Application of Compromise Programming Method and Fuzzy-Spatial Indicators for Assessment of Water Allocation Scenarios, (Case Study; Aras Basin)

Document Type : Research Paper

Authors

1 PhD student of Water Engineering, Department of Water Resources Engineering, Faculty of Water Engineering, University of Shahid Beheshti, Tehran, Iran.

2 Associate Professor, Department of Irrigation & Reclamation Engineering, Faculty of Agricultural Engineering & Technology, University of Tehran, Karaj, Iran.

3 Associate Professor, Department of Water Resources Engineering, Faculty of Water Engineering, University of Shahid Beheshti, Tehran, Iran.

4 Professor, Department of Irrigation & Reclamation Engineering, Faculty of Agricultural Engineering & Technology, University of Tehran, Karaj, Iran.

Abstract

  In the context of integrated water resources management, assessment of water allocation scenarios is very important and complex. There are different and sometimes conflicting indicators in water resources management that have different values in different areas. Regarding this, evaluation of allocation scenarios involves performing the spatial multi-criteria analysis. The aim of this study was to evaluate water resources allocation scenarios using a spatial decision support system. Therefore, the compromise programming method with the economic, social and environmental indicators has been implemented in the Aras basin. In the first step, the indicators were considered as lumped and distributed form with equal weight. In the second step, the sensitivity of the compromise programming method was analyzed changing one of the indicators weight, while maintaining the other indicators constant. In step three, group and fuzzy decision making approach was used to determine the weight of the indicators. Then, scenarios 1 to 5 ranked fifth, third, second, first and fourth respectively. The results of this study showed implementing spatial distribution of indicators influence both scores and rankings of the water resources allocation scenarios. So that the Spearman correlation coefficient of the rankings, caused by application of lumped and distributed indicators, was calculated to be 0.6. Also, application of the compromise programming method, group-fuzzy weight and distributed indicators leads to a change in ranking and reduce correlation coefficient up to 0.2. Regarding the effect of two parameters, including the type of indicators and the group-fuzzy weight of indicators, on the scenarios ranking results, a significant uncertainty in the process of assessing scenarios could be occurred if the proposed parameters would not be considered. Therefore, it is essential to consider the spatial distribution of the values and the group-fuzzy decision-making should be used to determine the weight of evaluation indices.

Keywords

Main Subjects

References

Abrishamchi, A., Ebrahimian, A., Tajrishi, M. and Mariño, M. A. (2005). Case study: application of multicriteria decision making to urban water supply. Journal of water resources planning and management, 131(4), 326-335.
Adiat, K. A. N., Nawawi, M. N. M. and Abdullah, K. (2012). Assessing the accuracy of GIS-based elementary multi criteria decision analysis as a spatial prediction tool–a case of predicting potential zones of sustainable groundwater resources. Journal of Hydrology, 440, 75-89.
Afshar, A., Mariño, M. A., Saadatpour, M. and Afshar, A. (2011). Fuzzy TOPSIS multi-criteria decision analysis applied to Karun reservoirs system. Water resources management, 25(2), 545-563.
Babaei, H., Hoorfar, A. and Araghinejad, SH. (2012). Provision of a Novel and Integrated Model to Assess Regional Drought Risk. Iranian Journal of Soil and Water Research, 43(1), 123-128. (In Farsi)
Bakhtiari, E.B., Malekian, A. and Salajeghe, A. (2016). Assessment of groundwater vulnerability using Modified DRASTIC, Logistic Regression and AHP-DRASTIC (Hashtgerd plain). Iranian Journal of Soil and Water Research, 47(1), 269-279. (In Farsi)
Cai, X., Lasdon, L. and Michelsen, A. M. (2004). Group decision making in water resources planning using multiple objective analysis. Journal of Water Resources Planning and Management, 130(1), 4-14.
Calizaya, A., Meixner, O., Bengtsson, L. and Berndtsson, R. (2010). Multi-criteria decision analysis (MCDA) for integrated water resources management (IWRM) in the Lake Poopo Basin, Bolivia. Water Resources Management, 24(10), 2267-2289.
Carrick, N. A. and Ostendorf, B. (2007). Development of a spatial Decision Support System (DSS) for the Spencer Gulf penaeid prawn fishery, South Australia. Environmental Modelling & Software, 22(2), 137-148.
Chen, Y., Khan, S. and Paydar, Z. (2010). To retire or expand? A fuzzy GIS‐based spatial multi‐criteria evaluation framework for irrigated agriculture. Irrigation and Drainage: The journal of the International Commission on Irrigation and Drainage, 59(2), 174-188.
Connell, E. O., Bathurst, J., Kilsby, C., Parkin, G., Quinn, P., Younger, P., ... and Riley, M. (2000). Integrating mesoscale catchments experiments with modeling: The potential for sustainable water resources management, Fifth IHP/IAHS George Kovacs Colloquium, HELP. International Hydrological Programme, UNESCO, Paris.
Coulibaly, N., Coulibaly, L., Sengupta, S., Savanna, I. and Umesh, B. (2013). Use of Multi-criteria Evaluation and Geographic Information Systems for Water Resources Management: case of Bâoulé Basin (North-West of Côte d'Ivoire). Indian Journal of Science and Technology, 6(2), 4035-4040.
de Sousa, F. E., Moura, E. A. and Marinho-Soriano, E. (2012). Use of geographic information systems (GIS) to identify adequate sites for cultivation of the seaweed Gracilaria birdiae in Rio Grande do Norte, Northeastern Brazil. Revista Brasileira de Farmacognosia, 22(4), 868-873.
Dodge, Y. (2008). The concise encyclopedia of statistics. Springer Science & Business Media.
Hafezparast, M. (2013). Development of Decision Support System for Integrated Water Resources Mnagement at Basin Scale. Ph. D. dissertation, University of Tehran.
Hajkowicz, S. and Collins, K. (2007). A review of multiple criteria analysis for water resource planning and management. Water resources management, 21(9), 1553-1566.
Jamali, I. A., Mörtberg, U., Olofsson, B. and Shafique, M. (2014). A spatial multi-criteria analysis approach for locating suitable sites for construction of subsurface dams in Northern Pakistan. Water resources management, 28(14), 5157-5174.
Labadie, J. W. (2006). MODSIM: decision support system for integrated river basin management.
Li, P., Qian, H., Wu, J. and  Chen, J. (2013). Sensitivity analysis of TOPSIS method in water quality assessment: I. Sensitivity to the parameter weights. Environmental monitoring and assessment, 185(3), 2453-2461.
Mahab Ghodss Consulting Engineering Co (2009), Comprehensive Study Of Khazar Water Shed, Report No 2385070.2050.23352: 1-123. (in Farsi)
Malczewski, J. (2004). GIS-based land-use suitability analysis: a critical overview. Progress in planning, 62(1), 3-65.
Mianabadi, H. and Afshar, A. (2008). Multi attribute decision making to rank urban water supply schemes. J. of Water and Wastewater, 66, 34-45. (In Farsi)
Opricovic, S. (2011). Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications, 38(10), 12983-12990.
Opricovic, S. and Tzeng, G.H.(2003) (2011), "Defuzzification with a Multi-Criteria Decision ModelFuzzy VIKOR with an Application to Water Resources Planning", International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Volume 3811, Issue 1005, 15, Pages 12983635–65212990.
Prodanovic, P. and Simonovic, S. P. (2002). Comparison of fuzzy set ranking methods for implementation in water resources decision-making. Canadian Journal of Civil Engineering, 29(5), 692-701.
Radmehr, A. and Araghinejad, S. (2014). Developing strategies for urban flood management of Tehran city using SMCDM and ANN. Journal of Computing in Civil Engineering, 28(6), 05014006.
Rahimi, M., Ebrahimi,K. and Araghinejad, Sh., (2017), "Presenting and evaluating a proposed method in determining the most appropriate wastewater applications", Iranian Journal of Soil and Water Research, 48(5), 963-974. (In Farsi)
Raju, K. S., Duckstein, L. and Arondel, C. (2000). Multicriterion analysis for sustainable water resources planning: a case study in Spain. Water Resources Management, 14(6), 435-456.
Rousta, B. A. and Araghinejad, S. (2015). Development of a multi criteria decision making tool for a water resources decision support system. Water Resources Management, 29(15), 5713-5727.
Sánchez-Lozano, J. M. and Fernández-Martínez, M. (2016). Near-Earth object hazardous impact: A Multi-Criteria Decision Making approach. Scientific reports, 6, 37055.
Simonovic, S. P. (2002). A spatial fuzzy compromise programming for management of natural disasters. Institute for Catastrophic Loss Reduction.
Sohrabi,M.T., Liaghat, A., Alizadeh, H. and Nazari,B.,(2014), " Modeling and simulation of long-term effects of Tehran sewage application on the water and soil resources of Varamin plain using dynamic systems", Iranian Journal of Soil and Water Research, 45(3), 267-281. (In Farsi)
Srdjevic, B. and Medeiros, Y. D. P. (2008). Fuzzy AHP assessment of water management plans. Water Resources Management, 22(7), 877-894.
Srdjevic, B., Medeiros, Y. D. P. and Faria, A. S. (2004). An objective multi-criteria evaluation of water management scenarios. Water resources management, 18(1), 35-54.
Team, R. C. (2013). R: A language and environment for statistical computing.
Toosi, S. R. and Samani, J. M. (2010). Ranking water transfer projects using fuzzy methods. Proceedings of the Institution of Civil Engineers, 163(4), 189.
Wolfslehner, B., Vacik, H. and Lexer, M. J. (2005). Application of the analytic network process in multi-criteria analysis of sustainable forest management. Forest ecology and management, 207(1-2), 157-170.
Yaccob, A. A. and Shamsudin, S. (2007). Management of Melana watershed using multicriteria decision making approaches (Doctoral dissertation, Universiti Teknologi Malaysia).
Yang, J. S., Chung, E. S., Kim, S. U. and Kim, T. W. (2012). Prioritization of water management under climate change and urbanization using multi-criteria decision making methods. Hydrology and Earth System Sciences, 16(3), 801-814.
Yilmaz, B. and Harmancioglu, N. (2010). Multi-criteria decision making for water resource management: a case study of the Gediz River Basin, Turkey. Water SA, 36(5).
Zarghami, M. and Szidarovszky, F. (2010). On the relation between compromise programming and ordered weighted averaging operator. Information Sciences, 180(11), 2239-2248.
Zeleny, M. (1973). Compromise programming. Multiple criteria decision making.
Zhang, H. and Huang, G. H. (2011). Assessment of non-point source pollution using a spatial multicriteria analysis approach. Ecological Modelling, 222(2), 313-321.
Iranian Journal of Soil and Water Research
Volume 50, Issue 5
September 2019
Pages 1265-1278

Files

Share

How to cite

Statistics