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Comparison of Compensatory and non-Compensatory Multi Criteria Decision Making Models in Water Resources Strategic Management

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Abstract

Growing water demands as well as inconsistency between water demand and water supply pose new challenges for water resources managers in arid regions. This study examines the strategies to tackle water shortage for a sustainable development in Shahrood, Iran. A contentious plan has been proposed to transfer water from the Caspian Sea in north of Iran to this region. Ensuring sustainable development, however, necessitates a strategic planning for water resources. The study develops all viable strategies for the region using Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis. Due to inability of the SWOT model to rank the alternatives, the developed strategies are ranked using Multi Criteria Decision Making (MCDM) models based on specified sustainable development criteria. The ranking is implemented using the compensatory models of Simple Additive Weighting (SAW) and Analytical Hierarchy Process (AHP), and the non-compensatory model of ELimination and Choice Translating REality (ELECTRE III). The results of all MCDM models introduce water transfer as the worst strategy for the region. Because of the uncertainty in the relative importance of specified criteria, sensitivity analysis is done for MCDM models by altering the criteria weights. The results show that the ELECTRE III method has lower sensitivity than the SAW and AHP methods to changes in the weights. Also, the compensatory methods exhibits a high dependency to the weights of some dominant criteria. Therefore, this research reveals that the rankings obtained from the ELECTRE III method are more reliable for decision makers to ensure a sustainable development in the region.

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Correspondence to Mohammad Ebrahim Banihabib.

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Banihabib, M.E., Hashemi-Madani, FS. & Forghani, A. Comparison of Compensatory and non-Compensatory Multi Criteria Decision Making Models in Water Resources Strategic Management. Water Resour Manage 31, 3745–3759 (2017). https://doi.org/10.1007/s11269-017-1702-x

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