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

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.

Drought Assessment in São Francisco River Basin, Brazil: Characterization through SPI and Associated Anomalous Climate Patterns

“…The 1-month scale (SPI-1) can reflect short-term conditions and can be used for the analysis of meteorological droughts [1]. The 12-month scale (SPI-12), in addition to long-term precipitation patterns, can also be associated with anomalies of river flows and reservoir levels [1], and it was chosen to assess hydrological droughts in the SF, following Santos et al [85]. By calculating the SPI, the time series is adjusted to a gamma function, and, after this process, it is transformed into a variable with normal distribution; therefore, the average of the SPI is always zero, and its variance has a unit value [86].…”

Pluviometric patterns in the São Francisco River basin in Minas Gerais, Brazil

“…These atmospheric conditions blocked the passage of cold fronts from the south and moisture from the Amazon Basin (Coelho et al, 2016;Nobre et al, 2016). Additionally, at time scales of six and twelve months, if the climate conditions were severe drought or rainy, switching to another class would be unlikely in the short term (Santos et al, 2019).…”

Long‐term meteorological drought characterization in the São Francisco watershed, Brazil: A climatic water balance approach

“…Moreover, the watershed presents itself as an interesting study subject due to its climate diversity and continental dimensions. Indeed, several studies were developed in the SFW with specific drought‐related objectives: water balance studies at the sub‐basin scales (de Assis et al ., 2017; Lopes et al ., 2017; dos Santos et al ., 2018), studies using standardized drought indices at specific sites in the basin (Santos et al ., 2017; 2019; dos Santos et al ., 2019), studies on hydrometeorological aspects of drought (Sun et al ., 2016; Martins et al ., 2018); and studies describing the links between rainfall deficit and large‐scale circulation patterns (Paredes‐Trejo et al ., 2016).…”