Abstract
Water scarcity during the growing season remains a major constraint for irrigated agriculture in Central Asia, particularly in transboundary river basins where water availability depends on mountain snow accumulation and melt processes. This study aims to assess how seasonal snow dynamics influence water availability in the Kuragaty sub-basin of the Shu river basin, with focus on downstream agricultural areas located in Kazakhstan and Kyrgyz Republic. Snow cover dynamics were derived from Sentinel-2 satellite imagery for elevations above 1000 m over the period from November to May, using a threshold-based snow detection approach. Evapotranspiration over agricultural lands was estimated from Landsat data using an energy balance model, while river discharge data from hydrometric stations were used to characterize the hydrological response. The results show a stable seasonal pattern of snow cover, with maximum extent observed in winter, where mean values exceed 55% and reach 59 ± 11.7% in December. In spring, snow cover rapidly decreases to 27.6 ± 12.7% in April and below 10% in May. The spring snow index (March-April) averages 37 ± 8.2%, reflecting strong interannual variability. Evapotranspiration follows a consistent seasonal cycle, increasing to 2.1 ± 0.6 mm/day in May and reaching peak values of up to 7.4 ± 1.2 mm/day in June. The total evapotranspiration during the growing season, averages 214.4 ± 24.2 mm. River discharge during this period shows moderate variability, with mean values of 4.26 ± 1.34 m3/s and peak flows occurring in early summer. A consistent positive relationship was observed between late-winter to early-spring snow cover and evapotranspiration during May-June, indicating that snowmelt contributes to water supply at the onset of the irrigation period. At the same time, evapotranspiration patterns are also influenced by vegetation development and increasing atmospheric demand, suggesting that snow dynamics act as an initial, but not the only, controlling factor.
01 Introduction
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02 References
- Adenova, D., Sarsekova, D., Absametov, M., Murtazin, Y., Sagin, J., Trushel, L., & Miroshnichenko, O. (2024). The Study of Groundwater in the Zhambyl Region, Southern Kazakhstan, to Improve Sustainability. Sustainability, 16(11), 4597. https://doi.org/10.3390/su16114597
- Al-Farabi Kazakh National University, & Safina, A. U. (2023). River runoff resources of the Shu-Talas water management basin in the context of climate change // Engineering Journal of Satbayev University, 145(3), 25–30. https://doi.org/10.51301/ejsu.2023.i3.04
- Adenova, D., Murtazin, E., Miroshnichenko, O., Sotnikov, E., & Tazhiev, S. (2025). Application of digital technologies in monitoring transboundary aquifers of the Shu–Talas basin // Izdenister Natigeler, (3(107)). https://doi.org/10.37884/3-2025/42
- Allen, R. G., Tasumi, M., & Trezza, R. (2007). Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Model // Journal of Irrigation and Drainage Engineering, 133(4), 380–394. https://doi.org/10.1061/(ASCE)0733-9437(2007)133:4(380)
- Chen, J., Tang, F., Lin, H., Huang, B., & Lin, X. (2026). Spatial Heterogeneity and Drivers of Vertical Error in Global DEMs: An Explainable Machine Learning Approach in Complex Subtropical Coastal Zones. Remote Sensing, 18(8), 1125. https://doi.org/10.3390/rs18081125
- Gascoin, S., Barrou Dumont, Z., Deschamps-Berger, C., Marti, F., Salgues, G., López-Moreno, J. I., Revuelto, J., Michon, T., Schattan, P., & Hagolle, O. (2020). Estimating Fractional Snow Cover in Open Terrain from Sentinel-2 Using the Normalized Difference Snow Index. Remote Sensing, 12(18), 2904. https://doi.org/10.3390/rs12182904
- Hao, X., Fan, X., Zhao, Z., & Zhang, J. (2023). Spatiotemporal Patterns of Evapotranspiration in Central Asia from 2000 to 2020. Remote Sensing, 15(4), 1150. https://doi.org/10.3390/rs15041150
- Kaliyeva, K., Punys, P., & Zhaparkulova, Y. (2021). The Impact of Climate Change on Hydrological Regime of the Transboundary River Shu Basin (Kazakhstan–Kyrgyzstan): Forecast for 2050. Water, 13(20), 2800. https://doi.org/10.3390/w13202800
- Koshim, A., Takibayev, Z., Gafurov, A., Munaitpassova, A., Kanatkaliyev, D., Bekzhanova, A., Zhumalipov, A., & Sharapkhanova, Z. (2026). Long-Term Spatiotemporal Dynamics of Snow Cover in the Arys River Basin (Western Tien Shan). Hydrology, 13(4), 115. https://doi.org/10.3390/hydrology13040115
- Kumar, N., & Hamouda, M. A. (2025). Utility of single-source surface energy balance models in estimation of daily actual evapotranspiration in arid regions // Hydrological Sciences Journal, 70(4), 664–686. https://doi.org/10.1080/02626667.2024.2446266
- Li, Z., Chen, Y., Li, Y., & Wang, Y. (2020). Declining snowfall fraction in the alpine regions // Central Asia. Scientific Reports, 10(1), 3476. https://doi.org/10.1038/s41598-020-60303-z
- Linke, S., Lehner, B., Ouellet Dallaire, C., Ariwi, J., Grill, G., Anand, M., Beames, P., Burchard-Levine, V., Maxwell, S., Moidu, H., Tan, F., & Thieme, M. (2019). Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution. Scientific Data, 6(1), 283. https://doi.org/10.1038/s41597-019-0300-6
- Ma, Y., & Zhang, Y. (2022). Improved on snow cover extraction in mountainous areas based on multi-factor ndsi dynamic threshold. The International Archives of the Photogrammetry // Remote Sensing and Spatial Information Sciences, XLIII-B3-2022, 771–778. https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-771-2022
- Narbayeva, К., Tairov, A., Ismailova, G., Narbayev, M., Mukhanbet, Y. (2025). Assessment of water resources in the shu-talas river basin // Hydrometeorology and Ecology, 117(2), 8–17. https://doi.org/10.54668/2789-6323-2025-117-2-8-17
- Singh, R., & Senay, G. (2015). Comparison of Four Different Energy Balance Models for Estimating Evapotranspiration in the Midwestern United States. Water, 8(1), 9. https://doi.org/10.3390/w8010009
- Yang, S., Chen, H., Zhang, Y., Shi, Q., Peng, B., Han, Y., & Hong, Z. (2026). Snow Density Retrieval Based on Sentinel-2 Multispectral Data and Deep Learning. Remote Sensing, 18(8), 1200. https://doi.org/10.3390/rs18081200
- Zhang, L., Guli∙Jiapaer, Yu, T., Liang, H., Lin, K., Ju, T., De Maeyer, P., & Van De Voorde, T. (2025). Evaluating the performance of snow depth reanalysis products in the arid region of Central Asia // International Journal of Digital Earth, 18(1), 2447368. https://doi.org/10.1080/17538947.2024.2447368