Application of Multi Criteria Decision Making models in Site selection of the Khersan-1 Dam and Hydropower plant

Subject Areas : Article frome a thesis

Abbas Roozbahani ¹ , Mahshid Shahbazi Sehrani ²

1 - استادیار گروه آبیاری و زهکشی، پردیس ابوریحان، دانشگاه تهران
2 - دانشجوی کارشناسی ارشد مهندسی عمران-محیط زیست، دانشگاه خواجه نصیرالدین طوسی

Received: 2016-10-24 Accepted : 2016-10-24 Published : 2016-06-21

Keywords: TOPSIS, AHP, SAW, MCDM, dam construction projects,

Abstract :

Recently, water resources development projects and their selectivity have received much attention due to the accelerating population growth and their water requirements. The aim of this research is an application of the multi criteria decision making (MCDM) models in the proper selection and prioritization of dam construction projects. Application of three groups of MCDMs including SAW (simple additive weighing), AHP (analytic hierarchy process) and TOPSIS (techniques for order preference by similarity to ideal solution) have been discussed to select the best site and type of reservoir considering the important decision making criteria. To explain the effectiveness of the mentioned models, a case study is presented on the site selection of the Khersan-1 Dam and hydropower Plant in the province of Chaharmahal & Bakhtiari benefiting from opinions given by some experts and decision makers. The results of an application of these three methods have been analyzed using the Borda method and the best alternative has been selected. To this end, the screening has been Performed for 6 primary axes A to F, and three different alternatives: an arch concrete dam located on the D axis, a gravel dam located on the D axis, and an arch concrete dam located on the F axis were compared with respect to 8 quantitative and qualitative economic and technical criteria. The results confirmed that an arch concrete dam located on the D axis was the best alternative. This research can help the water industry for accurate management of dam construction projects using the novel decision making models combined with expert opinion.

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