Generation of Water Demand Time Series through Spline Curves
Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 11
Abstract
A novel application of spline curves was developed for tracing average daily trends of water demand. These trends were used as input of a stochastic model to generate synthetic time series considering the number of water users as the main input parameter. Hermite polynomials were used for a piecewise interpolation of some known points of the daily trend which were obtained through reliable equations from the literature, whereas unknown points were deduced based on the mathematical properties of the demand pattern. Daily demand time series were generated for different time resolutions using a Monte Carlo approach based on a mixed probability distribution. Results were compared with real observed demand data to validate the effectiveness of the proposed approach, showing encouraging results.
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Data Availability Statement
The data used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.
The code generated or used during the study is available at https://www.unicas.it/siti/laboratori/lia-laboratorio-di-ingegneria-delle-acque/link/residential-water-demand.aspx.
Acknowledgments
The authors thank Dr. Francesco Calabrò and Prof. Antonio Corbo for providing valuable suggestions for the mathematical framework. The authors also thank Dr. Mirjam Blokker for kindly providing the real data set used in the numerical application.
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Published In
Journal of Water Resources Planning and Management
Volume 146 • Issue 11 • November 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Nov 27, 2018
Accepted: May 22, 2020
Published online: Aug 25, 2020
Published in print: Nov 1, 2020
Discussion open until: Jan 25, 2021
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