Surendran, Seevali, Tota-Maharaj, Kiran and Chen, Hua-Peng (2016) Validation of log logistic distribution to model water demand using UK and North American data. In: 8th International Perspective on Water Resources and the Environmen, 4th - 6th January, 2016, Colombo, Sri Lanka.

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Abstract

There is a general assumption that potable water consumption is stochastic in nature with increasing in recognition of the need to allow for this when planning, designing or assessing the performance of water distribution systems. The stochastic nature of water demand is best addressed by fitting water demand into a suitable probability distribution. It is often assumed that variations in water demands follow a normal distribution without adequate justification. However, there had been insufficient studies previously to conclude the suitability of the appropriate probability distribution functions in modelling water demand. The purpose of this study is to validate an appropriate probability density function to apply in simulating water demand using real water consumption data. Daily water consumption data for five years obtained from a water company in Canada and four years for UK are analysed using normal, log normal, log logistic and Weibull distributions and a comparison on the applicability of each distribution was assessed. Statistical modelling was performed using MINITAB. The Anderson Darling (AD) statistic was used as the goodness of fit parameter in the analysis.

Item Type:	Conference or Conference Paper (Paper)
Uncontrolled Keywords:	water demand; stochastic nature; probability distribution function; log logistic distribution; Minitab; Anderson Darling
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > Q Science (General) T Technology > TC Hydraulic engineering. Ocean engineering
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Engineering (ENG)
Related URLs:	Publisher http://www.ft.lk/article/409553/Sri-Lank...
Last Modified:	18 Jan 2024 10:49
URI:	http://gala.gre.ac.uk/id/eprint/14578

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