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Prediction of SPI Drought Class Transitions Using Markov Chains

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  • Ana Paulo
  • Luis Pereira

Abstract

Using the SPI relative to 67 years data sets, a Markov chains approach has been utilized for several locations in Alentejo, southern Portugal, to characterize the stochasticity of droughts, which allowed predicting the transition from a class of severity to another up to 3 months ahead. Markov models were applied using both the homogeneous and non-homogeneous formulations. The results of the application of the Markov models are presented and discussed, showing in particular the usefulness of adopting a non-homogeneous formulation, which allows to differentiate predictions in relation to the initial month considered, thus understanding the probable evolution of a drought as influenced by the climate and, in particular, the seasonality of rainfall. However, these results, which are promising in view of drought management, require further developments and to be associated with other predictive tools of stochastic or physical nature. Possible approaches on using predictions of drought class transitions in view of drought risk management are also discussed. Copyright Springer Science+Business Media, Inc. 2007

Suggested Citation

  • Ana Paulo & Luis Pereira, 2007. "Prediction of SPI Drought Class Transitions Using Markov Chains," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(10), pages 1813-1827, October.
    • Handle: RePEc:spr:waterr:v:21:y:2007:i:10:p:1813-1827
    DOI: 10.1007/s11269-006-9129-9
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    References listed on IDEAS

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    1. Frank Bickenbach & Eckhardt Bode, 2003. "Evaluating the Markov Property in Studies of Economic Convergence," International Regional Science Review, , vol. 26(3), pages 363-392, July.
    2. B. Bonaccorso & I. Bordi & A. Cancelliere & G. Rossi & A. Sutera, 2003. "Spatial Variability of Drought: An Analysis of the SPI in Sicily," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 17(4), pages 273-296, August.
    3. Paulo, A.A. & Ferreira, E. & Coelho, C. & Pereira, L.S., 2005. "Drought class transition analysis through Markov and Loglinear models, an approach to early warning," Agricultural Water Management, Elsevier, vol. 77(1-3), pages 59-81, August.
    4. Sergio Vicente-Serrano, 2006. "Differences in Spatial Patterns of Drought on Different Time Scales: An Analysis of the Iberian Peninsula," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(1), pages 37-60, February.
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