Extreme events such as drought and floods in Iran have always been one of the most important and harmful issues in the country and their occurrence and prediction have been in the focus of most researchers. Occurrence of floods in recent years and the inability of the management system to act in a timely manner to reduce its effects on flood-prone communities have led everyone to use various methods to predict floods. However, the lack of facilities for monitoring and collection of meteorological and hydrological data in the country's watersheds is considered a major obstacle to flood studies. Therefore, using the minimum available data to predict floods can be a good way to plan and study floods in Iran quickly. Therefore, in this study, the application of ARIMA time series modeling and ARIMA-Fourier hybrid model for modeling the maximum instantaneous discharge on an annual scale in 6 stations of Gorganroud watershed was investigated. The results showed that the use of ARIMA model alone cannot have an acceptable result, especially in the annual data scale, but the application of ARIMA-Fourier model could well increase the accuracy and efficiency of the model, so that the accuracy and efficiency indices of the model were significantly improved. As a result, the use of hybrid models such as ARIMA-Fourier can be used to improve the modeling efficiency of flood flows time series.