A short-term, pattern-based model for water-demand forecasting

Abstract

The short-term, demand-forecasting model described in this paper forms the third constituent part of the POWADIMA research project which, taken together, address the issue of real-time, near-optimal control of water-distribution networks. Since the intention is to treat water distribution as a feed-forward control system, operational decisions have to be based on the expected future demands for water, rather than just the present known requirements. Accordingly, it was necessary to develop a short-term, demand-forecasting procedure. To that end, monitoring facilities were installed to measure short-term fluctuations in demands for a small experimental network, which enabled a thorough investigation of trends and periodicities that can usually be found in this type of time-series. On the basis of these data, a short-term, demand-forecasting model was formulated. The model reproduces the periodic patterns observed at annual, weekly and daily levels prior to fine-tuning the estimated values of future demands through the inclusion of persistence effects. Having validated the model, the demand forecasts were subjected to an analysis of the sensitivity to possible errors in the various components of the model. Its application to much larger case studies is described in the following two papers.