This study presents a comprehensive assessment of land use land cover (LULC) dynamics and their influence on tourism development potential in the Konaev city (south eastern Kazakhstan) region, based on multi-temporal analysis of Sentinel-2 satellite imagery for 2017, 2024, and a projected scenario for 2030. The findings reveal substantial landscape transformation driven by urban expansion and agricultural intensification ? evidenced by a sharp decline in grasslands (from 53% to 35%) and wetlands (from 0.7% to 0.2%), and a significant increase in croplands (from 1% to 14%) and built-up areas (from 10% to 18%). A spatially weighted tourism suitability analysis identified three strategic development directions: ecotourism (39.2%), aquatic tourism (36.7%), and urban-cultural tourism (20.1%). While the region demonstrates high tourism potential, the ongoing degradation of natural ecosystems presents critical challenges to sustainability. These trends emphasize the urgent need for integrated land-use planning that aligns tourism growth with ecosystem preservation. The study concludes that sustainable tourism in the Konaev city requires a science-informed, multisectoral approach balancing environmental stewardship with infrastructure development and service quality enhancement. Such a framework can ensure resilient, diversified tourism growth and contribute meaningfully to regional economic and ecological sustainability.

Understanding the interactions among mountain snow resources, river discharge, and irrigated agriculture is essential for sustainable water management in transboundary river basins of Central Asia. This study evaluated the relationships among high-elevation snow conditions, hydroclimatic factors, summer river discharge, and agricultural vegetation dynamics in the transboundary Chu River Basin during 2001–2025 using MODIS snow-cover, snow-persistence, and NDVI products together with meteorological and hydrological observations. The results showed that snow cover was widespread during winter but declined substantially during spring, while the Mann–Kendall analysis indicated that no statistically significant trend predominated across most of the high-elevation snow zone, although significant decreases in snow persistence occurred across 12.83% of the analyzed area. For summer cropland NDVI, 61.15% of the analyzed area showed no significant trend, while significant decreases and increases occurred across 26.24% and 12.62%, respectively. Spring temperature exhibited a significant negative correlation with snow persistence (r = −0.64, p < 0.001), indicating the sensitivity of mountain snow resources to warming conditions. Summer river discharge was strongly correlated with summer precipitation (r = 0.77, p < 0.0001), vegetated cropland area (r = 0.76, p < 0.0001), and mean summer NDVI (r = 0.69, p < 0.001). In addition, snow persistence showed a significant positive relationship with summer river discharge (r = 0.63, p < 0.001), vegetated cropland area (r = 0.52, p = 0.008), and mean summer NDVI (r = 0.42, p = 0.036), suggesting a linkage between high-elevation snow conditions, seasonal water availability, and downstream agricultural vegetation. Canonical correlation analysis further revealed a strong multivariate association between hydroclimatic and hydroagricultural variables (Rc = 0.900, Rc² = 0.810). Overall, the findings indicate significant statistical linkages among climate conditions, snow resources, river discharge, and irrigated agriculture, providing a scientific basis for water-resource management and climate-change adaptation in transboundary mountain-fed basins.