Effectiveness of log-logistic distribution to model water-consumption data

Seevali Surendran*, Kiran Tota-Maharaj

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

Water consumption varies with time of use, season and socio-economic status of consumers, and is defined as a continuous random variable. Incorporating probabilistic nature in water-consumption modelling will lead to more realistic assessments of performance of water distribution systems. Furthermore, fitting water-consumption patterns into a suitable statistical distribution will assist in determining how often peaks will occur, or the probability of exceeding the peaking factor in a system, for incorporation into design calculations. There are few studies in the literature where the random variations of consumption have been considered. The purpose of this study is to evaluate real water-consumption data from the United Kingdom (UK) and North America and to investigate the possibility of establishing a standard probability distribution function to apply in simulating water consumption in developed countries. Daily water-consumption data for 5 years (2009–2013) were obtained from water companies in the UK and North America and analysed by fitting into normal, lognormal, log-logistic and Weibull distributions. Statistical modelling was performed using MINITAB version 18 statistical package. The Anderson-Darling goodness-of-fit test was used to show how well the selected statistical distribution fits the water-consumption data.

Original languageEnglish
Pages (from-to)375-383
Number of pages9
JournalJournal of Water Supply: Research and Technology - AQUA
Volume67
Issue number4
Early online date11 May 2018
DOIs
Publication statusPublished - 1 Jun 2018

Keywords

  • Anderson-darling statistical test
  • Log-logistic distribution
  • MINITAB
  • Probability distribution function
  • Random nature
  • Water demand

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