Urban Water Demand Forecasting Using the Stochastic Nature of Short Term Historical Water Demand and supply Pattern

Thewodros G. Mamo; Ilan Juran; Isam Shahrour
Today’s big city water utility companies are experiencing high level of water loss due to various problems in covering a large scale of water supply pipeline networks, therefore any significant improvement of water loss prevention from supply network to treatment plant would require an apprehends stochastic nature of historical water demand and supply pattern. For this reason urban water demand forecasting is one of key important parameters used when water utility companies are trying to find more efficient and robust ways of supplying water for a large number of urban consumers. Water demand forecasting also plays a significant role in managing and planning water supply operations and water conservation and optimization strategies. However, traditional forecasting approaches based on a set of deterministic design capacity factors or using demand forecasting algorithms without evaluating the relationship between supply reliability in response to the stochastic nature of historical water consumption data and supply pattern often become misleading due to the inability to sufficiently forecast forthcoming events and lack of relevant historical pattern and data. This paper presents an analysis and water demand forecasting demonstration using the stochastic nature of short term historical water demand and supply Pattern for Lille University Z6 pipeline networks research area in France.
Urban Water Demand; Time series (AR1); Forecasting; Stochastic Simulation; Historic Demand Pattern
Download | Back to Issue| Archive