Urban Water Demand Forecasting: Review of Methods and Models

Abstract

AbstractThis paper reviews the literature on urban water demand forecasting published from 2000 to 2010 to identify methods and models useful for specific water utility decision making problems. Results show that although a wide variety of methods and models have attracted attention, applications of these models differ, depending on the forecast variable, its periodicity and the forecast horizon. Whereas artificial neural networks are more likely to be used for short-term forecasting, econometric models, coupled with simulation or scenario-based forecasting, tend to be used for long-term strategic decisions. Much more attention needs to be given to probabilistic forecasting methods if utilities are to make decisions that reflect the level of uncertainty in future demand forecasts.