Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/58173
Type: Conference paper
Title: MORE and POMORE sensitivity analysis of salt interception schemes in the River Murray
Author: Ravalico, J.
Maier, H.
Dandy, G.
Citation: The 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation, Cairns, Australia from 13–17 July 2009 / R. S. Anderssen, R. D. Braddock and L. T. H. Newham (eds.): pp.3208-3215
Publisher: The Modelling & Simulation Society of Australia & NZ Inc
Publisher Place: Australia
Issue Date: 2009
ISBN: 9780975840078
Conference Name: World IMACS and MODSIM09 International Congress (18th : 2009 : Cairns, Qld)
Editor: Anderssen, R.S.
Braddock, R.D.
Newham, L.T.H.
Statement of
Responsibility: 
Ravalico, J. K., H. R. Maier and G. C. Dandy
Abstract: The MSM-BIGMOD model of the River Murray is a comprehensive flow and salinity routing model, used to assess the impacts of potential changes in river management on river flow and salinity levels. The modelling suite consists of a combination of two models (MSM and BIGMOD) that have been developed over a period of years. Sensitivity analysis of the model is particularly important, given that decisions are made about management of the River Murray based on outputs from the model. The large number of model inputs and parameters arising from the inclusion of the many tributaries, storages, drains, and diversions pose a challenge for traditional sensitivity analysis methods, such as one-at-a-time parameter perturbation methods. The Management Option Rank Equivalence (MORE) method of sensitivity analysis and the expanded Pareto Optimal Management Option Rank Equivalence (POMORE) are innovative methods of sensitivity analysis developed especially for use with complex models used for decision-making. The methods assess the sensitivity of management decisions based on model output, to changes in the model inputs, in order to provide a sensitivity analysis in the decision context. MORE searches the parameter space to find parameter combinations that result in an equal preference of two management options that are closest in Euclidean distance to the calibrated model parameters. POMORE searches similarly for parameter combinations that result in an equal preference of two management options; however, it uses a Pareto optimal search to determine the combinations which are the most similar to the original calibrated parameters. The difference in the search criteria, allows POMORE to find several solutions, allowing further categorisation of sensitivity throughout the parameter space. A sensitivity analysis of the MSM-BIGMOD model of the River Murray using MORE and POMORE is presented in this research. The analysis investigates the sensitivity of the decision to improve a salt interception scheme (SIS) based on the net present value of the savings due to a reduction in the salinity of water used for irrigation, domestic and industrial use, to changes in the cost parameters, the crop yield reduction parameters, and the salt removal parameters. The model is found to be reasonably robust, with a change of 37.5% of the maximum possible change in parameters required in order to alter the decision. However the sensitivity varies throughout the parameter space, indicated by a further 30.2% change of the maximum possible, required to ensure that the decision will change. This variation in sensitivity throughout the parameter space, has shown that there is a need for further sensitivity analysis, and as such POMORE is used to gain additional information about other sensitive regions. This research demonstrates a comprehensive use of the MORE and POMORE methods of sensitivity analysis on a case study which poses considerable problems for traditional sensitivity analysis methods. The results obtained in the case study demonstrate the value of the MORE and POMORE approaches and the extremely useful information that they provide to decision-makers.
Keywords: MORE, POMORE
sensitivity analysis
multi-objective optimization
decision-making
genetic algorithm
pareto dominance
Rights: Copyright status unknown
Description (link): http://www.mssanz.org.au/modsim09/
Published version: http://www.mssanz.org.au/modsim09/I2/ravalico.pdf
Appears in Collections:Aurora harvest
Civil and Environmental Engineering publications
Environment Institute publications

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