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Seasonal Sensitivity of Drought Indices in Northern Kazakhstan: A Comparative Evaluation and Selection of Optimal Indicators

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  • Laura Ryssaliyeva

    (Faculty of Geography and Environmental Sciences, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan)

  • Vitaliy Salnikov

    (Faculty of Geography and Environmental Sciences, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan)

  • Zhaohui Lin

    (International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China)

  • Zhanar Raimbekova

    (Faculty of Geography and Environmental Sciences, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan)

Abstract

Drought is one of the main climate-induced risks threatening agricultural sustainability in semi-arid regions. Northern Kazakhstan, a key grain-producing region in Central Asia, exhibits increasing vulnerability to droughts due to climatic variability and reliance on rainfed agriculture. This study evaluates the informativeness of drought indices based on the response of agricultural vegetation to dry conditions using remote sensing-based vegetation indices across Northern Kazakhstan from 1990 to 2024. Ground-based meteorological indices—the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Hydrothermal Coefficient (HTC), and the Modified China-Z Index (MCZI)—and vegetation indices—the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI), and the Vegetation Health Index (VHI)—were analyzed using data from 11 representative meteorological stations. For the first time in Kazakhstan, the MCZI was calculated, demonstrating high sensitivity to local climate variability and strong agreement with the VHI. The SPI, MCZI, and HTC showed strong seasonal correlations with vegetation indices, whereas the SPEI had a weak correlation, limiting its applicability. The highest correlations (r ≥ 0.82) between meteorological and vegetation indices were recorded in summer, while spring and autumn were influenced by phenological and temperature factors. Persistent drying trends in the southern and southwestern areas contrasted with moderate wetting in the north. The combined use of the SPI, MCZI, HTC, and VHI proved effective for monitoring droughts. The results provide a reproducible foundation for local drought assessment and early warning systems, supporting climate-resilient agricultural planning and sustainable land and water resource management. The results also offer actionable insights to enhance adaptation strategies and support long-term agricultural and environmental sustainability in Central Asia and similar continental agroecosystems.

Suggested Citation

  • Laura Ryssaliyeva & Vitaliy Salnikov & Zhaohui Lin & Zhanar Raimbekova, 2025. "Seasonal Sensitivity of Drought Indices in Northern Kazakhstan: A Comparative Evaluation and Selection of Optimal Indicators," Sustainability, MDPI, vol. 17(21), pages 1-25, October.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:21:p:9413-:d:1777799
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    References listed on IDEAS

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    1. Yuan Li & Yi Dong & Dongqin Yin & Diyou Liu & Pengxin Wang & Jianxi Huang & Zhe Liu & Hongshuo Wang, 2020. "Evaluation of Drought Monitoring Effect of Winter Wheat in Henan Province of China Based on Multi-Source Data," Sustainability, MDPI, vol. 12(7), pages 1-19, April.
    2. Tobias M. Erhardt & Claudia Czado, 2018. "Standardized drought indices: a novel univariate and multivariate approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 643-664, April.
    3. Stanislav E. Shmelev & Vitaliy Salnikov & Galina Turulina & Svetlana Polyakova & Tamara Tazhibayeva & Tobias Schnitzler & Irina A. Shmeleva, 2021. "Climate Change and Food Security: The Impact of Some Key Variables on Wheat Yield in Kazakhstan," Sustainability, MDPI, vol. 13(15), pages 1-23, July.
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