ABSTRACT
Climate change has become the greatest threat to the survival of the world and its ecosystem, due to the increasing problems associated with the rise in sea level, food-insecurity, natural resources scarcity, seasonal disorders. Among these problems, is the issue of water scarcity resulting from the lack of water resources and global warming which has plagued several nations and acknowledged by the United Nations (UN) as a primary resource to the development of societies under the “Water Goal” of the sustainable development goals. As such the changing climate and intermittent availability of water resources pose major challenges to forecast demand, especially in countries like the United Arab Emirates (UAE) which has one of the highest per capita residential water consumption rates in the world. This study therefore aims to propose a water demand forecasting model as a form of criterion validity that incorporates the significant factors considering “mean temperature”, “mean rainfall”, “relative humidity”, “Gross Domestic Product (GDP)”, “Consumer Price Index (CPI)” and “population growth” as the significant factors for predicting the future water demand of the UAE. The Long Short-Term Memory (LSTM) forecasting model was adopted along with test conducted such as R 2 known as the coefficient of determination and Mean squared error (MSE) to evaluate predictive validity of the forecasting model. The measure of predictive validity indicates that the model is reliable and valid which predicts the water demand forecasting in the UAE showing that the future demand will decrease from 1821 million m3 in 2018 to 1809.9 million m3 in 2027.
