Abstract

Population growth, rapid urbanization and climate change have been producing an ever increasing stress on the limited resources of fresh water. This situation makes prediction models of water demand an important tool for decision making regarding urban water management and conservation. However, there is still the need for improvement of the predictions of the existing models, especially in their estimations of base water use. The purpose of this thesis is to develop a more reliable water demand prediction model which gives a better understanding of water use behaviour. The employed techniques represent a new approach to predictions of daily water use; its base use component is predicted using a function of socioeconomic factors, as opposed to a function of time as in existing approaches. The prediction by the model proposed in this thesis is compared with those by two other existing models, in an application to the city of Brossard in Quebec. Time series of predicted daily urban water use captures observed characteristics very well and improves the results of the weighted coefficient of determination, the relative index of agreement and the root mean square error from the existing approaches. Water use in the city exhibits a downward trend possibly due to an increasing annual charge for water use. The analysis procedures reported in this thesis can be applied to analyze water use in any other cities. The new approach would be a useful tool for decision makers to manage water use by adjusting water consumption policies and price.