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Scholars Journal of Physics, Mathematics and Statistics | Volume-1 | Issue-02
Forecasting Monthly Water Production in Gaza City Using a Seasonal ARIMA Model
Mahmoud K. Okasha, Deaa M.M Abu Shanab
Published: Nov. 26, 2014 | 83 74
DOI: 10.36347/sjpms
Pages: 61-70
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Abstract
This paper aimed to analyze seasonal time series data on monthly water production in the Gaza Strip during the period between 2006 and 2012 using the Box-Jenkins methodology. A model was proposed that could forecast future monthly water production in the Gaza Strip, one of the mostly densely populated areas with one of the highest natural growth rates in the world and very limited water resources. The increasing demand for domestic water consumption requires Palestinian officials and international donors to take suitable measures to conserve or allocate water supplies. A model was found that best represented the time series data according to different criteria; the Box-Ljung test identified a seasonal model of lag 12 (SARIMA (1 , 1 , 1) × (1, 1 , 1)12). Monthly water production in Gaza Strip was forecast for the period from January 2013 to December 2013 using this model. A comparison of these forecasts with observed values over this time period indicated that the model was highly accurate. Keywords: Box-Jenkins methodology, Seasonal models, Forecasting, Box-Ljung test, Augmented Dickey-Fuller test, Kwiatkowski-Phillips-Schmidt-Shin test.