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This paper presents a methodology to estimate probable trajectories of 6-month (Oct-Mar) precipitation in order to apply the Extended Streamflow Prediction method in the upper São Francisco river basin, located in the tropical climate zone of southeastern Brazil. The method consists of using the mixed distribution of 6-month (Oct-Mar) precipitation volumes, that is the sum of the distributions associated with the below-normal, normal and abovenormal rainfall, adopting the results of a long-range probabilistic forecasting model for 6-month (Oct-Mar) precipitation, as weights, and thus applying the precipitation time distribution. The probabilistic forecasting model employs a few climate indexes, such as the sea surface temperature (SST), as observed in different ocean regions, and the Southern Oscillation Index (SOI) as predictor variables. The time trajectories of 6-month (Oct-Mar) precipitation are used as input data to the MSD-30 rainfall-runoff model. Considering the results of the Half-Brier scores, this method yields goods results, as compared to the climatologybased-only forecasts. The results show that this method is an advance, as it allows the inclusion of climate indexes to estimate the mixed distribution of 6-month (Oct-Mar) precipitation volumes. Furthermore, the proposed method does not require the usual ESP assumption that past observations have the same probability of occurring in the future, since the distribution curve will change with the climate indexes information. Key-words: hydrologic forecasting, Extended Streamflow Prediction (ESP), mixed distribution.

rbrh

Metodologia para Previsão Sazonal de Vazões na Bacia do Alto Rio São Francisco, Incorporando as Estimativas das Prováveis Trajetórias Temporais de Precipitação Associadas às Condições de Indicadores Climáticos