Abstract
Precise performance assessment of irrigation projects is a difficult task due to several uncertainties and ambiguity in some operation and maintenance parameters. This work proposes a fuzzy-based methodology to assess these projects using the major criteria of technical, managerial, environmental, social, and economic aspects. Twenty-one sub-criteria indicators are considered for the assessing process. The methodology is developed based on the well-known, multi-criteria decision method of Analytical Hierarchy Process (AHP) and fuzzy triangular numbers. The approach is applied to four irrigation projects, and the results demonstrate that the managerial criterion has the greatest impact on the assessment process. The technical, social, economical, and environmental criteria rank next in effectiveness, respectively. Hence, in order to improve irrigation system performance, all rehabilitation tasks should focus more on the managerial issues. The findings reveal that the overall score of irrigation projects is not sensitive to relative weight of an individual indicator and only large change in priority weights of several criteria has a significant effect on ranking of the irrigation projects. The most and least efficient performance values were 74.1 and 57.5%, respectively. The proposed methodology deals with uncertainty and vague data using triangular fuzzy numbers, and, moreover, it provides a comprehensive decision-making technique to assess the performance of irrigation projects.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.