Development of a Fuzzy Decision Support System for Irrigation Network Operation Under Water Scarcity Conditions

Document Type : Methodologies

Authors

1 Ph.D. Student, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

2 Associate Professor, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

3 Assistant Professor, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

Abstract

Inefficient irrigation and drainage networks lead to an increase in the gap between water supply and demand, especially under water scarcity conditions. Proper operation of irrigation networks plays an important role in ensuring water supply and demand management. This requires the implementation of a comprehensive approach to making the right decisions at the time of operation. The design of this approach is complex due to the existence of conflicts of interest, uncertainty, and the intrinsic complexity of irrigation network operation topics. In Iran, current practices in irrigation network operations rely on personal experiences and lack comprehensive decision-making tools. This study proposes a fuzzy decision support system to address this challenge. The fuzzy decision support system leverages a fuzzy conceptual model to capture the inherent complexity and uncertainty of irrigation networks. It utilizes a systems approach to identify problems, propose key decision options, and evaluate various solutions. The study emphasizes the effectiveness of multi-criteria decision-making methods for handling complex irrigation network issues. An example of the results of structuring the decision-making process, along with the development of a hierarchical analysis method that is combined with fuzzy set theory (FAHP), is presented in this paper. This shows how the fuzzy decision support system structure can be applied in a real-world irrigation network. Implementing such a system in irrigation management companies is expected to improve water distribution indicators by enabling data-driven, informed decision-making.

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