Application of Markov chains to Standardized Precipitation Index (SPI) in São Francisco River Basin

  • Esdras Adriano Barbosa dos Santos Universidade Federal de Sergipe (UFS), São Cristóvão, SE, Brasil Departamento de Estatística e Ciências Atuariais (DECAT).
  • Tatijana Stosic Universidade Federal Rural de Pernambuco (UFRPE), Recife, PE, Brasil Departamento de Estatística e Informática (DEINFO).
  • Ikaro Daniel de Carvalho Barreto Universidade Federal Rural de Pernambuco (UFRPE), Recife, PE, Brasil Departamento de Estatística e Informática (DEINFO).
  • Laélia Campos Universidade Federal de Sergipe (UFS), São Cristóvão, SE, Brasil Departamento de Física (DFI).
  • Antonio Samuel Alves da Silva Universidade Federal Rural de Pernambuco (UFRPE), Recife, PE, Brasil Departamento de Estatística e Informática (DEINFO).
DOI: https://doi.org/10.4136/ambi-agua.2311
Keywords: drought, Markov chains, standardized precipitation index.

Abstract

This work evaluated dry and rainy conditions in the subregions of the São Francisco River Basin (BHSF) using the Standardized Precipitation Index (SPI) and Markov chains. Each subregion of the BHSF has specific physical and climatic characteristics. The data was obtained from the National Water Agency (ANA), collected by four pluviometric stations (representative of each subregion), covering 46 years of data, from 1970 to 2015. The SPI was calculated for the time scales of six and twelve months and transition probabilities were obtained using the Markov chain. Transition matrices showed that, at both scales, if the climate conditions were severe drought or rainy, switching to another class would be unlikely in the short term.  Correlating this information with the probabilities of the stationary distribution, it was possible to find the regions that are most likely to be under rainy or dry weather in the future. The recurrence times calculated for the stations that belong to the semi-arid region were smaller when compared to the value of the return period of the representative station of Upper São Francisco that has higher levels of precipitation, confirming the predisposition of the semi-arid region to present greater chances of future periods of drought.


Published
20/05/2019
Issue
Vol. 14 No. 3 (2019)
Section
Papers

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