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Article

Forecasting Urban Water Demand Using Cellular Automata

Hydraulic and Environmental Engineering Department (DEHA), Federal University of Ceará, Fortaleza 60020-181, Brazil
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Water 2020, 12(7), 2038; https://doi.org/10.3390/w12072038
Received: 29 May 2020 / Revised: 5 July 2020 / Accepted: 14 July 2020 / Published: 17 July 2020
(This article belongs to the Special Issue Management of Urban Water Services)
Associating the dynamic spatial modeling based on the theory of cellular automata with remote sensing and geoprocessing technologies, this article analyzes what would be the per capita consumption behavior of Fortaleza-CE, located in the Northeast of Brazil, in 2017, had there not been a period of water scarcity between 2013 and 2017, and estimates the future urban water demand for the years 2021 and 2025. The weight of evidence method was applied to produce a transition probability map, that shows which areas will be more subject to consumption class change. For that, micro-measured water consumption data from 2009 and 2013 were used. The model was validated by the evaluation of diffuse similarity indices. A high level of similarity was found between the simulated and observed data (0.99). Future scenarios indicated an increase in water demand of 6.45% and 10.16% for 2021 and 2025, respectively, compared to 2017. The simulated annual growth rate was 1.27%. The expected results of urban water consumption for the years 2021 and 2025 are essential for local water resources management professionals and scientists, because, based on our results, these professionals will be able to outline future water resource management strategies. View Full-Text
Keywords: water demand; cellular automata; dynamic modeling water demand; cellular automata; dynamic modeling
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MDPI and ACS Style

Marques de Oliveira, L.; Maria Oliveira da Silva, S.; de Assis de Souza Filho, F.; Maria Nunes Carvalho, T.; Locarno Frota, R. Forecasting Urban Water Demand Using Cellular Automata. Water 2020, 12, 2038. https://doi.org/10.3390/w12072038

AMA Style

Marques de Oliveira L, Maria Oliveira da Silva S, de Assis de Souza Filho F, Maria Nunes Carvalho T, Locarno Frota R. Forecasting Urban Water Demand Using Cellular Automata. Water. 2020; 12(7):2038. https://doi.org/10.3390/w12072038

Chicago/Turabian Style

Marques de Oliveira, Laís, Samíria Maria Oliveira da Silva, Francisco de Assis de Souza Filho, Taís Maria Nunes Carvalho, and Renata Locarno Frota. 2020. "Forecasting Urban Water Demand Using Cellular Automata" Water 12, no. 7: 2038. https://doi.org/10.3390/w12072038

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