Determination of Optimum Cropping Pattern Using Advanced Optimization Algorithms
Publication: Journal of Hydrologic Engineering
Volume 23, Issue 6
Abstract
The quantity and various sources of water for irrigation are important controlling factors in the agricultural development of any area. The aim of this work is to determine an optimal cropping pattern to maximize the net annual returns, to conserve groundwater resources, and to use optimal land under cultivation for a region that has a scarcity of surface water resource and uncertain rainfall. Hence, mathematical models are developed based on data collected from government agencies, interviews of farmers in the region, and a practical survey of the region. An optimization problem is formulated based on the developed mathematical models. For this purpose, an optimization problem is formulated. Sinnar Taluka of Maharashtra state in India is the study area, in which groundwater is the only source for irrigation in this region. Hence, the Minor Irrigation Department (MID) of Nasik has planned an artificial recharge for the study area. The existing cropping pattern is studied extensively, and a new cropping pattern is suggested by solving the optimization problem using advanced optimization algorithms such as Jaya and particle swarm optimization (PSO). The PSO algorithm is widely used in water management. The Jaya algorithm is new in the area of water management and has significantly shown its competitiveness in this study. It has allocated land and water optimally in less computational time and provided higher net annual returns than PSO.
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Acknowledgments
The authors thank the Senior Geologist, Groundwater Surveys and Development Agency (GSDA) Nasik, India, Executive Engineer, Nasik Irrigation Department, Nasik, India and Taluka Agricultural Officer, Sinnar, India, for providing required data to conduct this study. The authors also thank other various government agencies of MS, India, who helped in one way or another to carry out this research. The authors used figures of the study area prepared by Maharashtra Remote Sensing Application Centre (Autonomous Body of Planning Department, Govt. of Maharashtra) VNIT Campus, S.A. Road, Nagpur. The authors express sincere thanks for providing these figures.
References
Abhishek, K., Kumar, V. R., Datta, S., and Mahapatra, S. S. (2017). “Application of Jaya algorithm for the optimization of machining performance characteristics during the turning of CFRP (epoxy) composites: Comparison with TLBO, GA, and ICA.” Eng. Comput., 33(3), 457–475.
Allen, R. G., Utah, L., Pereira, L. S., Raes, D., and Smith, M. (1998). “Crop evapotranspiration: Guidelines for computing crop water requirements.” FAO Irrigation and Drainage Paper No. 56, Rome.
Azimi, V., Salmasi, F., Entekhabi, N., Tabari, H., and Niaghi, A. R. (2013). “Optimization of deficit irrigation using non-linear programming (case study: Mianeh Region, Iran).” Int. J. Agric. Crop Sci., 6(5), 252–260.
Benli, B., and Kodal, S. (2003). “A non-linear model for farm optimization with adequate and limited water supplies application to the south-east Anatolian project (GAP) region.” Agric. Water Manage., 62(3), 187–203.
CropWat 8 [Computer software]. Food and Agriculture Organization, Rome.
Debbarman, J., Roy, P. K., and Mazumdar, A. (2013). “Assessment of dynamic groundwater potential of Agartala municipality area.” Int. J. Emerging Trends Eng. Dev., 3(1), 220–231.
Dhungel, R., and Fiedler, F. (2016). “Water balance approach to recharge calculations: Implications for watershed management using systems dynamics approach.” J. Hydrol., 3, 1–19.
Gharaman, B., and Sepaskhan, A. (2004). “Linear and non-linear optimization models for allocation of a limited water supply.” Irrig. Drain., 53(1), 39–54.
Karamouz, M., Zahraie, B., Kerachian, R., and Eslami, A. (2010). “Crop pattern and conjunctive use management: A case study.” Irrig. Drain., 59(2), 161–173.
Kaur, S., Aggarwal, R., Jalota, S., Vashisht, B., and Lubana, P. (2014). “Estimation of groundwater balance using soil-water-vegetation model and GIS.” Water Resour. Manage., 28(12), 4359–4371.
Kennedy, J., and Eberhart, R. (1995). “Particle swarm optimization.” Proc., IEEE Int. Conf. on Neural Network, Vol. 4, IEEE, New York, 1942–1948.
Kumar, C. P. (1997). “Estimation of natural groundwater recharge.” ISH J. Hydraul. Eng., 3(1), 61–74.
Kumar, P. G., and Srinivas, P. (2012). “Evaluation of groundwater resources and estimation of stage of groundwater development in a basin—A case study.” Irrig. Drain., 61(1), 129–139.
Lalehzari, R., Nasab, S. B., Moazed, H., and Haghighi, A. (2016). “Multiobjective management of water allocation to sustainable irrigation planning and optimal cropping pattern.” J. Irrig. Drain. Eng., 05015008.
Li, X., et al. (2017). “Applying uncertain programming model to improve regional farming economic benefits and water productivity.” Agric. Water Manage., 179, 352–365.
Maharashtra Remote Sensing Application Centre. (2018). ⟨http://www.mrsac.gov.in/en⟩ (Mar. 5, 2018).
Manghi, F., Mortazavi, B., Crother, C., and Hamdi, M. (2009). “Estimating regional groundwater recharge using a hydrological budget method.” Water Resour. Manage., 23(12), 2475–2489.
MATLAB [Computer software]. MathWorks, Natick, MA.
Noory, H., Liaghat, A. M., Parsinejad, M., and Haddad, O. B. (2012). “Optimizing irrigation water allocation and multicrop planning using discrete PSO algorithm.” J. Irrig. Drain. Eng., 437–444.
Oluwole, A. A., Oludayo, O. O., and Josiah, A. (2014). “A comparative study of state-of-the-art evolutionary multi-objective algorithms for optimal crop-mix planning.” Int. J. Agric. Sci. Technol., 2(1), 1–9.
PSO (Particle Swarm Optimization). (2018). “Population based stochastic optimization technique.” ⟨http://www.swarmintelligence.org⟩.
Raju, S. K., and Kumar, N. D. (2004). “Irrigation planning using genetic algorithms.” Water Resour. Manage., 18(2), 163–176.
Rao, R. V. (2016). “Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems.” Int. J. Ind. Eng. Comput., 7(1), 19–34.
Rao, R. V., More, K. C., Taler, J., and Ocłon, P. (2016). “Dimensional optimization of a micro-channel heat sink using Jaya algorithm.” Appl. Therm. Eng., 103, 572–582.
Rao, R. V., and Waghmare, G. G. (2016). “A new optimization algorithm for solving complex constrained design optimization problems.” Eng. Optim., 49(1), 60–83.
Shaikh, I. A., Wayayok, A., and Lee, T. S. (2015). “Preference index-based allocation of optimized cropping area at the Mirpurkhas Subdivision: Jamrao irrigation scheme in Sindh, Pakistan.” J. Irrig. Drain. Eng., 04015021.
Singh, A., and Panda, S. N. (2013). “Optimization and simulation modelling for managing the problems of water resources.” Water Resour. Manage., 27(9), 3421–3431.
Venkata Rao, R. (2018). “Jaya algorithm.” ⟨https://sites.google.com/site/jayaalgorithm/home⟩.
Warid, W., Hizam, H., Mariun, N., and Abdul-Wahab, N. I. (2016). “Optimal power flow using Jaya algorithm.” Energies, 9(9), 678.
Yang, Y. S., Kalin, R. M., Zhang, Y., Lin, X., and Zou, L. (2001). “Multi-objective optimization for sustainable groundwater resource management in a semiarid catchment.” Hydrol. Sci. J., 46(1), 55–72.
Zhang, Y., Yang, X., Cattani, C., Rao, R. V., Wang, S., and Phillips, P. (2016). “Tea category identification using a novel fractional Fourier entropy and Jaya algorithm.” Entropy, 18(77), 1–17.
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Published In
Journal of Hydrologic Engineering
Volume 23 • Issue 6 • June 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Apr 5, 2017
Accepted: Nov 20, 2017
Published online: Apr 12, 2018
Published in print: Jun 1, 2018
Discussion open until: Sep 12, 2018
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