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In most hydrological time series data studies atypical observations (outliers) are not usually considered in the data modelling process. As a result, the performance of stochastic modelling, in terms of liability and accuracy, has not been very good. This paper presents a comparative study of stochastic modelling of the monthly maximum flow rate of River Jucu (one of the two main water suppliers to Great Vitória, State of Espírito Santo, Southeastern Region of Brazil), by considering or not outliers as part of the flow rate time series. Based on the modelling performance indicators MSE (mean square error) and MAPE (mean absolute percentile error), the version of the SARIMA model taking outliers into account presented a much better performance in terms of prediction reliability and accuracy than the SARIMA model in its usual form (without considering outliers). Thus, the case study presented in this paper calls attention to the importance of taking into account the presence of outliers when modelling time series in a variety of water resources problems such as floods and droughts.

Modelagem de Séries Temporais Sazonais na Presença de Ooutliers Estudo de Caso da Vazão Máxima Mensal do Rio Jucu, ES, Brasil