Management Option Rank Equivalence (MORE) - A new method of sensitivity analysis for decision-making

Abstract

Models used to aid decision-making often incorporate knowledge from various disciplines to provide an overarching assessment of the impact of different management decisions. Such models generally require numerous parameters from varying sources; many of which are not known with certainty. Rapid increases in model size and complexity, particularly in the case of integrated models used to assist decision-making, pose new challenges for effective sensitivity analysis. In particular, the sensitivity that is of interest is often that of the decision being made to the model's varying inputs and parameters. The Management Option Rank Equivalence (MORE) method of sensitivity analysis has been developed specifically for use with models used to assist decision-making. The method operates on the assumption that model outputs will result in a ranking of management options. Where models are used to assist decision-making it is important to ensure that the solution is robust and that rankings will not alter with small changes in model inputs. MORE uses numerical optimisation methods in order to determine the smallest and largest changes in model inputs and parameters that will result in a change of the ranking of management options. This allows a translation of the set of acceptable model outcomes into a corresponding range of model inputs, thus allowing decision-makers to directly assess whether current certainties of model inputs are adequate for differentiating between management options. The MORE method is demonstrated using a mathematical test model, as well as a case study of the MSM-BIGMOD flow and salinity model of the River Murray in South-Eastern Australia. © 2009 Elsevier Ltd. All rights reserved.