Este trabalho objetivou avaliar períodos secos e chuvosos nas sub-regiões da Bacia Hidrográfica do Rio São Francisco (BHSF) utilizando o Índice de Precipitação Padronizado (SPI) e cadeias de Markov. Cada sub-região da BHSF possui características físicas e climáticas específicas, dessa forma foram utilizadas quatro estações pluviométricas contendo dados com 46 anos, de 1970 a 2015, obtidas na Agência Nacional de Águas (ANA), representativas de cada sub-região. O SPI foi calculado para as escalas de tempo de seis e doze meses e as matrizes de probabilidades de transição foram obtidas utilizando as cadeias de Markov. As matrizes de transição mostraram que, em ambas as escalas, caso a condição climática estivesse em classe de seca severa ou chuvosa, a mudança para outra classe seria pouco provável a curto prazo. Correlacionando esta informação com as probabilidades da distribuição estacionária, foi possível encontrar as regiões que têm maiores possibilidades de no momento futuro estar sob clima chuvoso ou de seca. Os tempos de recorrência calculados para as estações inseridas no semiárido foram menores quando comparado com o valor do tempo da estação representativa do Alto São Francisco que possui maiores níveis de precipitação, confirmando a predisposição do semiárido em apresentar maiores chances de períodos futuros de seca.
Palavras-chave: cadeias de Markov, índice de precipitação padronizado, seca.
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.
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.
