Rainfall Prediction in Tartous Station Located in the Southern Part of the Syrian Coast

Rainfall is considered as one of the most difficult and complex elements of the hydrological cycle, to understand and model, due to the complexity of air operations that generate rain. The importance of research comes from the direct relationship between the rainfall amount and economic & social activities of the population, planning scopes of the water resources management, particularly with respect to the agricultural development. The research aims to highlight the rainfall amounts in Tartous station which is located in the southern part of the Syrian coast, and applying one model of Box-Jenkins models for the purpose of predicting future rainfall amounts. Multiple Arima models have been tested. The results showed that the model SARIMA (3,0,4) was the best one. Data were divided into 43 years to build the model and eight years to test it. The test results gave high accuracy in the performance, and the model was used to predict the values of annual rainfall for the next twenty years.

A Comparative study on ARIMA model and Exponential smoothing method in time series forecasting

The study aims at comparing ARIMA models and the exponential smoothing method in forecasting. This study also highlights the special and basic concepts of ARIMA model and the exponential smoothing method. The comparison focuses on the ability of both methods to forecast the time series with a narrow range of one point to another and the time series with a long range of one point to another, and also on the different lengths of the forecasting periods. Currency exchange rates of Shekel to American dollar were used to make this comparison in the period between 25/1/2010 to 22/10/2016. In addition, weekly gold prices were considered in the period between 10/1/2010 to 23/10/2016. RMSE standard was used in order to compare between both methods. In this study, the researcher came up with the conclusion that ARIMA models give a better forecasting for the time series with a long range of one point to another and for long term forecasting, but cannot produce a better forecasting for time series with a narrow range of one point to another as in currency exchange prices. On the contrary, exponential smoothing method can give better forecasting for Exchange Rates that has a narrow range of one point to another for its time series, while it cannot give better forecasting for long term forecasting periods