Using Best Worst Scaling to prioritise issues in major river catchments: The Murray Darling Basin in Australia

Abstract

There is an increasing focus on improving environmental health in major river catchments to address pressures from extensive modification and overuse. However, river catchments often involve many complex and competing uses, making it difficult to prioritise where remediation actions should be concentrated. In this research, the Best Worst Scaling (BWS) technique is applied to assess community views about the relative importance of multiple major issues in the Murray Darling Basin that span environmental, social, economic, and cultural dimensions. The BWS technique was applied by identifying 16 major issues relevant to river management, generating a statement for each, and then using an experimental design to create profiles with four statements each. A random sample of respondents across New South Wales were each presented with four profiles and asked to identify the statement that they agreed with most and least for each profile. The results, analysed through both counting and logistic regression methods, show that the community prioritized environmental issues over economic, social, and cultural aspects. Improved water quality, native animals, water flow management and fish populations were identified as greater priority issues with both the logit model and counting model approaches. The analysis demonstrates how application of the logit model generates greater insights than is available with the counting approach.