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Spatio-Temporal Distribution of Hydrological and Meteorological Droughts in the South Morava Basin

  • Slaviša Trajković
  • Milan Gocić
  • Danilo Misic
  • Mladen MilanovicEmail author
Chapter
  • 27 Downloads
Part of the Springer Tracts in Civil Engineering book series (SPRTRCIENG)

Abstract

Over the years, the appropriateness of selection and application of drought indices in a particular climate area have been discussed. A number of drought indicators have been defined for each type of drought (meteorological, hydrological, agricultural) based on different measured data. The Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI) were used to establish the association between meteorological and hydrological droughts. Based on the availability, type and accuracy of data, SPI and SDI are the simplest indices to obtain. This paper analyzes the different ways of processing drought data for the South Morava basin in a GIS environment. The largest agricultural drought was recorded in 2007 and because of that this year was selected for the drought analysis. The intensity of the SPI index for the year 2007 was calculated based on monthly precipitation data from eight meteorological stations in the South Morava basin. The SDI data for the year 2007 are provided for 16 hydrological stations. The paper compares the results of meteorological and hydrological droughts in the South Morava basin for the year 2007. The data were processed in the Quantum GIS software package and as a result visualisation of spatial data on meteorological and hydrological droughts was obtained in order to be applied in drought monitoring at the regional level.

Keywords

Meteorological drought Hydrological drought SPI SDI Quantum GIS 

Notes

Acknowledgements

The study is supported by the Ministry of Education, Science and Technological Development, Republic of Serbia (Grant No. TR37003), Bilateral science and technological cooperation program between Serbia and Hungary (Grant No. 451-03-02294/2015-09/10) and Serbian Academy of Sciences and Arts Branch in Nis (Grant No. O-15-18).

Conflict of Interest

The authors declare that they have no conflict of interest.

References

  1. Abramowitz, M., & Stegun, I.A. (1964). Handbook of mathematical functions with formulas, graphs and mathematical tables. Washington, D.C.: United States Department of Commerce, National Bureau of Standards Applied Mathematics Series 55.Google Scholar
  2. Doesken, N.J., & Garen, D. (1991). Drought monitoring in the Western United States using a surface water supply index. In Proceedings of the 7th Conference on Applied Climatology. American Meteorological Society: Salt Lake City, UT., pp. 266–269.Google Scholar
  3. Frank, A., Armenski, T., Gocic, M., Popov, S., Popovic, L., & Trajkovic, S. (2017). Influence of mathematical and physical background of drought indices on their complementarity and drought recognition ability. Atmospheric Research, 194, 268–280.  https://doi.org/10.1016/j.atmosres.2017.05.006.CrossRefGoogle Scholar
  4. Gocic, M., Shamshirband, S., Razak, Z., Petkovic, D., Sudheer, Ch., & Trajkovic, S. (2016). Long-term precipitation analysis and estimation of precipitation concentration index using three support vector machine methods. Advances in Meteorology.  https://doi.org/10.1155/2016/7912357.CrossRefGoogle Scholar
  5. Gocic, M., & Trajkovic, S. (2013a). Analysis of precipitation and drought data in Serbia over the period 1980–2010. Journal of Hydrology, 494, 32–42.CrossRefGoogle Scholar
  6. Gocic, M., & Trajkovic, S. (2013b). Analysis of changes in meteorological variables using Mann-Kendall and Sen’s slope estimator statistical tests in Serbia. Global and Planetary Change, 100, 172–182.CrossRefGoogle Scholar
  7. Gocic, M., & Trajkovic, S. (2014a). Spatiotemporal characteristics of drought in Serbia. Journal of Hydrology, 510, 110–123.CrossRefGoogle Scholar
  8. Gocic, M., & Trajkovic, S. (2014b). Drought characterisation based on water surplus variability index. Water Resources Management, 28(10), 3179–3191.CrossRefGoogle Scholar
  9. Hao, B., Xue, Q., Marek, T. H., Jessup, K. E., Beckerm J. D., Hou, X., Hu, W., Bynum, E.D., Bean, B. W., Colaizzi, P. D., & Howel, T. A. (2019). Grain yield, evapotranspiration, and water-use efficiency of maize hybrids differing in drought tolerance. Irrigation Sciences, 37, 25–34.  https://doi.org/10.1007/s00271-018-0597-5.
  10. Jacobi, J., Perrone, D., Lyons Duncan, L., & Hornberger, G. (2013). A tool for calculating the Palmer drought indices. Water Resources Research, 49, 6086–6089.  https://doi.org/10.1002/wrcr.20342.
  11. Lavaysse, C., Vogt, J., Toreti, A., Carrera, M. L., & Pappenberger, F. (2018). On the use of weather regimes to forecast meteorological drought over Europe. Natural Hazards and Earth System Sciences, 18(12), 3297–3309.CrossRefGoogle Scholar
  12. Malik, A., Kumar, A., & Singh, R. P. (2018). Application of heuristic approaches for prediction of hydrological drought using multi-scalar streamflow drought index. Water Resources Management, 33(11), 3985–4006.CrossRefGoogle Scholar
  13. McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology, Anaheim, Calif: American Meterological Society, 17–22 January 1993.Google Scholar
  14. McKee, T. B., Doesken, N. J., & Kleist, J. (1995). Drought monitoring with multiple time scales. In Proceedings of the 9th Conference on Applied Climatology, Boston: American Meteorological Society, pp. 233–236.Google Scholar
  15. Nalbantis, I. (2008). Evaluation of a hydrological drought index. European Water, 23(24), 67–77.Google Scholar
  16. Nalbantis, I., & Tsakiris, G. (2009). Assessment of hydrological drought revisited. Water Resources Management, 23, 881–897.CrossRefGoogle Scholar
  17. Nguvava, M., Abiodun, B. J., & Otieno, F. (2019). Projecting drought characteristics over East African basins at specific global warming levels. Atmospheric Research, 228, 41–54.CrossRefGoogle Scholar
  18. Parente, J., Amraoui, M., Menezes, I., & Pereira, M. G. (2019). Drought in Portugal: Current regime, comparison of indices and impacts on extreme wildfires. Science of the Total Environment, 685, 150–173.CrossRefGoogle Scholar
  19. Park, J., Lim, Y. J., Kim, B. J., & Sung, J. H. (2018). Appraisal of drought characteristics of representative drought indices using meteorological variables. KSCE Journal of Civil Engineering, 22(5), 2002–2009.  https://doi.org/10.1007/s12205-017-1744-x.CrossRefGoogle Scholar
  20. Ramírez-Cuesta, J. M., Cruz-Blanco, M., Santos, C., & Lorite, I. J. (2017). Assessing reference evapotranspiration at regional scale based on remote sensing, weather forecast and GIS tools. International Journal of Applied Earth Observation and Geoinformation, 55, 32–42.CrossRefGoogle Scholar
  21. Stojkovic Piperac, M., Milosevic, D., Petrovic, A., & Simic, V. (2018). The best data design for applying the taxonomic distinctness index in lotic systems: A case study of the Southern Morava River basin. Science of the Total Environment, 610–611, 1281–1287.CrossRefGoogle Scholar
  22. Sun, F., Mejia, A., Zeng, P., & Che, Y. (2019). Projecting meteorological, hydrological and agricultural droughts for the Yangtze River basin. Science of the Total Environment, 696, 134076.CrossRefGoogle Scholar
  23. Svoboda, M., & Fuchs, B., (2016). Handbook of drought indicators and indices. Linkoln, USA: Drought Mitigation Center Faculty Publications, University of Nebraska.Google Scholar
  24. Tabari, H., Nikbakht, J., & Hosseinzadeh Talaee, P. (2013). Hydrological drought assessment in Northwestern Iran based on streamflow drought index (SDI). Water Resources Management, 27(1), 137–151.CrossRefGoogle Scholar
  25. Thenkabail, P. S., & Rhee, J. (2017). GIScience and remote sensing (TGRS) special issue on advances in remote sensing and GIS-based drought monitoring. GIScience and Remote Sensing, 54(2), 141–143.CrossRefGoogle Scholar
  26. Tosic, I., & Unkasevic, M. (2014). Analysis of wet and dry periods in Serbia. International Journal of Climatology, 35(4), 1357–1368.CrossRefGoogle Scholar
  27. Trajkovic, S., Gocic, M., Pongracz, R., & Bartoly, J. (2019). Adjustment of Thornthwaite equation for estimating evapotranspiration in Vojvodina. Theoretical and Applied Climatology.  https://doi.org/10.1007/s00704-019-02873-1.CrossRefGoogle Scholar
  28. Tsakiris, G., & Vangelis, H. (2005). Establishing a drought index incorporating evapotranspiration. European Water, 9(10), 3–11.Google Scholar
  29. Vicente-Serrano, S. M., Beguería, S., & Lopez-Moreno, J. I. (2010). A multi-scalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index–SPEI. Journal of Climate, 23, 1696–1718.CrossRefGoogle Scholar
  30. Wilhite, D. A., & Glantz, M. H. (1985). Understanding the drought phenomenon: The role of definitions. Water International, 10, 111–120.CrossRefGoogle Scholar
  31. World Meteorological Organization. (2012). Standardized precipitation index user guide, WMO-No 1090, Switzerland.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Slaviša Trajković
    • 1
  • Milan Gocić
    • 1
  • Danilo Misic
    • 1
  • Mladen Milanovic
    • 1
    Email author
  1. 1.Faculty of Civil Engineering and ArchitectureUniversity of NisNisSerbia

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