Despite the exponential growth of wind farms in recent years, the Brazilian energy matrix is mainly composed of hydroelectric plants.One of the main characteristics of hydroelectric generation systems is the strong dependence on hydrological regimes. Currently, the Brazilian electric sector uses the Natural Energy In flow to generate hydrological scenarios from a PAR model.Such model is adjusted from the estimated parameters of the time series history, that is, it does not consider any exogenous information that could affect the hydrological regimes and, consequently, the energy production. Recent studies indicate that the use of climatic variables in the modeling of inflow series in the Brazilian basins may serve as a factor to reduce uncertainties due to the existence of correlation between these variables. It was also identified benefits by decomposing hydrological series into signal and noise and using only the signal for modeling. In this context, the development of hybrid models that combine techniques of decomposition of the hydrological series and time series models with exogenous variable are study objects of this work, as well as the development of models that associate such variables in a non-linear and periodic way. These new approaches contemplate the use of SSA and MSSA decomposition techniques in combination with PAR, the application of the PARX and the development of the PGAM model. As conclusion, the applied models were efficient for the proposed objectives and also presented better performance, in some cases, when compared with models already published in the literature.