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Title: Uncertainty in Environmental Decision-Making: Issues, Challenges and Future Directions

Author
item MAIER, HOLGER - UNIVERSITY OF ADELAIDE
item Ascough Ii, James
item WATTENBACH, MARTIN - UNIVERSITY OF ABERDEEN
item RENSCHLER, CHRIS - UNIVERSITY OF BUFFALO
item LABIOSA, W. - STANFORD UNIVERSITY
item RAVALICO, JAKIN - UNIVERSITY OF ADELAIDE

Submitted to: Environmental Modelling & Software
Publication Type: Book / Chapter
Publication Acceptance Date: 5/14/2007
Publication Date: 10/17/2008
Citation: Maier, H.R., Ascough Ii, J.C., Wattenbach, M., Renschler, C.S., Labiosa, W.B., Ravalico, J.K. 2008. Uncertainty in Environmental Decision-Making: Issues, Challenges and Future Directions. Environmental Modeling & Software.

Interpretive Summary: Environmental decision-making is complicated by the complexity of natural systems and the often competing needs of multiple stakeholders. Modelling tools are often used to assist at various stages of the environmental decision-making process. If such models are to provide effective decision support, the uncertainties associated with all aspects of the decision-making process need to be accounted for explicitly. However, as models become more complex to better represent integrated environmental, social and economic systems, achieving this goal becomes more difficult. Some of the important issues discussed in this paper that need to be addressed in relation to the incorporation of uncertainty in environmental decision-making processes include: 1) the development of appropriate risk-based performance criteria that are understood and accepted by a range of scientific disciplines; 2) the development of methods for quantifying the uncertainty associated with human input; 3) the development of approaches and strategies for increasing the computational efficiency of integrated models, optimization methods, and methods for estimating risk-based performance measures; and 4) the development of integrated frameworks that enable all sources of uncertainty to be incorporated in the environmental decision-making process.

Technical Abstract: Environmental decision-making is complicated by the complexity of natural systems and the often competing needs of multiple stakeholders. Modelling tools are often used to assist at various stages of the environmental decision-making process. If such models are to provide effective decision support, the uncertainties associated with all aspects of the decision-making process need to be accounted for explicitly. As model complexity increases in order to better represent environmental and socio-environmental systems, there is an increased need to identify potential sources of uncertainty and to quantify their impact, so that appropriate management quantification of certain aspects of uncertainty, such as the development of risk-based options can be identified with confidence. Many studies have focused on the identification and performance measures and the incorporation of uncertainty into environmental models, optimisation methods, multicriteria methods, decision-support tools, and adaptive management systems. However, there is a need to examine the decision-making process in an integrated fashion, in order to identify all sources of uncertainty and ways of incorporating them into the decision-making process. Recent research studies have focused on modelling uncertainty in an integrated decision analysis context. In addition, several regional, cooperative research efforts are underway at present to address this problem including the Harmoni-CA project in Europe, the eWater Co-operative Research Centre in Australia, and the Interagency Steering Committee on Multimedia Environmental Models-Workgroup 2: Uncertainty Analysis and Parameter Estimation in the United States. In order to build upon these efforts, the overall objectives of this paper are to discuss the major steps in the environmental decision-making process and identify possible sources of uncertainty at each stage of the environmental decision-making process. In addition, we discuss important issues that need to be addressed in relation to the incorporation of uncertainty in environmental decision-making processes including: 1) the development of appropriate risk-based performance criteria that are understood and accepted by a range of scientific disciplines; 2) the development of methods for quantifying the uncertainty associated with human input; 3) the development of approaches and strategies for increasing the computational efficiency of integrated models, optimization methods, and methods for estimating risk-based performance measures; and 4) the development of integrated frameworks that enable all sources of uncertainty to be incorporated in the environmental decision-making process.