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Modelling of Meteo-Droughts

Author

Listed:
  • Julius Fabian

    (E. Zelenhasic University of Novi Sad)

  • Emir Zelenhasic

    (E. Zelenhasic University of Novi Sad)

Abstract

A simple stochastic model of meteorological droughts (meteo-droughts) is presented. All its components are analyzed and described, along with their probabilistic structures. The model is composed of ten defining descriptive parameters and each of them is a random variable. The statistical explanation of the entire probabilistic process of meteo-droughts provides the base from which the procedure of developing the m-year synthetic meteo-drought is derived. From the meteorologist’s and consulting engineer’s point of view this model can be used efficiently to explain meteo-drought phenomenon in a quantifiable manner. This model is an approximate, not exact theoretical method of the probabilistic meteo-drought analysis. The method is intended for practical use by various professionals, such as irrigation, agricultural and forest engineers, hydrologists and meteorologists. The method has been applied in this paper to data observed at Sombor meteorological station, Serbia. Each defined meteorological drought be it past, present or future, can be described quantitatively and completely by the presented stochastic method. In other words, each meteo-drought is given its “identification card” (ID card). The application of the procedure has shown that the method is simple, yet complete, reliable and efficient.

Suggested Citation

  • Julius Fabian & Emir Zelenhasic, 2016. "Modelling of Meteo-Droughts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(9), pages 3229-3246, July.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:9:d:10.1007_s11269-016-1342-6
    DOI: 10.1007/s11269-016-1342-6
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    References listed on IDEAS

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    1. Emir Zelenhasic, 2002. "On the Extreme Streamflow Drought Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 16(2), pages 105-132, April.
    2. Harris Vangelis & Mike Spiliotis & George Tsakiris, 2011. "Drought Severity Assessment Based on Bivariate Probability Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(1), pages 357-371, January.
    3. G. Tsakiris & D. Pangalou & H. Vangelis, 2007. "Regional Drought Assessment Based on the Reconnaissance Drought Index (RDI)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 821-833, May.
    4. Milan Gocic & Slavisa Trajkovic, 2014. "Drought Characterisation Based on Water Surplus Variability Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 3179-3191, August.
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