• Igor Leščešen University of Novi Sad, Climatological and Hydrological Research Center, Novi Sad
  • Dragan Dolinaj University of Novi Sad, Climatological and Hydrological Research Center, Novi Sad
  • Milana Pantelić University of Novi Sad, Climatological and Hydrological Research Center, Novi Sad
  • Srđan Popov University of Novi Sad, Faculty of Technical Sciences, Chair of Applied Computer Science, Novi Sad




SPI, droughts, k-means, regionalization, Vojvodina


Droughts are natural hazards that endanger the safety of population, their property and can create serious agricultural and ecological problems over the affected region. An analysis of the Standardized Precipitation Index (SPI) was performed by using the database of sixty years (1956–2016) of the monthly precipitation for the nine meteorological stations in Vojvodina region (Serbia). The SPI has been used for drought determination. The present study investigates the application of k-means clustering methods on the SPI at the 12-month timescale values to detect distinct drought clusters. For the purpose of determining the optimal number of clusters, the Gap Statistics was used. The results show that the total of four clusters (regions) can be identified in Vojvodina: three stations are listed in region 1 (Sombor, Palić, and Novi Sad), two stations in region 2 (Bač and Sremska Mitrovica), region 3 is a single-station region (Bela Crkva), while in region 4, three stations are grouped (Kikinda, Zrenjanin, and Vršac). The Mann-Kendall test has shown that only in region 1 there is a trend in SPI values ranging from arid towards more humid conditions in the 1956–2016 period. In other regions no trend was observed in the data series. These results could contribute to water resources and agricultural planning and management in Vojvodina region and also confirm the usefulness of clustering methods for drought regionalization.

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How to Cite

Leščešen, I. ., Dolinaj, D. ., Pantelić, M. ., & Popov, S. . (2019). DROUGHT ASSESSMENT IN VOJVODINA (SERBIA) USING K-MEANS CLUSTER ANALYSIS. Journal of the Geographical Institute “Jovan Cvijić” SASA, 69(1), 17–27. https://doi.org/10.2298/IJGI1901017L