An empirical investigation of water consumption forecasting methods

Panagiotis I. Karamaziotis, Achilleas Raptis, Konstantinos Nikolopoulos (), Konstantia Litsiou and Vassilis Assimakopoulos

International Journal of Forecasting, 2020, vol. 36, issue 2, 588-606

Abstract: Many regions on earth face daily limitations in the quantity and quality of the water resources available. As a result, it is necessary to implement reliable methodologies for water consumption forecasting that will enable the better management and planning of water resources. This research analyses, for the first time, a large database containing data from 2 million water meters in 274 unique postal codes, in one of the most densely populated areas of Europe, which faces issues of droughts and overconsumption in the hot summer months. Using the R programming language, we built and tested three alternative forecasting methodologies, employing univariate forecasting techniques including a machine-learning algorithm, with very promising results.

Keywords: Water consumption; Water management; Time series forecasting; Prediction intervals; Neural networks (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:36:y:2020:i:2:p:588-606

DOI: 10.1016/j.ijforecast.2019.07.009

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