American Society of Civil Engineers

A Comparison of Short Term Forecast Methods for Municipal Water Use

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

pp. 649-652

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Document type: Conference 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.

ASCE Subject Headings:
Water demand
Water management
Neural networks

Author Keywords:
Water supply
Mathematical models - Neural networks - Urban planning
Lexington Kentucky - Lumped response model - Short term demand models