Assessing the likelihood of realizing idealized goals: the case of urban water strategies
Urban water management can be challenging, but in Small Island Developing States it is particularly difficult due to resource constraints and isolation. This is the situation in the town of Tarawa in Kiribati, where attempts to improve water services have often not led to the desired outcomes. The reasons are varied, and include widely a lack of consideration of local circumstances, process requirements, and inadequate involvement of affected stakeholders, and inadequate cross-sectoral coordination. In light of the tendency in urban water planning to assume only the idealized performance of strategies, the authors argue that there is a need to also formally consider the likelihood of realizing this idealized performance. It is difficult to assess such likelihoods, other than via the use of judgments by expert and local stakeholders. Such judgments are typically qualitative and fairly abstract and often not directly concerning a particular strategy. The current paper provides a methodology to assess the likelihood of the idealized performance of strategies, based on Bayesian Networks (BNs) and Subjective Logic (SL) utilizing expert and local knowledge, creating a capacity to capture and apply previous experiences, and dispersed knowledge in decision making and planning. The methodology has been developed and tested on water management strategies in the town of Tarawa, Kiribati. As such, this paper provides a method for mapping the causal explanations for why developments do not achieve their set goals, and the approach may form the basis for assessments to be more widely applied when evaluating urban water strategies in similar contexts. In this paper, the approach has been applied by using existing data from interviews and literature to evaluate one strategy, reserve extensions and groundwater extraction. Other strategies, i.e. rainwater harvesting, desalination and have also been evaluated but have not been described in this paper because of limited space. 2012 Elsevier Ltd. All rights reserved.
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