Urban Water Demand Prediction for a City That Suffers from Climate Change and Population Growth: Gauteng Province Case Study

• Published in: Water (Basel) Vol. 12; no. 7; p. 1885
• Main Authors: Zubaidi, Salah L., Ortega-Martorell, Sandra, Al-Bugharbee, Hussein, Olier, Ivan, Hashim, Khalid S., Gharghan, Sadik Kamel, Kot, Patryk, Al-Khaddar, Rafid
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2020
• Subjects: Accuracy; Algorithms; Artificial intelligence; artificial neural network; backtracking search algorithm; Cities; Climate change; Demand; Engineering; Freshwater resources; Historical account; Information processing; Literature reviews; municipal water demand; Neural networks; Optimization techniques; Population growth; Prediction models; Principal components analysis; Search algorithms; Security; Socioeconomic factors; Studies; Water consumption; Water demand; Water security; Water shortages; Water supply; Water utilities; South Africa

The proper management of a municipal water system is essential to sustain cities and support the water security of societies. Urban water estimating has always been a challenging task for managers of water utilities and policymakers. This paper applies a novel methodology that includes data pre-proc...