Multicriterion decision making in irrigation planning |
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| Institution: | 1. Department of Civil Engineering, S.E.S. College of Engineering, Kopargaon 423 603, India;2. Department of Civil Engineering, Indian Institute of Technology, Kharagpur 721 302, India;1. School of Mechanical Engineering, KIIT University, Bhubaneswar, Odisha 751024, India;2. Mechanical Engineering Department, Sikkim Manipal Institute of Technology, Majhitar, Sikkim 737136, India;1. State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China;2. Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China;3. School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, China;4. Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada;1. School of Water Conservancy Engineering, Zhengzhou University, Zhengzhou, 450001, China;2. Zhengzhou Key Laboratory of Water Resource and Environment, Zhengzhou, 450001, China;3. Henan Key Laboratory of Groundwater Pollution Prevention and Rehabilitation, Zhengzhou, 450001, China;4. Capital University of Economics and Business, Beijing, 100070, China;5. School of Environment, Beijing Normal University, Beijing, 100875, China;6. Department of Civil and Environmental Engineering, Brunel University London, Uxbridge, UB8 3PH, United Kingdom;1. School of Energy and Environmental Engineering, University of Science Technology Beijing, Beijing, 100083, China;2. School of Economics and Management, Beijing University of Technology, Beijing, 100124, China;3. Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Sask, S4S 0A2, Canada |
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| Abstract: | Selection of the best compromise irrigation plan is examined in the multi objective context. The study deals with three conflicting objectives: net benefits, agricultural production and labour employment. Three-stage procedure is adopted combining multi objective optimisation, cluster analysis and multicriterion decision-making (MCDM) methods. Two MCDM methods, namely, PROMETHEE-2 and a newly developed method EXPROM-2, are employed in the evaluation. Spearman rank correlation test is used to assess the correlation between the ranks. The above methodology is applied to a case study of Sri Ram Sagar Project, Andhra Pradesh, India. Sensitivity analysis studies indicated that ranking pattern is quite robust to parameter changes as far as the first two positions are concerned. It is found that net benefits, agricultural production and labour employment per hectare on average for the culturable command area are 8980 rupees ($225), 3.73 tonnes and 242 man-days, respectively, in the best compromise plan. |
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