Membrane and Water Treatment

  • 제9권6호
  • /
  • Pages.421-434
  • /
  • 2018
  • /
  • 2005-8624(pISSN)
  • /
  • 2092-7037(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Modeling of decision-makers negotiations in reservoir operation with respect to water quality and environmental issues

  • Mojarabi-Kermani, A.R. (Department Water Science and Engineering, Khuzestan Science and research Branch, Islamic Azad University) ;
  • Shirangi, Ehsan (Department of Civil Engineering, Karaj Branch, Islamic Azad University) ;
  • Bordbar, Amin (Department Water Science and Engineering, Ahvaz Branch, Islamic Azad University) ;
  • Bedast, A.A. Kaman (Department Water Science and Engineering, Ahvaz Branch, Islamic Azad University) ;
  • Masjedi, A.R. (Department Water Science and Engineering, Ahvaz Branch, Islamic Azad University)
  • 투고 : 2018.05.17
  • 심사 : 2018.07.21
  • 발행 : 2018.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

Decision-makers have different and sometimes conflicting goals with utilities in operating dam reservoirs. As repeated interactions exist between decision-makers in the long-term, and the utility of each decision-making organization is affected not only by its selected strategy, but also by other rivals' strategies; selecting and prioritizing optimum strategies from a decision maker's point of view are of great importance while interacting with others. In this paper, a model based on a fuzzy set theory, for determining the priority of decision-makers' strategies in optimal qualitative-quantitative operation management of dam reservoir is presented. The fuzzy priority matrix is developed via defining membership functions of a fuzzy set for each decision maker's strategies, so that all uncertainties are taken into account. This matrix includes priorities assigned to possible combination for other decision makers' strategies in bargaining with each player's viewpoint. Here, the 15-Khordad Dam located in the central part of Iran, suffering from low water quality, was studied in order to evaluate the effectiveness of the model. Then, the range of quality of water withdrawal agreed by all decision-makers was determined using the prioritization matrix based on fuzzy logic. The results showed that the model proposed in the study had high effectiveness model.

키워드

참고문헌

  1. Abed-Elmdoust, A., and Kerachian, R. (2012), "Water resources allocation using a cooperative game with fuzzy payoffs and fuzzy coalitions", Water Resour. Manag., 26(13), 3961-3976. https://doi.org/10.1007/s11269-012-0115-0
  2. Adhami, M., Sadeghi, S.H.R. and Sheikhmohammady, M. (2018), "Making competent land use policy using a co-management framework", Land Use Policy., 72, 171-180. https://doi.org/10.1016/j.landusepol.2017.12.035
  3. Alizadeh, M.R., Nikoo, M.R. and Rakhshandehroo, G.R. (2017), "Developing a multi-objective conflict-resolution model for optimal groundwater management based on fallback bargaining models and social choice rules: A case study", Water Resour. Manag., 31(5), 1457-1472. https://doi.org/10.1007/s11269-017-1588-7
  4. Dehghan Manshadi, H.R., Niksokhan, M.H. and Ardestani, M. (2015), "Quantity-quality model for inter-basin water transfer system using game theoretic and virtual water approaches", Water Resour Manag., 29(13), 4573-4588. https://doi.org/10.1007/s11269-015-1076-x
  5. Ganji, A., Khalili, D. and Karamouz, M. (2006), "Development of stochastic dynamic Nash game model for reservoir operation. I: The symmetric stochastic model with perfect information", Adv. Water Resour., 30(3), 528-542. https://doi.org/10.1016/j.advwatres.2006.04.004
  6. Ganji, A., Khalili, D. and Karamouz, M. (2007), "Development of stochastic dynamic Nash game model for reservoir operation. II: The value of players' information availability and cooperative behaviors", Adv. Water Resour., 30(1), 157-168. https://doi.org/10.1016/j.advwatres.2006.03.008
  7. Garagic, D. and Cruz, J. (2003), "An approach to fuzzy noncooperative Nash games", J. Optim. Theory Appl., 118(3), 475-491. https://doi.org/10.1023/B:JOTA.0000004867.66302.16
  8. Haan, T.Y., Shah, M., Chun, H.K. and Mohammad, A.V. (2018), "A study on membrane technology for surface water treatment: Synthesis, characterization and performance test", Membr. Water Treat., 9(2), 69-77. https://doi.org/10.12989/MWT.2018.9.2.069
  9. Jiang, S.K., Zhang, G.M., Yan, L. and Wu, Y. (2018), "Treatment of natural rubber wastewater by membrane technologies for water reuse", Membr. Water Treat., 9(1), 17-21. https://doi.org/10.12989/MWT.2018.9.1.017
  10. Jokic, A.I., Seres, L.L., Milovic, N.R., Seres, Z.I., Maravic, N.R., Saranovic, Z. and Dokic, L.P. (2018), "Modelling of starch industry wastewater microfiltration parameters by neural network", Membr. Water Treat., 6(1), 77-94. https://doi.org/10.12989/mwt.2015.6.1.077
  11. Karimi, A., Nikoo, M.R., Kerachian, R. and Shirangi, E. (2011), "Assessment of water transport projects impact on long term water supply in Zayandehrood basin by multi-period optimization analysis", Iran. Water Res. J., 6(11), 153-163.
  12. Kerachian, R. and Karamouz, M. (2006), "Optimal reservoir operation considering the water quality issues: a stochastic conflict resolution approach", Water Resour. Res., 42(12), 1-15.
  13. Kerachian, R. and Karamouz, M. (2007), "A stochastic conflict resolution model for water quality management in reservoirriver systems", Adv. Water Res., 30(4), 866-882. https://doi.org/10.1016/j.advwatres.2006.07.005
  14. Kerachian, R. and Shirangi, E. (2008), "A case study for conflict resolution in reservoir operation for water quantity and quality", World Water and Environmental Resources Congress, Hawaii, May.
  15. Lee, C.S., Nam, Y.W. and Ki, D.I. (2017), "Economical selection of optimum pressurized hollow fiber membrane modules in water purification system using RbLCC", Membr. Water Treat., 8(2), 137-147. https://doi.org/10.12989/mwt.2017.8.2.137
  16. Lee, J., Cha, H.Y., Min, K.J., Cho, J. and Park, K.Y. (2018), "Electrochemical nitrate reduction using a cell divided by ionexchange membrane", Membr. Water Treat., 9(3), 189-194. https://doi.org/10.12989/MWT.2018.9.3.189
  17. Li, B., Tan, G. and Chen, G. (2016), "Generalized uncooperative planar game theory model for water distribution in transboundary rivers", Water Resour. Manag., 30(1), 225-241. https://doi.org/10.1007/s11269-015-1158-9
  18. Luo, G., Li, W., Tan, H. and Chen, X. (2017), "Comparing salinities of 0, 10 and 20 in biofloc genetically improved farmed tilapia (Oreochromis niloticus) production systems", Aquacult. Fisher., 2(5), 220-226. https://doi.org/10.1016/j.aaf.2017.10.002
  19. Madani, K. (2010), "Game theory and water resources", J. Hydrology., 381(3-4), 225-238. https://doi.org/10.1016/j.jhydrol.2009.11.045
  20. Madani, K. and Hipel, K. (2011), "Non-cooperative stability definitions for strategic analysis of generic water resources conflicts", Water Resour. Manag., 25(8), 1949-1977. https://doi.org/10.1007/s11269-011-9783-4
  21. Madani, K. and Hooshyar, M. (2014), "A game theory reinforcement learning (GT-RL) method to develop optimal operation policies for multi-reservoir multi-operator systems", J. Hydrology., 519, 732-742. https://doi.org/10.1016/j.jhydrol.2014.07.061
  22. Mahjouri, N. and Ardestani, M. (2011), "Application of cooperative and non-cooperative games in large-scale water quantity and quality management: A case study", Environ. Monit. Assess., 172(1-4), 157-169. https://doi.org/10.1007/s10661-010-1324-8
  23. Poorsepahy-Samian, H., Kerachian, R. and Nikoo, M.R. (2012), "Water and pollution discharge permit allocation to agricultural zones: Application of game theory and min-max regret analysis", Water Resour. Manag., 26(14), 4241-4257. https://doi.org/10.1007/s11269-012-0142-x
  24. Rashidi, B. Shirangi, E. and Baymaninezhad, M. (2018), "Multiple criteria decision making method for selecting of sealing element for earth dams considering long and short terms goals", Wind Struct., 26(2), 69-74. https://doi.org/10.12989/WAS.2018.26.2.069
  25. Rojas-Serrano, F., Alvarez-Arroyo, R., Perez, J.I., Plaza, F., Garralon, G. and Gomez, M.A. (2015), "Ultrafiltration membranes for drinking-water production from low-quality surface water: A case study in Spain", Membr. Water Treat., 6(1), 77-94. https://doi.org/10.12989/mwt.2015.6.1.077
  26. Sadegh, M., Mahjouri, N. and Kerachian, R. (2010), "Optimal inter-basin water allocation using crisp and fuzzy shapley games", Water Resour. Manag., 24(10), 2291-2310. https://doi.org/10.1007/s11269-009-9552-9
  27. Sadegh, M. and Kerachian, R. (2011), "Water resources allocation using solution concepts of fuzzy cooperative games: fuzzy least core and fuzzy weak least core", Water Resour. Manag., 25(10), 2543-2573. https://doi.org/10.1007/s11269-011-9826-x
  28. Sanada, K. (2018), "Real-time implementation of Kalman filter for unsteady flow measurement in a pipe", J. Hydromechatronics., 1(1), 3-15. https://doi.org/10.1504/IJHM.2018.090303
  29. Sechi, G.M., Zucca, R. and Zuddas, P. (2013), "Water costs allocation in complex systems using a cooperative game theory approach", Water Resour. Manag., 27(6), 1781-1796. https://doi.org/10.1007/s11269-012-0171-5
  30. Shirang, E. and Kerachian, R. (2007), "A simplified model for optimal reservoir operation considering the water quality issues", Proceedings of CEMEPS/SECOTOX Conference, Skiathos island, Greece, June.
  31. Shirangi, E., Kerachian, R. and Shafai Bajestan, M. (2008), "A simplified model for optimal reservoir operation considering the water quality issues: Application of the Young conflict resolution theory", Environ. Monit. Assess., 146(1-3), 77-89. https://doi.org/10.1007/s10661-007-0061-0
  32. Shirangi, E., khaleghi, S., Baghaei, F., Mansoori, A. and Pourmand, E. (2016), "Developing real time optimal reservoir operation rules using Bayesian networks: Application of group conflict resolution model", J. Water Soil Resour. Conserv., 5(3), 1-11.
  33. Singh, A., Panda, S., Saxena, C., Verma, C., Uzokwe, V., Krause, P. and Gupta, S. (2016), "Optimization modeling for conjunctive use planning of surface water and groundwater for irrigation" J. Irrig. Drain. Eng., 142(3), 1-9.
  34. Soltani, M.A., Karimi, A., Bazargan-lari, M.R. and Shirangi, E. (2008), "Stochastic multi-purpose reservoir operation planning by scenario optimization and differential evolutionary algorithm", J. Appl. Sci., 8(22), 4186-4191. https://doi.org/10.3923/jas.2008.4186.4191
  35. Soltani, F., Kerachian, R. and Shirangi, E. (2010), "Developing operating rules for reservoirs considering the water quality issues: Application of ANFIS-based surrogate models", Expert Syst. Appl., 37(9), 6639-6645. https://doi.org/10.1016/j.eswa.2010.03.057
  36. Stelson, K. (2018), "Academic fluid power research in the USA", J. Hydromechatronics, 1(1), 126-152.
  37. Teegavarapu, R.S., Ferreira, A.R. and Simonovic, S.P. (2013), "Fuzzy multiobjective models for optimal operation of a hydropower system", Water Resour. Res., 49(6), 3180-3193. https://doi.org/10.1002/wrcr.20224
  38. Wang, Z., Xie, Z. and Huang, W. (2018), "A pin-moment model of flexoelectric actuators", J. Hydromechatronics, 1(1), 72-90. https://doi.org/10.1504/IJHM.2018.090306
  39. Wu, H., Chen, C., Wang, Q., Lin, J. and Xue, J. (2017), "The biological content of ballast water in China: A review", Aquacult. Fisher., 2(6), 241-246. https://doi.org/10.1016/j.aaf.2017.03.002
  40. Yang, G., Song, L., Lu, Q., Wang, N. and Li, Y. (2017), "Effect of the exposure to suspended solids on the enzymatic activity in the bivalve Sinonovacula", Aquacult. Fisher., 2(1), 10-17. https://doi.org/10.1016/j.aaf.2017.01.001
  41. Yang, Z., Liu, P., Cheng, L., Wang, H., Ming, B. and Gong., W. (2018), "Deriving operating rules for a large-scale hydrophotovoltaic power system using implicit stochastic optimization", J. Cleaner Product., 195, 562-572. https://doi.org/10.1016/j.jclepro.2018.05.154