Abstract
Time series analysis and forecasting has become a major tool in different applications in hydrology and environmental management fields. Linear stochastic models known as multiplicative seasonal autoregressive integrated moving average (SARIMA) model were used to simulate and forecast monthly streamflow of Rahad River, Sudan. For the analysis, monthly streamflow data for the years 1972 to 2009 were used. A visual inspection of the time plot gives the expected impression of a generally horizontal trend and 12-month seasonal periodicity. The seasonality observed in auto correlation function (ACF) and partial auto correlation function (PACF) plots of monthly streamflow data was removed using first order seasonal differencing prior to the development of the SARIMA model. Interestingly, the SARIMA (2, 0, 0) × (0, 1, 1)12 model developed was found to be most suitable for simulating monthly streamflow for Rahad River. The model was found appropriate to forecast three years of monthly streamflow and assist decision makers to establish priorities for water demand.
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