Optimization of Water Delivery Schedule in Reduced Allocation Scenarios of Zarinehroud Irrigation Network Using PSO Algorithm

Document Type : Research Paper


1 Ph.D. Graduate of Irrigation and Drainage, Department of Water Engineering, Urmia University, Urmia, Iran.

2 Associate Professor, Department of Irrigation and Reclamation Engineering, College of Agricultural Engineering and Technology, University of Tehran, Tehran, Iran.

3 Professor, Department of Hydraulic Structures, Tarbiat Modares University, Tehran, Iran.


Optimization of operational performance in irrigation networks is essential for increasing water consumption efficiency in Urmia Lake Basin and its restoration. Various optimization algorithms have been developed. In this research, PSO algorithm with the ability of swarm intelligence and convergence speed was used to optimize the water delivery schedule of Zarinehroud left bank Irrigation Network in two reduced water allocation scenarios. The first scenario follows the Urmia Lake Restoration Plan (ULRP) based on the reduction of agricultural water consumption by 40%; and the second scenario focuses on the delivery of 70% to 90% of network water demand. Suitable values of model parameters have been determined by sensitivity analysis, and used in the modeling of two scenarios. Results of the first scenario indicated that, with supplement of 66% of water demand, the feasibility of 9% increase in water efficiency, 30% and 38% increase in the stability and adequacy indices can be achieved, respectively. In the second scenario, with 82% supply of water demand; the efficiency, stability and adequacy indices could be increased by 25%, 32% and 42%, respectively. The second scenario is recommended due to the gradually reduction of water allocation and greater values of the performance indices, while preserving the dependability and trust of water-users in the Zarinehroud irrigation network.


Azadnia, A and Zahraie, B. (2010). Using PSO algorithm for optimization of multi-objective dam reservoirs operation. 5th national congress of civil engineering, Ferdosi University of Mashhad, Iran. (In Farsi). 
Azarafza H., Rezaei H. Behmanesh, J. and Besharat, S. (2012) Results Comparison of Employing PSO,    GA and SA Algorithms in Optimizing Reservoir Operation (Case Study: Shaharchai Dam, Urmia, Iran). Journal of Water and Soil 26(5) 1101-1108. (In Farsi).
Baltar, A. and Fontane, D. G. (2004). A multiobjective particle swarm optimization model for reservoir operations and planning. Dept. of Civil and Environmental Engineering, Colorado State University, USA.
Dolatshahi-Zand, A. and Damghani, K. (2015). Design of SCADA water resource management control center by a bi-objective redundancy allocation problem and particle swarm optimization. Reliability Engineering and System Safety 133, (2015), 11-21.
Ghaderi, k. and Goruhi, f. (2016). Performance assessment of PSO and ICA algorithms in optimization of irrigation canals water delivery schedule (case study: Ordibehesht canal of Dorudzan network). 15th Hydraulic Conference, Ghazvin (In Farsi). 
Hosseini, M. Mazandarani zadeh, H and Nazari, B. (2020). Simultaneously Management of Surface and Groundwater Resources and Increasing Farmers' Resilience to Water Scarcity by Predicting the Price of Agricultural Products (Case Study of Irrigation and Drainage Network of Qazvin Plain). Journal of Iran soil and Water researches. doi:10.22059/ijswr.2021.313809.668805.
Kashkoul, B. (2009).Simultaneous layout and pipe size optimization of pressurized irrigation networks using Meta heuristic techniques. M.SC Thesis in Water Structures Engineering, Tarbiat Modares University. (In Farsi).
Kennedy, J. and Eberhart, R. (1995). Particle Swarm Optimization. Proceedings of the IEEE International Conference on Neural Networks, Perth, Australia 1995, pp. 1942-1948.
Khodadadi S, Yasi M and Monem M J (2017). Performance Evaluation and Optimization of Water Delivery Schedule in the Zarinehroud Irrigation Network. Journal of Water and Irrigation management. No. 1(7), 105-119 (In Farsi).
Khodaverdi, M. Hashemi, R. Khashei, A and Pourreza, M. (2019). Optimal Design of Groundwater-Quality Sampling Networks with MOPSO-GS (Case Study: Neyshabour Plain). Journal of Water and Irrigation management. No. 9(2), 199-210 (In Farsi).
Khoshnavaz S. (2019). Uncertainty Analysis of Water Distribution Planning in Mian-Ab Irrigation Network in Shooshtar
Plain: Application of Genetic Algorithm and Simulated Annealing. Journal of Iran soil and Water researches. No.51(1), 151-164 (In Farsi).
Mehdipur, A. F. and Haddad, A. B. (2012). Optimization of operation from multi-purpose dams reservoir using particle swarm algorithm. Journal of Water and Wastewater. No.4, 97-105 (In Farsi).
Meraji, H., Afshar, M. H. and Afshar, A. (2008). Optimal design of flood control systems using Particle Swarm Optimization algorithm. Journal of Civil Engineering, Iran University of Science & Technology 19(8), 41-53. (In Farsi).
Moghadam, A., Alizadeh, A., Ziaie, A. N. Hoseini, A. F and Fallah, D. (2014). Effect of PSO algorithm parameters in optimal design of water distribution networks. 8th national congress of civil engineering. Babol University. (In Farsi).
Moghaddasi, M., Morid, S. and Araghinejad, Sh. (2008). Optimization of water allocation in deficit condition using non-linear, PSO and GA algorithms (case study). Journal of Iran Water Resource Research, 3(4), 1-13. (In Farsi).
Molden, D. J. and Gates, T. K. (1990). Performance Measures for Evaluation of Irrigation-Water Delivery System. Journal of Irrigation and Drainage Engineering, Journal of American Society of Civil Engineering. 116( 6), 804- 822.
Monem, M. J. and Nouri, M. A. (2010). Using PSO algorithm in optimization of water delivery schedule in irrigation networks. Journal of Iran Irrigation and drainage. 1(4), 73-82. (In Farsi).
Montalvo, A., Joaquín Izquierdo, A., Silvia Schwarze, B. and Pérez-García, R. (2010). Multi-objective particle swarm optimization applied to water distribution systems design: An approach with human interaction. Journal of Mathematical and Computer Modelling, 52. 1219–1227.
Murray-Rust, D. H., Lashari, B. and Memon, Y. (2000). Extended Project on Farmer Managed Irrigated Agriculture under the National Drainage Program (NDP): Water Distribution Equity in Sindh Province, Pakistan. International Water Management Institute (IWMI), (Vol. 9).
Perez, R. E. and Behdinan, K. (2007). Particle swarm approach for structural design optimization. Journal of Computers and Structures, 85.1579–1588.
Rajabpur R. and Afshar M. H. (2008). Optimized Operation of serial pump stations using the PSO algorithm. Journal of Water and Wastewater. No.36, 56-66. (In Farsi).
Rezaie, F., Safavi, H. R., Mirchi, A. and Madani, K. (2017). F-MOPSO: An alternative multi-objective PSO algorithm for conjunctive water use management. Hydro-environment Research 14, 1–18.
Rezaie, H. MirAbbasi, R and Khani, Z. (2020). Two-Variable analysis of drought risk in west and north-west of Iran using PSO algorithm and
Roozbahani, R., Schreider, S. and Abbasi, B (2015). Optimal water allocation through a multi-objective compromise between environmental, social and economic preferences. Journal of Environmental Modelling & Software 64, 18-30.
Sargazi, A and Gavidel, M. (2017). Planning and Optimal Allocation of Water Resources in the Agricultural Sector (Case study of Someh Sara City). Journal of Iran-Water Resources Research 13(2), 74-81. Summer 2017 (IR-WRR) (In Farsi).
Shi, Y. and Eberhart, R. C. (1999). Empirical study of particle swarm optimization.” Proc. IEEE, International Congress Evolutionary Computation, Washington, D.C., USA, 1945 -1950.
Zoltay, V. I., Vogel, R. M., Kirshen, P. H., Westphal, K. S. (2010). Integrated watershed management modeling: generic optimization model applied to the Ipswich River Basin. Journal of Water Resour. Plan. Manag. 136 (5), 566-575.