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Optimized Planning of Different Crops in a Field Using Optimal Control in Portugal

Author

Listed:
  • Rui M. S. Pereira

    (Department of Mathematics and Center of Physics, University of Minho, 4710-057 Braga, Portugal)

  • Sofia Lopes

    (Department of Mathematics and Center of Physics, University of Minho, 4710-057 Braga, Portugal
    SYSTEC—Research Center for Systems and Technologies, University of Porto, 4200-465 Porto, Portugal)

  • Amélia Caldeira

    (SYSTEC—Research Center for Systems and Technologies, University of Porto, 4200-465 Porto, Portugal
    LEMA-ISEP, Instituto Politécnico do Porto, 4200-072 Porto, Portugal)

  • Victor Fonte

    (Department of Informatics, University of Minho, 4710-057 Braga, Portugal
    UNU-EGOV, R. Vila Flor 166, 4810-225 Guimarães, Portugal
    INESC TEC, R. Dr. Roberto Frias, 4200-465 Porto, Portugal)

Abstract

Climate change is a proven fact. In the report of 2007 from IPCC, one can read that global warming is an issue to be dealt with urgently. In many parts of the world, the estimated rise of temperature (in a very near future) is significant. One of the most affected regions is the Iberian Peninsula, where the increasing need for water will very soon be a problem. Therefore, it is necessary that decision makers are able to decide on all issues related to water management. In this paper, we show a couple of mathematical models that can aid the decision making in the management of an agricultural field at a given location. Having a field, in which different crops can be produced, the solution of the first model indicates the area that should be used for each crop so that the profit is as large as possible, while the water spent is the smallest possible guaranteeing the water requirements of each crop. Using known data for these crops in Portugal, including costs of labour, machines, energy and water, as well as the estimated value of the products obtained, the first mathematical model developed, via optimal control theory, obtains the best management solution. It allows creating different scenarios, thus it can be a valuable tool to help the farmer/decision maker decide the crop and its area to be cultivated. A second mathematical model was developed. It improves the first one, in the sense that it allows considering that water from the rainfall can be collected in a reservoir with a given capacity. The contribution of the collected water from the rainfall in the profit obtained for some different scenarios is also shown.

Suggested Citation

  • Rui M. S. Pereira & Sofia Lopes & Amélia Caldeira & Victor Fonte, 2018. "Optimized Planning of Different Crops in a Field Using Optimal Control in Portugal," Sustainability, MDPI, vol. 10(12), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:12:p:4648-:d:188552
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    References listed on IDEAS

    as
    1. 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.
    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.
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