Effectiveness of log-logistic distribution to model water-consumption data 1 2 Seevali Surendran 1,2 * and Kiran Tota-Maharaj 1 3 4 1 Faculty of Environment and Technology, University of the West of England, Bristol (UWE 5 Bristol), Bristol, BS16 1QY, UK; 2 Environment Agency, Kings Meadow House, Kings 6 Meadow Road, Reading, RG1 8DQ, UK. *Corresponding author Email: 7 seevali.surendran@environment-agency.gov.uk 8 9 ABSTRACT 10 Water consumption varies with time of use, season and socio-economic status of consumers, and 11 is defined as a continuous random variable. Incorporating probabilistic nature in water- 12 consumption modelling will lead to more realistic assessments of performance of water 13 distribution systems. Furthermore, fitting water-consumption patterns into a suitable statistical 14 distribution will assist in determining how often peaks will occur, or the probability of exceeding 15 the peaking factor in a system, for incorporation into design calculations. There are few studies 16 in the literature where the random variations of consumption have been considered. The purpose 17 of this study is to evaluate real water-consumption data from the United Kingdom (UK) and 18 North America and to investigate the possibility of establishing a standard probability 19 distribution function to apply in simulating water consumption in developed countries. Daily 20 water-consumption data for five years (2009–2013) were obtained from water companies in the 21 UK and North America and analysed by fitting into normal, log-normal, log-logistic and Weibull 22 distributions. Statistical modelling was performed using MINITAB version 18 statistical 23 package. The Anderson-Darling goodness-of-fit test was used to show how well the selected 24 statistical distribution fits the water-consumption data. 25 26 KEYWORDS | Anderson-Darling statistical test, log logistic distribution, MINITAB, 27 probability distribution function, random nature, water demand 28 29