Modelling Resilience of a Water Supply System under Climate Change and Population Growth Impacts

Pradeep Amarasinghe, An Liu (), Prasanna Egodawatta, Paul Barnes, James McGree and Ashantha Goonetilleke
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Pradeep Amarasinghe: Queensland University of Technology (QUT)
An Liu: Queensland University of Technology (QUT)
Prasanna Egodawatta: Queensland University of Technology (QUT)
Paul Barnes: Queensland University of Technology (QUT)
James McGree: Queensland University of Technology (QUT)
Ashantha Goonetilleke: Queensland University of Technology (QUT)

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2017, vol. 31, issue 9, No 22, 2885-2898

Abstract: Abstract Climate change impacts and increased demand due to population growth are among the most common disruptions or pressures that can undermine the service potential of a water supply system. Consequently, the successful management of a water supply system depends on an in-depth understanding of the resilience of the system to such pressures. This study developed a robust modelling approach to assess the resilience of a water supply system enabling the identification of critical trigger points at which the system would fail. The trigger points identified included maximum rainfall reduction percentage to maintain system functionality under increased demand and minimum initial storage beyond which the probability of failure increases rapidly. Additionally, a logistic regression model was developed for taking into consideration the cumulative effects of rainfall, demand and storage variations in order to predict the probability of failure of a water supply system. The study outcomes are expected to provide improved guidance to infrastructure system operators for enhancing the efficiency and reliability of water supply systems under threats posed by climate change and population growth impacts.

Keywords: Water supply system; Resilience; Climate change; Population growth (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s11269-017-1646-1

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