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Analysis of drought patterns and categories based on the Standard Precipitation-Temperature Index (SPTI): application of fuzzy c-means clustering and principal component analysis

Author

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  • Sabri Berhail

    (Abdelhafid Boussouf University Center)

  • Okan Mert Katipoğlu

    (Erzincan Binali Yıldırım University)

Abstract

This study deals with climate variability issues in the Kebir Rhumel basin, situated in northeastern Algeria. This region is experiencing significant changes in climate parameters, which will affect the region’s water resources, agriculture, and overall ecosystem health. The main goal of this study is to examine the severity and frequency of drought from 1981 to 2019. It used the Standard Precipitation-Temperature Index (SPTI), which was recently developed, and clustering methodologies such as c-means and k-means to examine the variation in rainfall patterns characterized by intervals of intense drought and heavy precipitation. These methods help assess the impact of these disturbances in water availability, which result in challenges for agricultural productivity and water management. Additionally, this study points out the significant trend in temperatures over the reported timeline, which aligns with global warming patterns; this intensifies the effect of drought and impacts the region’s water resources. The southeastern and western parts of the basin are areas that experience continuous extreme drought, and different levels of severe drought have been observed over decades. When comparing the results with existing methods, this research has revealed unique climatic trends in this basin area through clustering techniques applied to SPTI results. In particular, 45% of the stations indicate moderate wetness, 35% of the stations experience extreme wetness, and 20% of the stations are extremely dry. Each of these climatic patterns poses distinct challenges for water resource management. These findings demonstrate the complex interplay between rainfall variability, temperature increases, and drought severity. They underscore the urgent need for adaptive water management strategies and plans to address climate change impacts.

Suggested Citation

  • Sabri Berhail & Okan Mert Katipoğlu, 2025. "Analysis of drought patterns and categories based on the Standard Precipitation-Temperature Index (SPTI): application of fuzzy c-means clustering and principal component analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(10), pages 12025-12051, June.
    • Handle: RePEc:spr:nathaz:v:121:y:2025:i:10:d:10.1007_s11069-025-07271-7
    DOI: 10.1007/s11069-025-07271-7
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    References listed on IDEAS

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    1. Kiyoumars Roushangar & Roghayeh Ghasempour & Vahid Nourani, 2022. "Spatiotemporal Analysis of Droughts Over Different Climate Regions Using Hybrid Clustering Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 473-488, January.
    2. Salim Djerbouai & Doudja Souag-Gamane, 2016. "Drought Forecasting Using Neural Networks, Wavelet Neural Networks, and Stochastic Models: Case of the Algerois Basin in North Algeria," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2445-2464, May.
    3. Nadjib Haied & Atif Foufou & Samira Khadri & Adel Boussaid & Mohamed Azlaoui & Nabil Bougherira, 2023. "Spatial and Temporal Assessment of Drought Hazard, Vulnerability and Risk in Three Different Climatic Zones in Algeria Using Two Commonly Used Meteorological Indices," Sustainability, MDPI, vol. 15(10), pages 1-25, May.
    4. Dai, Meng & Huang, Shengzhi & Huang, Qiang & Leng, Guoyong & Guo, Yi & Wang, Lu & Fang, Wei & Li, Pei & Zheng, Xudong, 2020. "Assessing agricultural drought risk and its dynamic evolution characteristics," Agricultural Water Management, Elsevier, vol. 231(C).
    5. Kiyoumars Roushangar & Roghayeh Ghasempour & Vahid Nourani, 2022. "Correction to: Spatiotemporal Analysis of Droughts Over Different Climate Regions Using Hybrid Clustering Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 489-489, January.
    6. Belkhiri, Lazhar, 2021. "Spatial and temporal variability of water stress risk in the Kebir Rhumel Basin, Algeria," Agricultural Water Management, Elsevier, vol. 253(C).
    7. Li, Jiale & Li, Yu & Yin, Lei & Zhao, Quanhua, 2024. "A novel composite drought index combining precipitation, temperature and evapotranspiration used for drought monitoring in the Huang-Huai-Hai Plain," Agricultural Water Management, Elsevier, vol. 291(C).
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