Inter-basin water transfer planning with grey COPRAS and fuzzy COPRAS techniques: A case study in Iranian Central Plateau.

To overcome water scarcity and increasing water demands, achieving economic and social development, and to make regional equilibrium especially in countries with climate variations such as Iran, the inter-basin water transfer is considered as one of the crisis reduction methods. In this study, the COPRAS method, which is one of the new MCDM methods, is used for the first time to evaluate inter-basin water transfer projects in three configurations of integer, fuzzy, and grey (intervals). For this purpose, eight inter-basin water transfer scenarios from the Great Karoon Basin to the Central Iranian Plateau, are determined with the aim of overcoming drinking water scarcity. They are assessed by four important and practical criteria for inter-basin water transfer, including technical risks and the difficulty of execution, political and social problems, environmental problems, and cost per cubic meter of water according to the UNESCO standards. The weights of the criteria were obtained using three methods of AHP, DEMATEL, and Shannon entropy in the integer, fuzzy, and grey ways. Then, scenarios were prioritized using the COPRAS method. Finally, the results were ranked using the Borda count method, which is a method to aggregate the different ranking models. In this study, the results showed that among the criteria, technical risks, and then the cost per cubic meter of water are the essential criteria, respectively. Considering all ranking methods shows that among the scenarios, the eighth scenario, including water transfer from Behesht-Abad basin to Isfahan province and from Kharsan basin to Yazd and Kerman provinces, is superior to the other scenarios. Final COPRAS value of this scenario varies between 0.155 and 0.194 depending on the applied ranking method, and its total Borda score is 63. The findings of this study can help the decision-makers to evaluate the inter-basin water transfer projects in uncertain conditions.