Date of Award
Master of Science (MS)
Dr. Mohamed M. Mohamed,
Vijay P. Singh,
Water demand forecasting has become an essential component in effective water resources planning and management. It provides valuable trigger in determining the time and the capacity for new water resources development. In the United Arab Emirates, the need for an accurate water demand forecasting becomes particularly important. The reasons for this include, and are not limited to, high temperature throughout the year, high population growth rates, and high development growth.
The main objective of this study is to forecast the water demand in UAQ for the next 25 years using the IWR-MAIN software. Two methods; namely the Constant Use Rate Model (Model 1) and the Specify Forecasting Linear Model (Model 2) were used in this study. The forecast was performed using two different databases; each of which contains water consumption, populations, temperature and rainfall data. The first database represents the average daily water consumption and the total number of water supply connections in Umm AI Quwain from 1980 to 2007. The second database was organized using new computerized water system in UAQ WD for the metered water units from 2000 to 2007.
A linear predictive model shows that population is the most significant variable, and that rainfall and temperature have minor effects on water demand forecasting. Calibration and verification of the IWR-MAIN models suggests that the years 1999 and 2001 are the best base years from the first and second databases, respectively to forecast the water demand using model 1. The years 1993 and 2006 were the best base years for model 2. Based on the calibration results, different scenarios were performed to forecast water demand until the year 2035. It was found that considering the expected increase in the income level in the coming years will cause the water demand to increase. It was also found that by considering the unmetered/unaccounted water consumption ratio, the total demand increases. However, by minimizing this ratio, the increase in total water demand will be reduced. In addition, results indicate that Umm AI Quwain demand will be strongly affected by the expected high population due to the new expected developments.
Al Mualla, Aysha Abdulla, "Water Demand Forecasting in Umm Al Quwain Using the IWR-Main" (2009). Theses. 627.