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.
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References
Carvallo, H. O., Holzapfel, E. A., Lopez, M. A. and Marino, M. A.: 1998, 'Irrigated cropping optimization', J. Irrig. Drain. Engin. ASCE 124, 67–72.
Castillo, L. A. I., Morales, J. C. and Mariño, M. A.: 1997, 'A planning model for the Fuerte-Carrizo irrigation system, Mexico', Water Res. Manage. 11, 165–184.
Chang, F. H. and Chen, L.: 1998, 'Real-coded genetic algorithm for rule-based flood control reservoir management', Water Res. Manage. 12, 185–198.
Deb, K.: 1995, Optimization for Engineering Design: Algorithms and Examples. Prentice Hall, New Delhi.
Deb, K.: 1999, 'An introduction to genetic algorithms', Sadhana 24, 293–315.
Directorate of economics and statistics.: 1992, Statistical abstracts Andhra Pradesh, Government of Andhra Pradesh.
Garg, N. K. and Ali. A.: 1990, 'Two level optimization model for lower Indus basin', Agri. Water Manage. 36, 1–21.
Gentry, R.W., Camp, C. V. and Anderson, J. L.: 2001, 'Use of GA to determine areas of accretion to semi confined aquifer', J. Hydr. Engin. ASCE 127, 738–746.
Goldberg, D. E.: 1989, Genetic Algorithms. In: Search, Optimization and Machine Learning. Addison-Wesley, New York.
Gopalan, C., Sastri, B. V. R. and Balasubramanium, S. C.: 1984, Nutritive Value of Indian Foods. Indian Council of Medical Research, New Delhi.
Hilton, A. B. C. and Culver, T. B.: 2000, 'Constraint handling for genetic algorithms in optimal remediation design', J. Water Res. Plann. Manage. ASCE 126, 128–137.
Kumar, C. N., Indrasen, N. and Elango, K.: 1998, 'Nonlinear programming model for extensive irrigation', J. Irrig. Drain. Engin. ASCE 124, 123–1998.
Kuo, S. F., Merkley, G. P. and Liu, C. W.: 2000, 'Decision support for irrigation project planning using a genetic algorithm', Agri. Water Manage. 45, 243–266.
Lakshminarayana, V. and Rajagopalan, S. P.: 1977, 'Optimal cropping pattern for a basin in India', J. Irrig. Drain. Engin. ASCE 103, 53–70.
Loucks, D. P., Stedinger, J. R. and Haith, D. A.: 1981, Water Resources Systems Planning and Analysis. Prentice-Hall, Englewood Cliffs, New Jersey.
Maji, C. C. and Heady, E. O.: 1980, 'Optimal reservoir management and crop planning using deterministic and stochastic inflows', Water Res. Bull. 16, 438–443.
Mohammadi, E. M.: 1998, 'Irrigation planning: integrated approach', J. Water Res. Plann. Manage. ASCE 124, 272–279.
Mohan, S.: 1997, 'Parameter estimation of nonlinear muskingum models using genetic algorithm', J. Hydrl. Engin. ASCE 123, 137–142.
Nicklow, J. W., Ozkurt, O. and Bringer Jr. J. A.: 2003, Control of channel bed morphology in largescale river networks using a genetic algorithm', Water Res. Manage. 17, 113–132.
Paudyal, G. N. and Gupta, A. D.: 1990, 'Irrigation planning by multilevel optimisation', J. Irrig. Drain. Engin. ASCE 116, 273–291.
Reddy, S. L.: 1996, 'Optimal land grading based on genetic algorithms', J. Irrig. Drain. Engin. ASCE 122, 183–188.
Sharif, M. and Wardlaw, R.: 2000, 'Multireservoir systems optimization using genetic algorithms: case study', J. Comp. Civil Engin. ASCE 14, 255–263.
Sethi, L. N., Kumar, D. N., Panda, S. N. and Mal, B. C.: 2002, 'Optimal crop planning and conjunctive use of water resources in a coastal river basin', Water Res. Manage. 16, 145–169.
Tang, A. and Mays, L. W.: 1998, 'Genetic algorithms for optimal operation of soil aquifer treatment systems', Water Res. Manage. 12, 375–396.
Vedula, S. and Nagesh Kumar, D.: 1996, 'An integrated model for optimal reservoir operation for irrigation of multiple crops', Water Res. Res. 34, 1101–1108.
Wardlaw, R. and Sharif, M.: 1999, 'Evaluation of genetic algorithms for optimal reservoir system operation', Journal of Water Resources Planning and Management ASCE 125, 25–33.
Wu, Z. Y. and Simpson, A. R.: 2001, 'Competent genetic-evolutionary optimization of water distribution systems', J. Comp. Civil Engin. ASCE 15, 89–101.
Yoon, J. H. and Shoemaker, C. A.: 2001, 'An improved real-coded GA for groundwater bioremediation', J. Comp. Civil Engin. ASCE 15, 224–231.
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Srinivasa Raju, K., Nagesh Kumar, D. Irrigation Planning using Genetic Algorithms. Water Resources Management 18, 163–176 (2004). https://doi.org/10.1023/B:WARM.0000024738.72486.b2
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DOI: https://doi.org/10.1023/B:WARM.0000024738.72486.b2