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Conventionally, irrigation development planning has been based on cropping pattern selection aiming at maximizing the revenue from irrigation activities. In the real world however, several complexities make the cropping pattern selection a more complicated mathematical problem. Of great interest is the case of water supply from multiple sources (e.g. surface and groundwater) in which a multi-criteria approach is most appropriate. Goal programming has been used in the past to solve cropping pattern selection problems, with criteria of a similar nature, the net benefit being included as a constraint. This paper presents a methodology, based on the fuzzy set theory, for enhancing the goal programming approach to solve similar problems under various sets of criteria of a different nature. In the proposed methodology the net benefit maximization is considered together with all other criteria. The methodology is illustrated using data from the Thessaly Plain in Greece. [ABSTRACT FROM AUTHOR]