Publication:
Development of a decision support approach for sustainable urban water management

dc.contributor.advisor Moore, Stephen en_US
dc.contributor.advisor Lundie, Sven en_US
dc.contributor.advisor Ashbolt, Nicholas J. en_US
dc.contributor.advisor Lu, Jie en_US
dc.contributor.author Lai, Elizabeth en_US
dc.date.accessioned 2022-03-23T19:08:09Z
dc.date.available 2022-03-23T19:08:09Z
dc.date.issued 2011 en_US
dc.description.abstract The challenges of climate change, increasing population and drought have motivated water authorities around Australia to deliver water services more sustainably. Many of them have recently devised long-term water strategies using multi-criteria decision aid (MCDA) to assess their strategies. This thesis identified four shortcomings in the current practice of MCDA used in urban water management: (1) double counting, (2) judgement uncertainty, (3) interaction and (4) range sensitivity. The aim of this research was to account for these shortcomings, thereby aiding decision makers in their planning of more sustainable water strategies. A decision support approach was developed to address the shortcomings, and utilised: (1) value focused thinking, to carefully structure the criteria value tree; (2) fuzzy sets, to account for uncertainty in decision makers’ judgements on criteria weights and criteria scores; (3) the Choquet integral, to model interaction between criteria in conjunction with a linguistic preference elicitation technique; and (4) a novel technique to elicit criteria weights and to normalise criteria scores based on the concept of mitigation. The developed framework was applied to an empirical case study, the Gold Coast Waterfuture project to illustrate the approach. This involved interviewing three groups of decision makers (DMs)—water users, water experts and water managers—to elicit their preferences in relation to different water strategies. The results obtained using the framework were closer to the decision makers’ preferences, as compared to the conventional which neglects the identified shortcomings. The main finding was that the selection of an appropriate preference model is critically related to the DMs’ level of understanding of the decision problem. An averaging function can serve as a good initial approximation when no uncertainty is considered. More computationally demanding preference models which use fuzzy set theory and Choquet integral should only be used if the DMs have to make imprecise judgement with insufficient information and/or the DMs have a sufficient understanding of the interaction between the selected criteria. The practical application of this research is in providing decision makers with a stronger set of tools that include a modified and more rigorous MCDA which overcomes the shortcomings in the current practice. en_US
dc.identifier.uri http://hdl.handle.net/1959.4/51316
dc.language English
dc.language.iso EN en_US
dc.publisher UNSW, Sydney en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/3.0/au/ en_US
dc.subject.other choquet integral en_US
dc.subject.other Sustainability en_US
dc.subject.other Water en_US
dc.subject.other Decision en_US
dc.subject.other Uncertainty en_US
dc.subject.other Interaction en_US
dc.title Development of a decision support approach for sustainable urban water management en_US
dc.type Thesis en_US
dcterms.accessRights open access
dcterms.rightsHolder Lai, Elizabeth
dspace.entity.type Publication en_US
unsw.accessRights.uri https://purl.org/coar/access_right/c_abf2
unsw.identifier.doi https://doi.org/10.26190/unsworks/23870
unsw.relation.faculty Engineering
unsw.relation.originalPublicationAffiliation Lai, Elizabeth, Civil & Environmental Engineering, Faculty of Engineering, UNSW en_US
unsw.relation.originalPublicationAffiliation Moore, Stephen , Civil & Environmental Engineering, Faculty of Engineering, UNSW en_US
unsw.relation.originalPublicationAffiliation Lundie, Sven, Civil & Environmental Engineering, Faculty of Engineering, UNSW en_US
unsw.relation.originalPublicationAffiliation Ashbolt, Nicholas J., Civil & Environmental Engineering, Faculty of Engineering, UNSW en_US
unsw.relation.originalPublicationAffiliation Lu, Jie, Faculty of Information Technology, University of Technology, Sydney en_US
unsw.relation.school School of Civil and Environmental Engineering *
unsw.thesis.degreetype PhD Doctorate en_US
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