Increasingly, water management models are being used in decision making contexts that involve selecting a “preferred” course of action by weighing performance against competing objectives. The role of models within the decision process is often poorly articulated, uncertainty is not well accounted, and risk only evaluated after the selection has been made. For example, the technical performance of alternative integrated urban water management options are evaluated using various models, and the results presented in a technical report. The decision makers base their selection on the predicted performance, and the preferences of the stakeholders around the table. Risk assessment is then undertaken to identify and control any areas of high risk, which might be costly or even unachievable. A well structured decision process might have resulted in a different choice. eWater CRC is delivering a range of new tools to support decision-making in the water industry, ranging from selecting water sensitive design of new urban allotments to exploring policy options for Australia’s large regulated rivers. Central to this effort is a user requirement to incorporate uncertainty analysis, risk analysis, optimisation and prioritisation into the tools. This paper describes a decision making framework that places models, and other sources of knowledge, into a decision making context. The framework articulates the role of optimisation, risk analysis and prioritisation in the decision making process and clarifies the pervasive role of uncertainty. The framework provides a guide for the inclusion of these decision elements into modelling products, either as generic software elements that can be applied to multiple models, or as supporting material such as documentation or training. Using the framework, water-management stakeholders articulate problems by iterating around a cycle that defines objectives based on an initial problem statement, and determines what metrics will be used to ascertain that the objective has been achieved within the context of a well-defined system. Different proposed solutions are then evaluated in terms of the agreed metrics, and the outcomes are compared to select the “best” solution. Selection of “best” option is achieved by including considerations beyond the direct outputs of performance prediction models. By tracking uncertainties and providing assessment methods for risk and optimisation in an environment of compound considerations, a rational and scientifically justified suite of preferred options can be generated. These preferred solutions in turn inform a multi-objective decision process, which allows stakeholders to express preferences and assign weightings to make their final choice, while making full use of the outcomes of detailed scientific analysis. An understanding of the quality of the evidence used to support each step of the process enhances the value of the decision support. The decision framework complements a common model structure that is used to integrate the various component models developed by eWater CRC. Together the decision framework and the common model structure form the conceptual architecture of the eWater product offering.
18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. The 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation: Proceedings (Cairns, Qld 13-17 July, 2009) p. 3775-3781