Abstract
Soil salinization poses a significant threat to agricultural productivity and environmental sustainability, particularly in arid and semi-arid regions. This study presents a comprehensive spatiotemporal analysis of soil salinity dynamics in irrigated lands of Alakol District, Zhetisu Region, Kazakhstan, using multi-temporal Sentinel-2 satellite imagery and the Normalized Difference Salinity Index (NDSI). The analysis covered the 2024 growing season, from March to November, with one cloud-free image selected for each month. NDSI values were calculated monthly and classified into four salinity categories: non-saline, slightly saline, moderately saline, and highly saline. Field sampling at 31 locations provided electrical conductivity (EC) data for validation, enabling comparison between surface reflectance-based salinity estimates and ground measurements. The results demonstrated pronounced seasonal trends: NDSI values were lowest in spring due to leaching by precipitation and early irrigation, gradually increasing through summer as evaporation concentrated salts at the surface, and fluctuating in autumn depending on rainfall and drainage conditions. Spatially, fields situated in topographic depressions or near Lake Alakol exhibited the highest salinity levels, whereas upland areas remained relatively unaffected. Notably, no fields exceeded the moderate salinity threshold, indicating that while salinization is present, it remains in early stages. The NDSI approach proved effective for surface salinity detection, capturing both temporal fluctuations and spatial heterogeneity. These findings underscore the utility of remote sensing for operational salinity monitoring and highlight the importance of continuous observation to inform timely land management interventions. This study offers actionable insights for sustainable agriculture, particularly in tailoring irrigation and drainage strategies to mitigate salinity risks across vulnerable farmlands in Central Asia.