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This paper considers analyzing and modeling a time series of mean monthly streamflows using the stochastic model ARIMA (autoregressive integrated moving average). This analysis aims to model and forecast the monthly streamflow in the Potiribu river basin, located in the northwest region of Rio Grande do Sul state, Brazil. We tested several models of the SARIMA type, or ARIMA models which take the seasonal characteristics of the data into account. Among all tested models we selected some competing ones that had the lowest Akaike information criteria (AIC). Finally, we chose the SARIMA model (3,0,0) (2,1,2)12 which presented the best fit to the series of flows observed, with the Nash-Sutclife coefficient (NSC) equal to 0.68, as training data. The model was used to make forecasts for the six months forward, resulting in NSC = 0.81 as validating data

Modelagem e Previsão de Vazões Médias Mensais do Rio Potiribu Utilizando Modelos de Séries Temporais