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Journals / Eurasian Journal of Soil Science / 2026 / Volume: 14 Issue: 3

Analysis of drought dynamics using SPI and SARIMA models: A case study of the Rostov Region, Russia

Vasiliy Gudko(Academy of Biology and Biotechnology, Southern Federal University, Rostov-on-Don, Russia)0000-0002-6212-5410
Sudeep Tanwar(Nirma University, SG Highway, Ahmedabad, 382481,Gujarat, India)0000-0002-1776-4651
Tatiana Minkina(Academy of Biology and Biotechnology, Southern Federal University, Rostov-on-Don, Russia)0000-0003-3022-0883
Svetlana Sushkova(Academy of Biology and Biotechnology, Southern Federal University, Rostov-on-Don, Russia)0000-0003-3470-9627
Alexander Usatov(Academy of Biology and Biotechnology, Southern Federal University, Rostov-on-Don, Russia)0000-0003-0600-7927
Kirill Azarin(Academy of Biology and Biotechnology, Southern Federal University, Rostov-on-Don, Russia)0000-0003-4876-3237
Irina Safronenkova(Institute of Computer Technologies and Information Security, Southern Federal University, Taganrog, Russia)0000-0002-9588-2194
Yaroslav Melnik(Institute of Computer Technologies and Information Security, Southern Federal University, Taganrog, Russia)0000-0002-2331-2010
Vadim Voloshchuk(Institute of Computer Technologies and Information Security, Southern Federal University, Taganrog, Russia)0009-0003-0336-9305
Coşkun Gülser(Ondokuz Mayıs University, Faculty of Agriculture, Department of Soil Science and Plant Nutrition, Samsun, Türkiye)0000-0002-6332-4876
Rıdvan Kızılkaya(Ondokuz Mayıs University, Faculty of Agriculture, Department of Soil Science and Plant Nutrition, Samsun, Türkiye)0000-0001-7475-9851
Pages
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Publication Date
2025-07-01
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Nonetheless, the SARIMA approach remains a valuable supplementary tool for anticipating precipitation dynamics and drought events.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Based on precipitation data from six weather stations covering the period 1960–2024, this study presents a retrospective analysis of drought dynamics in the Rostov Region, Russia, and evaluates the potential of the SARIMA model for forecasting moisture regime fluctuations.
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Key Findings & Data:Two key phases of crop development were analyzed: the vegetation initiation period (March–May), assessed using the three-month SPI of May (SPI-3), and the full active growing season (April–September), assessed using the six-month SPI of September (SPI-6).
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Conclusion & Impact:Nonetheless, the SARIMA approach remains a valuable supplementary tool for anticipating precipitation dynamics and drought events.
🔬Design:Modeling & Simulation
📍Scope:2024 Verileri
⚙️Variables:Drought forecasting · Standardized Precipitation Index (SPI) · SARIMA model

Abstract

Based on precipitation data from six weather stations covering the period 1960–2024, this study presents a retrospective analysis of drought dynamics in the Rostov Region, Russia, and evaluates the potential of the SARIMA model for forecasting moisture regime fluctuations. The Standardized Precipitation Index (SPI) was employed as the primary drought indicator. Two key phases of crop development were analyzed: the vegetation initiation period (March–May), assessed using the three-month SPI of May (SPI-3), and the full active growing season (April–September), assessed using the six-month SPI of September (SPI-6). The Mann-Kendall test revealed a non-significant positive trend in SPI-3 across all stations, while SPI-6 trends were non-significant and varied in direction. The highest frequency of drought events, based on both SPI-3 and SPI-6, occurred during 1960–1969, with a general decline in subsequent decades. The lowest drought frequency was observed during 2010–2019. Notably, the frequency of extreme droughts has shown an increasing trend, posing significant risks to agricultural productivity. Although SARIMA modeling proved useful for short-term forecasting, its application was limited by unrealistic long-term projections and deviations from climatic norms. Consequently, drought forecasts were restricted to a two-year horizon. Nonetheless, the SARIMA approach remains a valuable supplementary tool for anticipating precipitation dynamics and drought events.

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Cite This Article

Gudko, V., Tanwar, S., Minkina, T., Sushkova, S., Usatov, A., Azarin, K., Safronenkova, I., Melnik, Y., Voloshchuk, V., Gülser, C., Kızılkaya, R. (2025). Analysis of drought dynamics using SPI and SARIMA models: A case study of the Rostov Region, Russia. Eurasian Journal of Soil Science, Volume: 14 Issue: 3. https://doi.org/10.18393/ejss.1682888

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