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Water 2017, 9(3), 172; doi:10.3390/w9030172

A Short-Term Water Demand Forecasting Model Using a Moving Window on Previously Observed Data

Engineering Department, University of Ferrara, 44121 Ferrara, Italy
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Academic Editor: Wilhelm Püttmann
Received: 13 January 2017 / Revised: 14 February 2017 / Accepted: 24 February 2017 / Published: 28 February 2017
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Abstract

In this article, a model for forecasting water demands over a 24-h time window using solely a pair of coefficients whose value is updated at every forecasting step is presented. The first coefficient expresses the ratio between the average water demand over the 24 h that follow the time the forecast is made and the average water demand over the 24 h that precede it. The second coefficient expresses the relationship between the average water demand in a generic hour falling within the 24-h forecasting period and the average water demand over that period. These coefficients are estimated using the information available in the weeks prior to the time of forecasting and, therefore, the model does not require any actual calibration process. The length of the time series necessary to implement the model is thus just a few weeks (3–4 weeks) and the model can be parameterized and used without there being any need to collect hourly water demand data for long periods. The application of the model to a real-life case and a comparison with results provided by another model already proposed in the scientific literature show it to be effective, robust, and easy to use. View Full-Text
Keywords: water demand; forecast; moving window water demand; forecast; moving window
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Pacchin, E.; Alvisi, S.; Franchini, M. A Short-Term Water Demand Forecasting Model Using a Moving Window on Previously Observed Data. Water 2017, 9, 172.

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