The growing volume of construction and demolition waste has made discarded concrete a major source of urban solid waste, placing increasing pressure on land resources and the environment. Recycling waste concrete into recycled aggregate concrete (RAC) offers an effective solution for resource conservation and carbon reduction, aligning with the goals of sustainable development. However, due to the residual mortar, high porosity, and microcracks of recycled aggregates, RAC generally exhibits lower compactness, strength, and durability than conventional concrete, particularly under freeze–thaw conditions where degradation accelerates and service life decreases. To address these challenges, this study investigates the optimization of RAC mix design and its frost resistance performance for pavement base applications. An orthogonal experimental design was employed, with the water-to-binder ratio, recycled aggregate replacement ratio, and air-entraining agent dosage as key variables, while 7-day compressive strength, permeability coefficient, and rebound modulus served as evaluation indices. The influence and interaction of these factors were analyzed to determine an optimal mix meeting both mechanical and durability requirements. Rapid freeze–thaw cycling tests were then conducted to examine the variations in mass loss, relative dynamic modulus, and compressive strength retention, followed by exponential and damage variable modeling to characterize the degradation process. Results show that the water-to-binder ratio primarily governs strength, the replacement ratio affects stiffness and permeability, and the air-entraining agent significantly enhances frost resistance by improving pore structure. The optimized mix retained over 70% of its relative dynamic modulus after 300 freeze–thaw cycles, exhibiting superior durability. This work establishes a systematic framework for multi-factor optimization and durability evaluation of RAC, providing theoretical and practical guidance for its application in cold-region pavement bases.

Soil moisture (SM) in the mountains is critical for agropastoral productivity, and it is subject to both large-scale climate gradients and fine-scale effects of terrain, vegetation and soil. However, how the climate, topography, soil and vegetation factors impact surface SM spatiotemporal dynamics remains elusive in mountainous terrains, due to their complex interactions. Based on multi-source datasets, this study employs the structural equation model to investigate the impact pathways of climate and vegetation factors on annual surface SM dynamics from the year 2000 to 2022 in the Tianshan Mountains of China (TS). We also utilize the factor and interaction detectors of Geographical Detector to explore the individual and interactive effects of climate, topography, soil and vegetation factors on the spatial pattern of the annual surface SM. Moreover, their integrated impacts on the spatiotemporal dynamics of annual surface SM were investigated based on the explanatory power from the factor detector and total effects from structural equation modeling. The results showed that the multi-year average surface SM was 0.21 m³·m⁻³ for the whole region, with greater values in areas with dense vegetation and high elevation. Annual surface SM exhibited significant increasing trends across different land cover classifications and elevation zones, which was directly influenced by vegetation greenness enhancement. Precipitation (PRE) and relative humidity (RH) also significantly influenced the temporal variations in surface SM through their indirect effect on vegetation greenness, while these indirect effects were much lower than the direct effect of vegetation greenness. RH, PRE and surface net solar radiation (SSR) showed strong individual and interactive effects on the spatial distribution of surface SM, particularly the interactive effects of RH and PRE with wind speed (WS). Surface SM was highly sensitive to RH and PRE in the central TS. Overall, vegetation greenness, PRE and RH were the main drivers of surface SM variations across both temporal and spatial scales, while SSR, total evaporation and WS primarily shaped its spatial distribution. These insights enhance our understanding of land–atmosphere interactions in mountainous areas and provide scientific references for sustainable agropastoral water resource management under global warming.