The Optimization of Irrigation Networks Using Genetic Algorithms


Mathematical-computational optimisation models of irrigation networks with a distributed flow that are capable of providing hydraulic data are important for understanding the behaviour of a system in relation to the distribution of the hydraulic head (energy) and the pressure in the pipes of the network. The objective of this study was to examine the distribution of the parameters of hydraulic irrigation pipes, which were optimised using genetic algorithms. The degree of the optimisation was evaluated with the help of the genetic algorithms based on the diameters of stretch of the network: two for the lateral lines, four for the derivation lines, four for the secondary lines and one for the main line. A MatLab code was developed that considered all of the losses of energy, both distributed losses and those at specific locations between the beginning of the network and the pump system. The sensitivity analysis was based on the variations in the slope of the ground (0%, 2.5% and 5%). The results show that for pipes with a distributed flow, the influence of the behaviour of the kinetic energy in the pipe contributed to the distance between the energy lines and the piezometric lines at the beginning of each stretch after the decrease in the diameter of the pipes. At the end of the pipes, the values of the energy lines and the piezometric lines were very similar, and they were essentially the same for the final emitter.

Share and Cite:

Marcuzzo, F. and Wendland, E. (2014) The Optimization of Irrigation Networks Using Genetic Algorithms. Journal of Water Resource and Protection, 6, 1124-1138. doi: 10.4236/jwarp.2014.612105.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Kuwabara, G. and Matsura, E.E. (1996) An Evaluation of the Hydraulic Behaviour of the Lateral Lines of Dripper Tubes. In: National Congress OF Irrigation and Drainage, 11. 1996, Campinas. Anais... Vicosa: Brazilian Association of Irrigation and Drainage, 275-287.
[2] Santiago, F.S., Montenegro, A.A.A. and Montenegro, S.M.G.L. (2004) Evaluation of Hydraulic Parameters and the Management of Microsprinkler Irrigation in a Settlement Area. Engenharia Agricola, 24, 632-643.
[3] Souza, I.H., Andrade, E.M. and Silva, E.L. (2005) Design and Hydraulics Evaluation of a Low-Head Microirrigation Bubbler System. Engenharia Agricola, 25, 264-271.
[4] Saad, J.C.C. and Marino, M.A. (2002) Optimum Design of Microirrigation Systems in Sloping Lands. Journal of Irrigation and Drainage Engineering, 128, 116.
[5] Saad, J.C.C. and Frizzone, J.A. (1996) Design and Management Optimization of Trickle Irrigation System Using Non-Linear Programming. Journal of Agricultural Engineering Research, 64, 109-118.
[6] Lucena, K.F.M. and Matos, J.A. (2001) Economic Analysis of Sub-Units of Localised Irrigation. In: Brazilian Congress of Agricultural Engineering, 30, 2001. Foz do Iguacu: Anais... Foz do Iguacu: Brazilian Association of Agricultural Engineering, 2001. 1 CD-ROM.
[7] Sarkar, S., Goswami, S.B., Mallick, S. and Nanda, M.K. (2008) Different Indices to Characterize Water Use Pattern of Micro-Sprinkler Irrigated Onion (Allium cepa L.). Agricultural Water Management, 95, 625-632.
[8] Sezen, S.M., et al. (2011) Comparison of Drip and Sprinkler Irrigation Strategies on Sunflower Seed and Oil Yield and Quality under Mediterranean Climatic Conditions. Agricultural Water Management, 98, 1153-1161.
[9] Gomes, A.W.A., Frizzone, J.A., Rettore Neto, O. and Miranda de, J.H. (2010) Localised Head Loss in Drippers Integrated into Polyethylene Tubes. Scielo Web Publishing.
[10] Zitterell Danieli, B., et al. (2009) Head Loss of Microtubes and Connectors Used in Irrigation. Publishing Scielo Brasil.
[11] Jin, X., Zhang, J., Gao, J. and Wu, W. (2007) Multi-Objective Optimization of Water Supply Network Rehabilitation with Non-Dominated Sorting Genetic Algorithm-II. Journal of Zhejiang University SCIENCE A, 9, 391-400.
[12] Opan, M. (2010) Irrigation-Energy Management Using a DPSA-Based Optimization Model in the Ceyhan Basin of Turkey. Journal of Hydrology, 385, 353-360.
[13] Singh, R.M. (2010) Design of Barrages with Genetic Algorithm Based Embedded Simulation Optimization Approach. Water Resources Management, 25, 409-429.
[14] Scaloppi, E.J. (1988) Adjusted F Factor for Multiple-Outlet Pipes. Journal of Irrigation and Drainage Engineering, 114, 169-174.
[15] Swamee, P.K. (1993) Design of a Submarine Pipeline. Journal of Transportation Engineering, 119, 159-170.
[16] Porto, R.M. (2006) Basic Hydraulics. 4th Edition, Rettec Grafica and Editor, Sao Paulo.
[17] Aneel, National Agency of Electric Energy (2006) Homologation Resolution No. 313 on the Fees for Providing Electric Energy. ANNEL Web Publishing, Brasilia, 12 p.
[18] Noronha, J.F. and Latapia, M.X.I.C. (1998) Custos de producao sob condicoes de risco no estado de Sao Paulo. Revista de Economia e Sociologia Rural, 26, 275-287.
[19] Frizzone, J.A. (2005) Analise de decisao economica em irrigacao. ESALQ, Piracicaba, 371 p.
[20] Marcuzzo, F.F.N. (2008) Sistema de otimizacao hidraulica e economica de rede de irrigacao localizada usando algoritmos geneticos. Tese de doutorado. EESC/USP, Sao Carlos, 361 p.
[21] Marcuzzo, F.F.N. and Wendland, E. (2010) Efeito da variacao na tarifacao pelo uso da agua no dimensionamento otimizado de rede de irrigacao localizada usando algoritmos geneticos. Revista Brasileira de Recursos Hidricos, 15, 109-118.
[22] Marcuzzo, F.F.N. and Wendland, E. (2010) Otimizacao de rede de irrigacao de microaspersao usando algoritmos geneticos sob diferentes declividades e tarifacao de agua e energia eletrica. Engenharia na Agricultura, 18, 50-62.
[23] Marcuzzo, F.F.N. and Wendland, E. (2011) Distribuicao de pressao em rede de irrigacao localizada otimizada por algoritmos geneticos. Engenharia Agricola, 31, 497-505.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.