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Irrigation Planning using Genetic Algorithms

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  • K. Srinivasa Raju
  • D. Nagesh Kumar

Abstract

The present study deals with the application of Genetic Algorithms(GA) for irrigation planning. The GA technique is used to evolve efficient cropping pattern for maximizing benefits for an irrigation project in India. Constraints include continuity equation, land and water requirements, crop diversification and restrictions on storage. Penalty function approach is used to convert constrained problem into an unconstrained one. For fixing GA parameters the model is run for various values of population, generations, cross over and mutation probabilities. It is found that the appropriate parameters for number of generations, population size, crossover probability, and mutation probability are 200, 50, 0.6 and 0.01 respectively for the present study. Results obtained by GA are compared with Linear Programming solution and found to be reasonably close. GA is found to be an effective optimization tool for irrigation planning and the results obtained can be utilized for efficient planning of any irrigation system. Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • K. Srinivasa Raju & D. Nagesh Kumar, 2004. "Irrigation Planning using Genetic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(2), pages 163-176, April.
    • Handle: RePEc:spr:waterr:v:18:y:2004:i:2:p:163-176
    DOI: 10.1023/B:WARM.0000024738.72486.b2
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    1. Laxmi Sethi & D. Kumar & Sudhindra Panda & Bimal Mal, 2002. "Optimal Crop Planning and Conjunctive Use of Water Resources in a Coastal River Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 16(2), pages 145-169, April.
    2. Kuo, Sheng-Feng & Merkley, Gary P. & Liu, Chen-Wuing, 2000. "Decision support for irrigation project planning using a genetic algorithm," Agricultural Water Management, Elsevier, vol. 45(3), pages 243-266, August.
    3. Aihua Tang & Larry Mays, 1998. "Genetic Algorithms for Optimal Operation of Soil Aquifer Treatment Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 12(5), pages 375-396, October.
    4. Fi-John Chang & Li Chen, 1998. "Real-Coded Genetic Algorithm for Rule-Based Flood Control Reservoir Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 12(3), pages 185-198, June.
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    3. Ajay Singh, 2014. "Irrigation Planning and Management Through Optimization Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 1-14, January.
    4. Aderemi Oluyinka Adewumi & Sivashan Chetty, 2017. "Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-22, August.
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    6. D. Regulwar & P Raj, 2008. "Development of 3-D Optimal Surface for Operation Policies of a Multireservoir in Fuzzy Environment Using Genetic Algorithm for River Basin Development and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(5), pages 595-610, May.
    7. Noor Khan & Mukand Babel & Tawatchai Tingsanchali & Roberto Clemente & Huynh Luong, 2012. "Reservoir Optimization-Simulation with a Sediment Evacuation Model to Minimize Irrigation Deficits," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(11), pages 3173-3193, September.
    8. Singh, Ajay, 2014. "Simulation–optimization modeling for conjunctive water use management," Agricultural Water Management, Elsevier, vol. 141(C), pages 23-29.
    9. Mandal, Uday & Dhar, Anirban & Panda, Sudhindra N., 2021. "Enhancement of sustainable agricultural production system by integrated natural resources management framework under climatic and operational uncertainty," Agricultural Water Management, Elsevier, vol. 252(C).
    10. Wang, Jinwen & Chen, Cheng & Liu, Shuangquan, 2018. "A new field-levelling procedure to minimize spillages in hydropower reservoir operation," Energy, Elsevier, vol. 160(C), pages 979-985.
    11. A. Vasan & Komaragiri Raju, 2007. "Application of Differential Evolution for Irrigation Planning: An Indian Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(8), pages 1393-1407, August.
    12. K. Ramakrishnan & C. Suribabu & T. Neelakantan, 2010. "Crop Calendar Adjustment Study for Sathanur Irrigation System in India Using Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 3835-3851, November.
    13. Qin Tu & Hong Li & Xinkun Wang & Chao Chen, 2015. "Ant Colony Optimization for the Design of Small-Scale Irrigation Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2323-2339, May.
    14. Gokmen Tayfur, 2017. "Modern Optimization Methods in Water Resources Planning, Engineering and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3205-3233, August.
    15. Shannak, Sa'd, 2022. "Optimizing dynamics of water-energy-food nexus in a desert climate," Energy Policy, Elsevier, vol. 164(C).
    16. Reeling, Carson J. & Lee, John & Mitchell, Peter & Halimi, Ghulam Hazrat & Carver, Andrew, 2012. "Policy options to enhance agricultural irrigation in Afghanistan: A canal systems approach," Agricultural Systems, Elsevier, vol. 109(C), pages 90-100.
    17. V. Jothiprakash & R. Arunkumar, 2013. "Optimization of Hydropower Reservoir Using Evolutionary Algorithms Coupled with Chaos," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 1963-1979, May.
    18. Haddad, Malik & Sanders, David, 2018. "Selection of discrete multiple criteria decision making methods in the presence of risk and uncertainty," Operations Research Perspectives, Elsevier, vol. 5(C), pages 357-370.
    19. V. Jothiprakash & Ganesan Shanthi & R. Arunkumar, 2011. "Development of Operational Policy for a Multi-reservoir System in India using Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(10), pages 2405-2423, August.
    20. Morimoto, T. & Ouchi, Y. & Shimizu, M. & Baloch, M.S., 2007. "Dynamic optimization of watering Satsuma mandarin using neural networks and genetic algorithms," Agricultural Water Management, Elsevier, vol. 93(1-2), pages 1-10, October.

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