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Optimization of Cropping Pattern in a Canal Command Area Using Fuzzy Programming Approach

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  • Paritosh Srivastava
  • Raj Singh

Abstract

Optimal cropping pattern depends on water availability and other constraints like crop area, soil properties, use of fertilizer, and local socio-economic conditions. Availability of water depends upon various hydrological and climatological factors like rainfall in area, aquifer properties of the area, existing canal network in the area etc. Use of surface and groundwater conjunctively not only improve production but also help in sustainable water utilization. Benefit and production (yield) are the two most important objectives for optimal cropping pattern. Single objectives considering benefit and production are formulated and solved for nine scenarios. Single objective separately optimize benefit or production only. Single objective maximization of benefit/production does not guarantee maximization of production/benefit. Multi objectives optimization of benefit and production simultaneously give optimal solution incorporating benefit and production. In present paper multi objectives optimization problem is formulated and solved using fuzzy programming approach (FPA) with linear, exponential and hyperbolic membership functions. Results of different optimization techniques (single objective, multi objective) and different membership functions are discussed and compared. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Paritosh Srivastava & Raj Singh, 2015. "Optimization of Cropping Pattern in a Canal Command Area Using Fuzzy Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(12), pages 4481-4500, September.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:12:p:4481-4500
    DOI: 10.1007/s11269-015-1071-2
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    References listed on IDEAS

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    Cited by:

    1. Ajay Singh, 2016. "Optimal Allocation of Resources for Increasing Farm Revenue under Hydrological Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2569-2580, May.
    2. J. Alarcón & L. Juana, 2016. "The Water Markets as Effective Tools of Managing Water Shortages in an Irrigation District," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2611-2625, June.
    3. Chen, Shu & Shao, Dongguo & Gu, Wenquan & Xu, Baoli & Li, Haoxin & Fang, Longzhang, 2017. "An interval multistage water allocation model for crop different growth stages under inputs uncertainty," Agricultural Water Management, Elsevier, vol. 186(C), pages 86-97.
    4. S. Dutta & B.C. Sahoo & Rajashree Mishra & S. Acharya, 2016. "Fuzzy Stochastic Genetic Algorithm for Obtaining Optimum Crops Pattern and Water Balance in a Farm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4097-4123, September.
    5. Chen, Shu & Shao, Dongguo & Tan, Xuezhi & Gu, Wenquan & Lei, Caixiu, 2017. "An interval multistage classified model for regional inter- and intra-seasonal water management under uncertain and nonstationary condition," Agricultural Water Management, Elsevier, vol. 191(C), pages 98-112.
    6. Ghazali, Mahboubeh & Honar, Tooraj & Nikoo, Mohammad Reza, 2018. "A hybrid TOPSIS-agent-based framework for reducing the water demand requested by stakeholders with considering the agents’ characteristics and optimization of cropping pattern," Agricultural Water Management, Elsevier, vol. 199(C), pages 71-85.
    7. Chen, Shu & Xu, Jijun & Li, Qingqing & Tan, Xuezhi & Nong, Xizhi, 2019. "A copula-based interval-bistochastic programming method for regional water allocation under uncertainty," Agricultural Water Management, Elsevier, vol. 217(C), pages 154-164.
    8. Shu Chen & Dongguo Shao & Xudong Li & Caixiu Lei, 2016. "Simulation-Optimization Modeling of Conjunctive Operation of Reservoirs and Ponds for Irrigation of Multiple Crops Using an Improved Artificial Bee Colony Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(9), pages 2887-2905, July.

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