Keywords
Multi-Criteria Decision Analysis; Preference Neutral; Murray-Darling Basin; Principal Component Analysis; Cluster Analysis
Start Date
15-9-2020 1:00 PM
End Date
15-9-2020 1:20 PM
Abstract
Historical over allocation of water resources has led to the degradation of many river systems, including in the Murray-Darling Basin, Australia. Water resource managers must balance the trade-offs between socio-economic and hydro-ecological benefits. Multi-Criteria Decision Analysis (MCDA) can help inform decision makers of the outcomes of different management alternatives by examining impacts on decision criteria. We examine results from an integrated environmental model, the Campaspe Integrated Model (CIM), developed for the Lower Campaspe catchment. The CIM provides indicative catchment-scale responses to policy options and farmer decisions under different climatic scenarios, in terms of water use, farm productivity, and suitability of river flows for ecological health. A companion model provides additional indication of impact on local employment. The CIM was run in an exploratory manner, results of which were then analysed using a combination of Principal Component Analysis (PCA) and K-means cluster analysis, to determine the correlation between performance criteria variables and examine evidence of clustering of output scenarios. Clusters were examined to determine whether data were grouped with regards to criteria performance. Finally, a preference neutral Multi-Criteria Decision Analysis was used to rank input combination scenarios that result in above average criteria performance. A range of model scenarios were elicited through a participatory process including workshops with local water managers and a catchment-wide survey of farmers. The analysis process allows outcomes of water resource allocation actions to be examined without the need to elicit preferences from stakeholders. The adopted approach restricts influence of bias from modellers, through the exploratory approach, and stakeholders through the MCDA analysis. This analysis could therefore be used to inform decision makers of the impacts of their actions and to provide a more objective examination of water allocation decisions.
A Preference Neutral Multi-Criteria Decision Analysis of Water Allocations in the Murray-Darling Basin, Australia
Historical over allocation of water resources has led to the degradation of many river systems, including in the Murray-Darling Basin, Australia. Water resource managers must balance the trade-offs between socio-economic and hydro-ecological benefits. Multi-Criteria Decision Analysis (MCDA) can help inform decision makers of the outcomes of different management alternatives by examining impacts on decision criteria. We examine results from an integrated environmental model, the Campaspe Integrated Model (CIM), developed for the Lower Campaspe catchment. The CIM provides indicative catchment-scale responses to policy options and farmer decisions under different climatic scenarios, in terms of water use, farm productivity, and suitability of river flows for ecological health. A companion model provides additional indication of impact on local employment. The CIM was run in an exploratory manner, results of which were then analysed using a combination of Principal Component Analysis (PCA) and K-means cluster analysis, to determine the correlation between performance criteria variables and examine evidence of clustering of output scenarios. Clusters were examined to determine whether data were grouped with regards to criteria performance. Finally, a preference neutral Multi-Criteria Decision Analysis was used to rank input combination scenarios that result in above average criteria performance. A range of model scenarios were elicited through a participatory process including workshops with local water managers and a catchment-wide survey of farmers. The analysis process allows outcomes of water resource allocation actions to be examined without the need to elicit preferences from stakeholders. The adopted approach restricts influence of bias from modellers, through the exploratory approach, and stakeholders through the MCDA analysis. This analysis could therefore be used to inform decision makers of the impacts of their actions and to provide a more objective examination of water allocation decisions.
Stream and Session
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