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.

Under the intensifying pressures of climate change and human activities, the characteristics of land-use types and landscape patterns are widely recognized to exert significant influences on river water quality. Nevertheless, in dry-hot valley basins characterized by fragile ecological conditions and frequent geological hazards, the responses of river water quality to changes in landscape characteristics under the combined effects of natural disasters and anthropogenic disturbances remain poorly understood. In the present study, the Xiaojiang River Basin, a typical dry-hot valley basin subjected to intensive anthropogenic activities and frequent geological hazards, was selected. Through the integration of landscape pattern indices analysis and redundancy analysis, the spatial and temporal variations in river water quality in the Xiaojiang River Basin were quantified, and the effects of land-use types and landscape patterns on river water quality were systematically elucidated. Results showed that (1) the key water quality indexes such as total phosphorus, total nitrogen, ammonia nitrogen and COD in the Xiaojiang River Basin were shown as flood season > non-flood season; for example, the average TN increased from 1.37 mg/L (non-flood season) to 2.90 mg/L (flood season), and the average COD increased from 3.24 mg/L to 15.98 mg/L. In contrast, DO decreased from 8.07 mg/L (non-flood season) to 6.72 mg/L (flood season), and conductivity decreased from 561.4 µs/cm to 480.90 µs/cm. (2) Spatially, these key water quality indicators were shown as hazard-prone area > residential area > cultivated land area. (3) The larger the area of the debris flow trace areas, the greater the fluxes of nitrogen and phosphorus in the tributaries and the main stream in the flood season, and the worse the water quality of the river; after heavy rainfall, the fluxes of key water quality indicators generally showed a geometric multiple increase, with average growth rates of 1.95 (TP), 2.41 (TN), 2.34 (NH₃-N) and 4.74 (COD), respectively. (4) The ability of landscape patterns in flood season to explain the change in water quality is better than that in non-flood season. On different spatial scales, in the down-stream hazard-prone areas, upstream residential areas and cultivated land areas, the changes in river water quality indicators were mainly affected by landscape pattern indicators such as PD_hazard-influenced areas, IJI_residential areas and DIV_cultivated land. Our results can provide scientific guidance for the soil and water conservation practice, ecological restoration, and land-use management in the dry-hot valley of Southwest China and the water environment protection of the Baihetan Reservoir area.

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.