Uncertainty analysis in a GIS-based multi-criteria analysis tool for river catchment management

Abstract: The importance of uncertainty analysis has been increasingly recognised, due to the influence of uncertainties in data, models and expert judgements. However, the successful integration of uncertainty analysis into multi-criteria analysis (MCA) has rarely been achieved. This paper analyses uncertainty sources in MCA. General methods of uncertainty analysis in MCA are reviewed, including probabilistic methods, indicator-based methods and fuzzy logic. Building on this review, an uncertainty analysis module developed for use within a GIS-based MCA tool for catchment management is presented. In this module, the influence of uncertainties on decision-making can be visually explored using an indicator-based method. The indicator-based method provides a pragmatic approach to communicating areas of uncertainty to decision-makers without assuming any prior knowledge of uncertainty analysis techniques. This enables uncertainty analysis to be more effectively operationalised within the decision-making process. An application example in the Tamar catchment, southwest UK, is used to illustrate the capability of the uncertainty analysis module when applied in a decision-making context. [Copyright &y& Elsevier]