A simplified model for reservoir operation considering the water quality issues: Application of the Young conflict resolution theory

Environmental Monitoring and Assessment

Volumn 146, Issue 1-3, 2008, Pages 77-89

  Shirangi, Ehsan ^a   Kerachian, Reza ^b   Bajestan, Mahmood Shafai ^c  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b UNIVERSITY OF TEHRAN   (Iran)

^c SHAHID CHAMRAN UNIVERSITY OF AHVAZ   (Iran)

Author keywords

Conflict resolution; Genetic algorithms; Reservoir operation; The Young theory; Water quality

Indexed keywords

BOOLEAN FUNCTIONS; COMMERCE; CURVE FITTING; DATA STORAGE EQUIPMENT; DECISION THEORY; FUZZY INFERENCE; FUZZY SYSTEMS; GENETIC ALGORITHMS; OPTIMIZATION; RELIABILITY; RESERVOIRS (WATER); RUNOFF; STOCHASTIC MODELS; STORAGE (MATERIALS); TIME SERIES ANALYSIS; WATER CONSERVATION; WATER QUALITY; WATER SUPPLY; WATER SUPPLY SYSTEMS;

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; BEST SOLUTION; COMPUTATIONAL BURDEN; CONFLICT RESOLUTION; CONFLICT RESOLUTIONS; DECISION-MAKERS; MULTI-OBJECTIVE GENETIC ALGORITHM; OBJECTIVE FUNCTION; OBJECTIVE FUNCTIONS; OPERATING POLICIES; OPTIMIZATION MODELING; RESERVOIR OPERATING RULES; RESERVOIR OPERATION; RESERVOIR OPERATIONS; RESERVOIR STORAGE; RESERVOIR WATER; RUN-TIME; SIMPLIFIED MODELS; SIMPLIFIED PROCEDURE; STOCHASTIC OPTIMIZATION MODEL; THE YOUNG THEORY; TIME-SERIES; WATER QUALITY ISSUES; WATER QUALITY SIMULATION; WATER QUANTITIES; WATER STORAGES; WATER YEAR;

HYDRAULIC MODELS;

DECOMPOSITION ANALYSIS; GENETIC ALGORITHM; NUMERICAL MODEL; OPTIMIZATION; RESERVOIR; STOCHASTICITY; TRADE-OFF; WATER QUALITY; WATER STORAGE; WATER SUPPLY;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; DECISION MAKING; FUZZY SYSTEM; GENETIC ALGORITHM; IRAN; PROCESS OPTIMIZATION; RELIABILITY; SIMULATION; STOCHASTIC MODEL; WATER QUALITY; WATER SUPPLY;

ALGORITHMS; FUZZY LOGIC; MODELS, STATISTICAL; WASTE DISPOSAL, FLUID; WATER SUPPLY;

EID: 53649094322     PISSN: 01676369     EISSN: 15732959     Source Type: Journal    
DOI: 10.1007/s10661-007-0061-0     Document Type: Article

References (22)

1. Abrishamchi, A., Afshar, A., & Kerachian, R. (2003). Spillway capacity optimization under hydrologic uncertainties. Iranian Journal of Science and Technology, 27 (B1), 111-122.
2. Chaves, P., & Kojiri, T. (2007). Deriving reservoir operational strategies considering water quantity and quality objectives by stochastic fuzzy neural networks. Advances in Water Resources, 30 (5), 1329-1341.
3. Chaves, P., Tsukatani, T., & Kojiri, T. (2004). Operation of storage reservoir for water quality by using optimization and artificial intelligence techniques. Mathematics and Computers in Simulations, 67, 419-432.
4. Dandy, G., & Crawley, P. (1992). Optimum operation of a multiple reservoir system including salinity effects. Water Resources Research, 28 (4), 979-990.
5. Fontane, D., Labadie, J. W., & Loftis, B. (1981). Optimal control of reservoir discharge quality through selective withdrawal. Water Resources Research, 17 (6), 1594-1604.
6. Ganji, A., Khalili, D., & Karamouz, M. (2007). Development of stochastic dynamic nash game model for reservoir operation. I: The symmetric stochastic model with perfect information. Advances in Water Resources, 30, 528-542.
7. Ganji, A., Khalili, D., & Karamouz, M. (2006). Development of stochastic dynamic nash game model for reservoir operation. II: The value of players' information availability and cooperative behaviors. Advances in Water Resources, 30, 157-168.
8. Hayes, D. F., Labadie, J. W., Sanders, T. G., & Brown, J. K. (1998). Enhancing water quality in hydropower system operation. Water Resources Research, 34 (3), 471-483.
9. Kaplan E. (1974). Reservoir optimization for water quality control, Ph.D. dissertation, Univ. of Pennsylvania, Philadelphia.
10. Karamouz, M., Zahraie, B., & Kerachian, R. (2003). Development of a master plan for water pollution control using MCDM techniques: A case study. Water International, IWRA, 28 (4), 478-490.
11. Kerachian, R., & Karamouz, M. (2005). Waste-load allocation model for seasonal river water quality management: Application of sequential dynamic genetic algorithms. Scientia Iranica, 12 (2), 117-130.
12. Kerachian, R. (2004). Water quality management in river-reservoir systems, Ph.D. dissertation, Department of Civil and Environmental Engineering, Amirkabir University (Tehran Polytechnic), Teheran, Iran.
13. Kerachian, R., & Karamouz, M. (2006). Optimal reservoir operation considering the water quality issues: A stochastic conflict resolution approach. Water Resources Research. AGU, W 12401, DOI 10.1029/ 2005WR004575, 42, 1-17.
14. Kerachian, R., & Karamouz, M. (2007). A stochastic conflict resolution model for water quality management in reservoir-river systems. Advances in Water Resources. DOI 10.1016/ j.advwaters.2006.07.005, 30, 866-882.
15. Loaiciga, H. A. (2004). Analytic game-theoretic approach to groundwater extraction. Journal of Hydrology, 297 (1-4), 22-33.
16. Loftis, B., Labadie, J. W., & Fontane, D. (1985). Optimal operation of a system of lakes for quality and quantity, Proceedings of Specially Conference on Computer Applications in Water Resources, Buffalo, N.Y.
17. Nandalal, K. D. W., & Bogardi, J. J. (1995). Reservoir management for improving river water quality. Proc. of Water Resources Management Under Drought or Water Storage Conditions, Rotterdam, 257-264.
18. Napel, S. (2002). Bilateral bargaining: Theory and applications. Berlin: Springer-Verlag.
19. Richards, A., & Singh, N. (1996). Two level negotiations in Bargaining over water, Proceedings of the International Game Theory Conference, Bangalore, India, 1-23.
20. Shirangi, E., & Kerachian, R. (2007). A simplified model for optimal reservoir operation considering the water quality issues, Proceedings of CEMEPE/SECOTOX Conference, June 24-28, Skiathos island, Greece.
21. U.S. Army Corps of Engineers (USACE) (1986). HEC-5, simulation of flood control and conservation systems, appendix on water quality analysis, report, Hydrol. Eng. Cent., Davis, Calif.
22. Young, H. P. (1993). An evolutionary model of bargaining. Journal of Economic Theory, 59, 145-168.