A Comparison of Short Term Forecast Methods for Municipal Water Use

by Ashu Jain, Univ of Kentucky, Lexington, United States,
Lindell Ormsbee, Univ of Kentucky, Lexington, United States,



Document Type: Proceeding Paper

Part of: Water Management in the '90s: A Time for Innovation

Abstract:

Water utilities routinely develop long range demand forecasts for use in the normal planning activities. In recent years, many utilities have sought to develop more short-term demand forecasts for use in daily operations. In the current study three different short-term (daily) demand models are developed and tested for the city of Lexington, Kentucky. Developed models include a lumped response model, a distributed response model, and a neural network based model.

Subject Headings: Mathematical models | Water demand | Municipal water | Forecasting | Neural networks | Water use | Water supply systems | Kentucky | United States

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