Journal of Water and Soil Vol. 26, No.5, Nov.-Dec. 2012, p BP14 BP Rotational Delivery 4- On- Demand Delivery 5- Arranged Delivery

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2 Journal of Water and Soil Vol. 26, No.5, Nov.-Dec. 2012, p. 1109-1118 ( ) 1109-1118. 1391 5 26 BP14 2 *1-1390/6/13 : 1391/5/10 :... BP14. 2100 2/5 6852... 10 90. 0/04. 41 105 :.. 4 3 5..... 3- Rotational Delivery 4- On- Demand Delivery 5- Arranged Delivery 21..(9)... () -2 1 (Email : emadia355@yahoo.com : -*)

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1117.......1381. -2....1385. -3......1386.... -4.(1) 3 :11-1. PSO.1389... -5.(1) 4 :73-82 6- Abbaspour K. C., Schulin R., and Van Genuchten M. T. 2001. Estimating Unsaturated soil hydraulic parameters using ant colony optimization. Advance Water Resources, 24(8): 827-841. 7- Afshar M. H., Ketabchi H., and Rasa E. 2006. Elitist Continuous Ant colony Optimization Algorithm: Application to Reservoir operation Problems. International Journal of Civil Engineering, 4(4): 274-285. 8- Afshar M. H. 2010. A parameter free Continuous Ant Colony Optimization Algorithm for the optimal design of storm sewer networks: Constrained and unconstrained approach. Advances in Engineering Software, 41:188-195. 9- Chamber R. 1988. Managing Canal Irrigation: Practical Analysis from south Asia, Cambridge University Press. 10- Dorigo M. 1991. Ant colony Optimization, New Optimization Techniques in Engineering. by onwubolu, G. C., and B. V. Babu, Springer- Verlag Berlin Heidel berg, 101-116. 11- Dorigo M., and Gambardella L. M. 1997. Ant colony System: A cooperative Learning approach to the traveling saleman problem. IEEE Transaction on Evolutionary Computation, 1(1):53-66. 12- Jalali M. R., Afshar A. and Marino M. A. 2006. Reservoir operation by ant colony optimization algorithms. Iranian Journal of Science and Technology, (IJST), 1(30): 107-117. 13- Maier H.R., Simpson A.R., Zecchin A. C., Foong W. K., Phang K. Y., Seah H. y., and Tan C. l. 2003. Ant colony optimization for design of water distribution system. Journal of Water Resources Planning and Management., ASCE, 129(3): 200-209. 14- Mathur Y. P., Sharma G., and Pawde A. W. 2009. Optimal operation scheduling of Irrigation canals using Genetic Algorithm. International Journal of Recent Trends in Engineering, 1(6): 11-15. 15- Monem M. J. and Namdarian R. 2005. Application of Simulated Annealing (SA) Techniques of optimal water Distribution in Irrigtion canals. Journal of Irrigation and Drainage, 54(1): 365-373. 16 - Nagesh Kumar D. and Janga Reddy M. 2005. Ant colony Optimization for Multi- purpose Reservoir operation. Water Resources Management, 20: 879-898. 17- Reddy J. M., Wilamowski B., and Sharmasarkar F.C. 1999. Optimal Scheduling Irrigation for lateral canals. ICID Journal, 48(3): 1-12. 18- Shouja Li. Yingxi Liu. and HeYu. 2006. Parameter Estimation Approach in Groundwater Hydrology using Hybrid Ant colony system. Irwin (Eds): ICIC 2006, LNBI 4115, 182-191. 19- Simpson A.R., Maier H.R., Foong W. K., phang K. Y., Seah H. Y., and Tan C. L. 2001. Selection of parameters for ant colony optimization applied to the optimal design of water distribution system. Proc., Int. Congress on Modeling and Simulation, Canberra, Australia, 1931-1936. 20- Suryavanshi A. R. and Reddy J. M. 1986. Optimal Operation Scheduling of irrigation distribution system. Agricultural Water Management, 11: 23-30. 21- Wang Z. R., Mohan J. and Feyan J. 1995. Improved 0-1 Programing model for optimal flow Scheduling in irrigation canals. Journal of Irrigation and Drainage system, 9: 105-116. 22- Zecchin A. C., Maier H. R., Simpson A. R., Roberts A., Berrisford M. J., and Leonard M. 2003. Max- Min ant system applied to water distribution system optimization. Modsim 2003- International Congress on Modeling and Simulation, Modeling and Simulation Society of Australia, 795-800.

Journal of Water and Soil Vol. 26, No.5, Nov.-Dec. 2012, p. 1109-1118 1391 - ( ) 1118 5 1109-1118 26. 1391 5 26 Water Delivery Optimization in BP14 Canal of Fumanat Irrigation Network Using Ants Colony System Algorithm A. Emadi 1 * - S. Kakouie 2 Received: 04-09-2011 Accepted: 31-07-2012 Abstract Poor delivery and distribution water in irrigation canals will cause the discontent of farmers, disrespect of equity in water delivery and increase operational losses. Therefore optimal water delivery scheduling will increase performance condition network, considerably. With the spread of computers and mathematical methods, it is possible that develop simulation and optimization mathematical models for optimal operation. In this study, Ants Colony System (ACS) optimization algorithm is used for development optimal water delivery in BP14 canal of Fumanat irrigation network in west of Gilan province. This canal has a length of 6852 meters with a trapezoidal cross section and capacity of 2.5 m 3 /s and land cover area of 2100 ha. The optimal delivery schedule canal is derived for two cases; single objective, canal capacity minimization and two objective including minimize canal capacity and delivery time. Comparison of the research with results obtained from Genetic Algorithm (GA) showed that ACS algorithm to GA in single objective state resulted in less canal capacity (90 l/s) and more irrigation schedule complement duration (10 hours). Also, the number of upstream gate regulations and water delivery deficiency obtained 1 and 0.04 percent, respectively. In two objective state, ACS determined less canal capacity (105 l/s) and more irrigation schedule complement duration (41 hours). Keywords: Water delivery, Optimal Scheduling, Irrigation network, Performance network 1,2- Assistant Professor and MSc Student, Deportment of Water Engineering, Sari Agricultural Sciences and Natural Resources University (*-Corresponding Author Email: emadia355@yahoo.com)