(untitled) (Research, Society and Development, 2020)
The objective of this paper was to investigate the patterns (trend and seasonality) of the levels of rainfall in the municipality of Aracaju, presenting a methodology to make adequate forecasts for short periods of time. It is known that the different Northeast Brazilian regions (NEB) have high temporal variability in rainfall. Specifically, NEB has been suffering from extreme weather, droughts and floods within the same year, and it is no different in the state of Sergipe, especially in its capital, Aracaju. For that, such predictions are used to anticipate the phenomena and organize mitigating actions. In this study, we opted to use the integrated autoregressive model of seasonal moving averages (SARIMA) which contains two parts: one non-seasonal and another seasonal. Accumulated monthly precipitation data in Aracaju, from 1986 to 2018, showed a decreasing trend and a twelve-month seasonality. Adjusting the class of SARIMA models to this historical series proved to be an adequate alternative for forecasting monthly rainfall in this city. Therefore, through the study of this manuscript, the selected model presented adequate estimates of precipitation, thus suggesting that models of the SARIMA class can be used as a tool for forecasting monthly levels of rainfall in the region under study. These estimates can be used to better manage water resources, anticipating society’s future needs, such as long periods of drought, droughts and floods.