Prioritization of Sezar Subbasins in Terms of Flooding Potentian Using Game Theory

Document Type : Research Article


1 MSc student, Department of Watershed Management Engineering, Faculty of Agriculture and Natural Resources, Lorestan University

2 Associate Professor, Department of Watershed Management Engineering, Faculty of Agriculture and Natural Resources, Lorestan University


Making the optimal decision to prioritize the operation in watershed management projects is to reduce the risk of flooding due to the impact of various parameters, complex and, of course, important. The game theory has a high performance in making the optimal decision to solve multi-objective problems. In this study, this method was used to prioritize on the watershed of the flood risk in the Sezar watershed. By using two Borda algorithms and bargaining in game theory, the most effective parameters in all sub-watersheds and the most critical sub-watersheds were identified. By implementing the Borda scoring method, residential parameters with 93.5, drainage density of 91 and average slope, and the shape of the sub area with a score of 90.5, and hence the implementation of the bargaining algorithm, the most effective parameters in the competition between the 12 parameters in all sub-watersheds, Moderate slope parameters, length of the main waterways and rangelands were used. According to the principles governing this method, the selection of these parameters is based on the running of all players in all fields. In fact, the three parameters mentioned above are faster in all sub-watersheds, and the number 16 is the number Subways have arrived. Finally, the Sezar watershed Prioritization Plans are presented with both methods, which are in the first place under the Borda method, under the domains I, N, G, P and O, and in the bargaining chamber, G, H, N, I and F are in the first place.


Main Subjects

[1]. Hagizhizadeh, A., Mohammadlou, M., Noori, F. Simulation of Rainfall-Runoff Process Using Artificial Neural Network and Adaptive Neural Fuzzy System and Multivariate Regression (Case Study, Khorramabad Water Basin), Journal of Ecohydrology, Volume 2, Issue 2, Summer 2013; pp. 233-243.
[2]. Amani, M., Safaviayan, A. Sub-basins prirization using morphometric analysis-remote sensing technique and GIS- Golestan-Iran. International Letters of Natural Sciences, 2015; 38(0): 56-65.
[3]. Khalighi, Sh. Madawi, M. Investigating the Effect of Land Use Change and Surface Water Hydrological Properties Case Study: Barandoz Chay Province, West Azarbaijan Province, Ph.D. Department of Natural Resources, University of Tehran, 2015; 142 p. (In Persian).
[4]. Sadeghi, S.H.R. A Semi-detailed technique for soil erosion mapping based on BLM and satellite image applications. J. Agr. Sci. Tech, 2005; 7 (3, 4), 133–142.
[5]. Alvani, M. Public Administration, Tehran University Press. 2005; 19th edition, 120 pages. (In Persian).
[6]. Golparvar, M., Shahabi, M. The Application of Game Theory in Explaining Electoral Competitions, Quarterly Journal of Political and International Studies of Islamic Azad University, Shahreza Branch, No. 6, 2011; 175-202. (In Persian).
[7]. Pawattana, C., Tripathi, N. K., & Howe, S.L. Development of Potential Floodwater Retention Zones using AHP and GIS: A Case Study in the Chi River Basin, Thailand. International Journal of Geo-informatics, 2011; 5(4): 17-25.
[8]. Saini, S.S and Kaushik. S.P. Risk and vulnerability assessment of flood hazard in part of Ghaggar Basin: A case study of Guhla block, Kaithal, Haryana, India. International Journal of Geomatics and Geosciences, 2012; 3(1): 42-54.
[9]. Amiri, M., Pourghasemi, H.R., Arabic Ameri, A.R. Prioritizing the flooding of Maharlo watershed basins in Fars province using morphometric parameters and decision making VIKOR, Journal of ecohydrology, Volume 5, Issue 3, Summer 2018; p. 813-827.
[10].            Mohammadi, P., Malekian, A. Prioritization of watersheds in terms of flood risk based on multivariate decision making models, Journal of Ecohydrology, Volume 4, Issue 2, Summer 2013, pp. 499-508.
[11].            Aher, P.D., Adinarayana, J. & Gorantiwar, S.D. Quantification of morphometric characterization and prioritization for management planning in of India. A remote sensing and GIS approach. Journal of Hydrology, 2014; 51(1): 850-860.
[12].            Soleimani, K., Bashir Gonbad, M., Mousavi, S., Khaliqi, Sh. Flood potential in watersheds using HEC-HMS model in GIS environment (case study of Kasaliyan Basin) , Natural History Research, 65, Autumn, 2008; 51-60. )In Persian).
[13].            Zehtabiyan, Gh., Ghoddusi, J., Ahmadi, H., Khalilizadeh, M., Moghali, M. Assessment of the Flood Potential Ranking of Sub-basins and Determination of Flood Source Areas, Journal of Environmental Hydrology, 2010; 18(24): 1-9.
[14].            Bahrami, S., A., Onagh, M., Farazjoo, H. River Rendering Role in Identifying and Prioritizing Hydrological Units in Boustan Dam Basin for Flood Management and Providing Management Solutions, Journal of Soil and Water Resources Conservation, 1 (1), autumn, 2011; 11-26.)In Persian).
[15].            Nikoo, M.R., BahmanBeiglou, P.H. & Mahjouri, N. "Optimizing multiple-pollutant waste load allocation in rivers: an interval parameter game theoretic model", Water Resources Management, 2016; 30(12), 4201-4220.
[16].            Adhami, M. & Sadeghi, S.H.R. Sub-watershed prioritization based on sediment yield using game theory. Journal of Hydrology, 2016; 541: 977–987.
[17].            Abdoli, Gh., Game Theory and Applications in Static and Dynamic Shifts, Jahad University Press, Tehran, 2008; Second Edition. (In Persian).
[18].            Mac Milan, j. Games, Strategies & Managers: How Managers Can Use Game Theory to Make Better Business Decision, Oxford University Press, 1996; United States of America, p 246.
[19].            Suresh, M. S, Sudhakar. K.N, Tiwari. V.M, Chawdary. Prioritization of watershed using morphometric parameters ond assement of surface water potential using RS. Jornal of indian society of Remote Sensing, 2004; 32 (3): 249-259.
[20].            Skardi, M.J.E., Afshar, A. and Solis, S.S. Simulation-Optimization Model for Non- Point Source Pollution Management in Watersheds: Application of Cooperative Game Theory, KSCE. Journal of Civil Engineering,2013; 17(6): 1232-1240.
[21].            Pacuit, E. Voting Methods. In: Zalta, E.N. (ed) the Stanford Encyclopedia of Philosophy, Winter 2012 edn.
[22].            Balinski, M., Laraki, R. A theory of measuring, electing and ranking. National Academy of Sciences, 2007; 104 (21): 8720-8725.
[23].            Brams, S.J., Kilgour, D.M. Fallback bargaining. Group. Decis. Negot, 2001; 10(4): 287-316.
[24].            Baharad, E., Nitzan, S. The Borda rule, The Condorcet consistency and Condorcet stability. Econ. Theor, 2003; 22 (3), 685–688.Bolstad, P. V, and Lillesand, T. M. 1991. Rapid maximum likelihood classification. Photogramm. Eng. Remote Sens. 57.
Volume 5, Issue 4
January 2019
Pages 1219-1231
  • Receive Date: 22 May 2018
  • Revise Date: 17 September 2018
  • Accept Date: 16 September 2018
  • First Publish Date: 22 December 2018
  • Publish Date: 22 December 2018