Ranking and classification of irrigation system performance using fuzzy set theory: case studies in Australia and China

Abstract

A methodology for ranking and classifying performance of irrigation systems through multidimensional performance indicators is developed using fuzzy set theory. The procedure uses the concepts of fuzzy resemblance and fuzzy dominance. Preference levels reflecting management priorities are incorporated into the analysis using appropriate weighting factors. The application of the procedure is demonstrated through two case studies: the Shi-Jin irrigation district in Hebei Province, China and the Goulburn irrigation region in Victoria, Australia. The classification of performance periods for the Australian system shows three clusters indicating the predominant effect of the increase in waterlogged area when higher priority is given to this indicator. No clear trend appeared when equal weight was assigned to all indicators. The effect of economic reforms implemented in 1977–78 in China is clearly reflected in the resulting ranking and clustering of the performance periods in the Shi-Jin irrigation district. Performance levels following reforms are shown to be consistently higher.