Discussion and Forecast Monthly Average Rainfall Techniques Using SARIMA (Case study: Pluviometry Station Babaaman Bojnourd)

Limited water resources needed for agricultural and non-agricultural water supply has caused major problems. Rain is considered as one of the available water resources. Therefore, to predict and estimate the amount of rainfall in any month or year and for each catchment area as one of the most important atmospheric parameters, of particular importance is the efficient use of water resources. For predict rain can be used of the time series. The aim of this study is the most appropriate model to estimate the rain, so that using the 30-year (1971-2001) monthly rainfall and after determining the model parameters and seasonal and non- seasonal SARIMA model and using the statistical software Minitab end of the period of ten years of monthly rainfall amounts (2002-2011) in the rain stations - located in North Khorasan Province Babaaman survey were estimated. The monthly rainfall amounts predicted by the statistical distribution, was calculated. By comparing the estimated values with actual values corresponding monthly rainfall was result of models with more are parameters the order autoregressive or moving average is more than 1 shows different values for the following years. But these differences are also limited to a few years to exceed the maximum number of model parameters. The correlation coefficients between actual and predicted values at station 0.64 were studied. The regression equation obtained can be used to correct moderate amounts of rainfall stations used in forecasting.