Seasonal snow cover in mountainous regions represents a critical natural freshwater reserve for arid and semi-arid areas of Central Asia. This study evaluates the long-term (2000–2024) spatiotemporal dynamics of snow cover in the Arys River basin, located within the Western Tien Shan. The research utilizes daily satellite data from MODIS Terra and Aqua, along with data from the MODSNOW automated processing system. Terra-Aqua composite imagery was employed to minimize cloud cover effects. Satellite-derived estimates were validated against observational data from five meteorological stations of the Republican State Enterprise (RSE) “Kazhydromet”. The results indicate significant interannual variability in snow cover extent: the snow-covered area during the cold season ranged from 16.2% to 54.1%, with a mean value of 34.4%. Trend analysis revealed a weak negative trend, while Sen’s slope estimator showed an average annual reduction in snow cover area of 0.37% per year. The most pronounced decline in snow accumulation was observed in mid-elevation mountain zones. These findings suggest potential increased risks to seasonal water availability in the Arys River basin and, more broadly, across the Syr Darya basin under ongoing climate change conditions. The results provide a scientific basis for quantifying climate impacts and developing adaptation strategies for integrated water resources management in Central Asia.

The active development of the foothill areas of the Almaty agglomeration (Southeastern Kazakhstan) requires reliable methods for landslide susceptibility assessment. This study aims to identify the spatial association between landslide occurrence and selected environmental and anthropogenic factors using the Frequency Ratio (FR) method and geographic information systems. The analysis is based on an inventory of 157 landslides, the SRTM digital elevation model, Landsat imagery, WorldClim climate data, geological maps, and OpenStreetMap data. Ten conditioning factors were analyzed: elevation, slope, aspect, precipitation, lithology, distance to faults, rivers and roads, the Normalized Difference Vegetation Index (NDVI), and land use. FR values were calculated for each factor and integrated to produce a landslide susceptibility map. Model performance was evaluated using Receiver Operating Characteristic (ROC) analysis and the Area Under the Curve (AUC). The resulting susceptibility map identifies areas with different levels of landslide susceptibility and provides a scientific basis for sustainable land-use planning, engineering-geological investigations, safer infrastructure development, natural hazard assessment, and disaster risk reduction in rapidly developing foothill regions. By supporting risk-informed land-use decisions and targeted mitigation measures, the study contributes to the long-term environmental safety and resilience of the Almaty agglomeration.