An investigation into identifying factors and building models for prediction of water usage in regional Australia

Nooriafshar, Mehryar and Maraseni, Tek Narayan (2006) An investigation into identifying factors and building models for prediction of water usage in regional Australia. In: 5th Annual Hawaii International Conference on Statistics, Mathematics and Related Fields, 16-18 Jan 2006, Honolulu, Hawaii, USA.

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Abstract

This paper is based on a research project with the aim of developing a suitable model for future water consumption in Toowoomba, Queensland, Australia. The project’s main aims were to, systematically, investigate the contributory factors in water usage and then build a mathematical model for prediction and performing sensitivity analysis. Water is without any doubt the most important resource used in farming, industrial and domestic applications. Hence, this project is timely and very appropriate in terms of meeting the needs of the community in and around Toowoomba.

The paper demonstrates how the most suitable multiple regression models were built in a progressive manner. For instance, a systematic investigation into the accuracy of models has revealed that by incorporating three dummy variables and using those in conjunction with either the city population or the number of dwellings in the city would produce the most accurate results. These dummy variables represented the presence or absence of tariff, restrictions rebate and dry weather.

Statistics for this ePrint Item

Item Type:	Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed:	Yes
Item Status:	Live Archive
Additional Information:	Authors retain copyright.
Depositing User:	Dr Mehryar Nooriafshar
Faculty / Department / School:	Historic - Faculty of Business - Department of Management and Organisational Behaviour
Date Deposited:	25 Jan 2010 13:06
Last Modified:	02 Jul 2013 23:37
Uncontrolled Keywords:	consumption; multiple regression; dummy variables
Fields of Research :	01 Mathematical Sciences > 0104 Statistics > 010401 Applied Statistics 09 Engineering > 0907 Environmental Engineering > 090702 Environmental Engineering Modelling 09 Engineering > 0905 Civil Engineering > 090509 Water Resources Engineering
Socio-Economic Objective:	D Environment > 96 Environment > 9609 Land and Water Management > 960912 Urban and Industrial Water Management
URI:	http://eprints.usq.edu.au/id/eprint/6689

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