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Article

Estimating Future Peak Water Demand with a Regression Model Considering Climate Indices

Institute of Urban Water Management and Landscape Water Engineering, Graz University of Technology, Stremayrgasse 10/I, 8010 Graz, Austria
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Academic Editors: Roberto Ranzi and Kazimierz Banasik
Water 2021, 13(14), 1912; https://doi.org/10.3390/w13141912
Received: 30 April 2021 / Revised: 4 July 2021 / Accepted: 7 July 2021 / Published: 10 July 2021
(This article belongs to the Special Issue Climate Change Impact and Adaptation in Water Resources Management)
Although Austria is a water-rich country, impacts of climate change on water supply are already noticeable. Some regions were affected by water scarcity in recent years. Due to climate change, an increase in peak water demand is expected in the future. Therefore, water demand prediction models that include climate indices are of interest. In this paper, we present a general multiple linear regression (GMLR) model that can be applied to selected study sites. We compared the performance of the GMLR model with different modeling approaches, i.e., stepwise multiple linear regression, support vector regression, random forest regression and a neural network approach. All models were trained with water demand and weather data reaching back several years and tested with the last available observation year. The applied modeling approaches achieved a similar performance. As a second step, the GMLR model was used to estimate the peak water demands for the time period 2025–2050. For the future water demand estimate, 16 different climate projections were used. These climate projections represent the worst-case climate change scenario (RCP 8.5). The expected increase in peak water demand could be confirmed with the modeling approach. An increase in peak water demand by 3.5% compared to the reference period was estimated. View Full-Text
Keywords: long-term daily water demand forecasting; peak water demand; climate change; MLR; SVR; RF; ANN long-term daily water demand forecasting; peak water demand; climate change; MLR; SVR; RF; ANN
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MDPI and ACS Style

Stelzl, A.; Pointl, M.; Fuchs-Hanusch, D. Estimating Future Peak Water Demand with a Regression Model Considering Climate Indices. Water 2021, 13, 1912. https://doi.org/10.3390/w13141912

AMA Style

Stelzl A, Pointl M, Fuchs-Hanusch D. Estimating Future Peak Water Demand with a Regression Model Considering Climate Indices. Water. 2021; 13(14):1912. https://doi.org/10.3390/w13141912

Chicago/Turabian Style

Stelzl, Anika, Michael Pointl, and Daniela Fuchs-Hanusch. 2021. "Estimating Future Peak Water Demand with a Regression Model Considering Climate Indices" Water 13, no. 14: 1912. https://doi.org/10.3390/w13141912

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