Prioritization of Water Consumption Management Strategies in Water Distribution Networks Using Multiple Criteria Decision Making Method of Fuzzy Analytic Hierarchy Process (Case Study: Tehran)

Document Type : Research Article


1 School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran

2 College of Abourayhan, University of Tehran, Tehran, Iran


As the volume of renewable water resources has been significantly decreased and developing new water resources are faced with serious limitations, there has been a change of emphasis in management practices from supply-sided to demand-sided approaches in most regions of the world. Water consumption management strategies seek to reduce water consumption and establish a reasonable and sustainable balance between water supply and demand. In this paper, a multi-attribute decisionmaking method and an algorithm is developed for selecting water consumption management strategies for water distribution networks. To demonstrate the applicability of suggested method, a case study is conducted in Tehran in which different water consumption management strategies are prioritized using Fuzzy Analytic Hierarchy Process (FAHP) and based on water and wastewater experts’ judgments. Applied strategies are performing educational programs among water users, non-revenue water reduction, increasing water price and using water-saving appliances. Furthermore, decision criteria used in this study are costs, time of implementation, water user’s satisfaction, the volume of non-revenue water and water-saving efficacy. To evaluate the impact of uncertainties lied in the model on final results, a sensitivity analysis is performed in terms of changes in the weight of decision-makers’ judgments and the shape of fuzzy membership functions. Finally, the non-revenue water reduction is gained the first rank among all water consumption management strategies. The results of this study show that in case of high degree of fuzzy uncertainties and dearth of sufficient quantitative data, the presented method can be employed as a robust decision-making tool by urban water managers.

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