Abstract
Time series analysis and forecasting is an important tool which can be used to improve water resources management. Iraq is facing a severe water shortage problem. The use of rainwater harvesting is one of the techniques to overcome this problem. To put this into practice, it is of prime importance to forecast future rainfall events on a weekly basis. Box-Jenkins methodology has been used in this research to build Autoregressive Integrated Moving Average (ARIMA) models for weekly rainfall data from four rainfall stations in the North West of Iraq: Sinjar, Mosul, Rabeaa and Talafar for the period 1990-2011. Four ARIMA models were developed for the above stations as follow: (3,0,2)x(2,1,1)30, (1,0,1)x(1,1,3)30, (1,1,2)x(3,0,1)30 and (1,1,1)x(0,0,1)30 respectively. The performance of the resulting successful ARIMA models were evaluated using the data year (2011).These models were used to forecast the weekly rainfall data for the up-coming years (2012 to 2016). The results supported previous work that had been carried out on the same area recommending the use of water harvesting in agricultural practices.