  Exponential smoothing is a time series forecasting method that presents the
forecast based on trend and seasonality components. In this work, we study the
behavior of two time series that describe the level of the water reservoirs of
the Descoberto and Santa Maria dams. We trained the fifteen models present in
the Pregels taxonomy, the criterion for choosing the model consists of the
model with the lowest Akaike information criterion. The results indicate that
the exponential smoothing model with damped additive trend and additive
seasonality best describes both time series.
