships, reflecting delayed recharge processes. Spatial patterns demonstrate strong heterogeneity across climate zones, geomorphic units, land cover types, and aquifer types: Shallow groundwater is concentrated in semi-arid climates, lowland plains, and urban areas, whereas mountainous regions, undeveloped land, and discontinuous carbonate aquifers sustain deeper and more variable WTDs. Anthropogenic stress further modulates these distributions, with bivariate LISA analysis identifying High–High clusters (intensive human modification and deep water tables) in the Chengdu Plain and central Yunnan, and Low–Low clusters in sparsely populated western highlands. A groundwater protection zoning framework derived from these results highlights shallow aquifers under intensive stress as priority areas for monitoring and regulation. These findings demonstrate the coupled influence of climate and human activity on groundwater variability and provide a practical basis for regionally targeted management strategies to enhance groundwater sustainability in SWC.

Anthropogenic activities are profoundly altering the terrestrial water cycle, yet a comprehensive understanding of their impact on surface soil moisture (SSM) at regional scales remains limited. This study investigates the spatiotemporal dynamics of SSM and its relationship with anthropogenic modification (OAM) across Southwest China from 2000 to 2017. We employed multi-year geospatial and statistical analyses, including kernel density estimation and boxplots, to examine the impacts of human activities on regional soil moisture patterns. The results revealed that SSM exhibited a slight long-term declining trend (Sen’s slope = −0.0009 m³/m³/year) but showed a notable recovery after 2011, while overall anthropogenic modification (OAM) intensified until 2010 before declining sharply by 2015. A statistically significant and systematic relationship was observed, with increasing OAM intensity corresponding to higher median SSM and reduced spatial variability, indicating a homogenizing effect of human activities. Critically, the impacts of detailed anthropogenic stressors were highly divergent: agricultural modification correlated with elevated SSM, whereas transportation infrastructure and energy-related activities exhibited a suppressive effect. These findings highlight the necessity of integrating high-resolution SSM and anthropogenic data into land-use planning and implementing stressor-specific management strategies, such as improving irrigation efficiency and developing infrastructure designs that minimize SSM suppression, to achieve sustainable water resource management in rapidly developing regions.