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Optimal Allocation of Resources for Increasing Farm Revenue under Hydrological Uncertainty

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  • Ajay Singh

    (Indian Institute of Technology Kharagpur)

Abstract

The formulation and application of two optimization models is presented in this study. The models were used to maximize the net farm revenue of an irrigated area located in northwest India by optimally allocating the available water and land resources. In order to moderate the rising water table issues, a ground water component was introduced in the model, while still ensuring optimal resources allocation. Results of the model indicates a reduction in barley, gram, mustard, and rice production area while at the same time an increase in sugarcane, millets, wheat, and cotton cultivation areas under optimal conditions. The ground water exploitation has increased in the model allocation, which consecutively moderated the rising water table problems. The model allocations has resulted in more than 31 % increase in net farm revenue. The proposed models can be employed as a dependable tool for making the decisions at local and regional levels and are capable of solving the rising water table issues of irrigated areas. The formulations proposed in this study are simple and can be employed anywhere for capitalizing on the farm revenue by moderating the water resources problems. The model constraints, though, be different considering the quality and quantity aspects of different water sources.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:waterr:v:30:y:2016:i:7:d:10.1007_s11269-016-1306-x
    DOI: 10.1007/s11269-016-1306-x
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    References listed on IDEAS

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    Cited by:

    1. Hosein Sheibani & Hosein Alizadeh & Mojtaba Shourian, 2019. "Optimum Design and Operation of a Reservoir and Irrigation Network Considering Uncertainty of Hydrologic, Agronomic and Economic Factors," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(2), pages 863-879, January.
    2. 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).
    3. Chongfeng Ren & Ruihuan Li & Ping Guo, 2016. "Two-Stage DEA Analysis of Water Resource Use Efficiency," Sustainability, MDPI, vol. 9(1), pages 1-17, December.
    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.

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