Prediction of SPI Drought Class Transitions Using Markov Chains

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