Glacial-lake outburst floods (GLOFs) threaten more than three million residents of south-east Kazakhstan, yet quantitative data on lake growth and storage are scarce. We inventoried 154 lakes on the northern flank of the Ile-Alatau and selected four moraine-dammed basins with the greatest historical flood activity for detailed study. Annual lake outlines (2016–2023) were extracted from 3 m PlanetScope imagery with a Normalised Difference Water Index workflow, while late-ablation echo-sounder surveys (2023–2024) yielded sub-metre bathymetric grids. A regionally calibrated area–volume power law translated each shoreline to water storage, and field volumes served as an independent accuracy check. The lakes display divergent trajectories. Rapid thermokarst development led to a 37% increase in the surface area of Lake 13bis, expanding from 0.039 km² to 0.054 km² over a 5-year period. In contrast, engineering-induced drawdown resulted in a 44% reduction in the area of Lake 6, from 0.019 km² to 0.011 km². Lakes 5 and 2, which are supplied by actively retreating glaciers, exhibited surface area increases of 4.8% and 15%, expanding from 0.077 km² to 0.088 km² and from 0.061 km² to 0.070 km², respectively. The empirical model reproduces field volumes to within ±25% for four lakes, confirming its utility for rapid hazard screening, but overestimates storage in low-relief basins and underestimates artificially drained lakes. This is the first study in Ile-Alatau to fuse daily 3 m multispectral imagery with ground-truth bathymetry, delivering an 8-year, volume-resolved record of lake evolution. The results identify Lake 5 and Lake 2 as priority targets for early-warning systems and demonstrate that sustained intervention can effectively suppress GLOF risk. Incorporating these storage trajectories into regional disaster plans will sharpen evacuation mapping, optimise resource allocation, and inform transboundary water-hazard policy under accelerating climate change.

Digital Elevation Models (DEMs) are a key tool for hydrological modeling and water resource analysis, enabling more accurate assessment of runoff processes, precipitation distribution, and flood risks. This study presents a comparative analysis of four global DEMs: Airbus WorldDEM4Ortho, ALOS AW3D, SRTM, and ASTER GDEM, aimed at evaluating their accuracy and practical applicability across different landscape conditions, including mountainous and flat terrains. To assess model quality, state geodetic points with high-precision elevation control and topographic maps were used, providing a reliable reference for comparison. Additionally, river networks extracted from the DEMs were compared with reference data obtained from Landsat 8 and Sentinel 2 satellite imagery, allowing verification of hydrological representation accuracy. The results indicate that Airbus WorldDEM4Ortho demonstrates the highest vertical accuracy and offers a more detailed and accurate representation of river networks due to its high spatial resolution and quality source data. The ALOS AW3D model showed comparable accuracy and hydrological reproduction, making it a worthy alternative. Meanwhile, the SRTM and ASTER GDEM models exhibit noticeable deviations, especially in flat areas, reducing their suitability for detailed hydrological modeling. Nevertheless, SRTM remains widely used due to its free accessibility, stability, and sufficient accuracy for large-area analyses. In contrast, ASTER GDEM is less suitable for high-resolution and detailed hydrological analysis tasks. This study emphasizes the critical importance of selecting the appropriate DEM based on terrain type and specific hydrological analysis goals, as this significantly impacts the quality of risk assessment related to water resource management and engineering planning

River runoff depends directly on climate conditions (e.g., temperature, precipitation and evapotranspiration), which affect water balance at the watersheds scale. The present work was conducted to investigate the impact of climate change on runoff in the Syrdarya River Basin, Central Asia. To assess the impact of climatic variation on runoff, the temporal trends of runoff were explored using the sensitivities of runoff to precipitation, temperature and potential evapotranspiration, and the aridity index was evaluated with the modified method of climate elasticity. The results showed that the average coefficients of sensitivity of runoff to precipitation and potential evapotranspiration were 2.4 and -1.4, and the sensitivity to temperature was -0.8 respectively, indicating that a 10% increase in precipitation or potential evapotranspiration would lead to a 24% increase or a 14% decrease in runoff, respectively. Additionally, the average coefficient of sensitivity of runoff to the aridity index varied from 0.65 to 2.8. The average coefficients of the sensitivity of runoff to climatic variation appeared to have an inverse relationship with the runoff coefficient, showing that the lower the river flow of the basin became, the more sensitive the runoff would be with respect to climatic variation. The results confirm the high sensitivity of river runoff in the Syrdarya River Basin to climatic changes. Precipitation was identified as the dominant factor controlling runoff formation, whereas an increase in potential evapotranspiration contributes to a reduction in basin water availability. The obtained estimates can be used to project future changes in regional water resources under changing climatic conditions.