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Development of a direct-solution algorithm for determining the optimal crop planning of farms using deficit irrigation

Author

Listed:
  • López-Mata, E.
  • Orengo-Valverde, J.J.
  • Tarjuelo, J.M.
  • Martínez-Romero, A.
  • Domínguez, A.

Abstract

The irrigation farms placed in areas of scare water demand methodologies that can increase their profitability via more efficient use of their resources. Determining the combination of factors that maximizes the profitability of any productive process requires the use of optimization methodologies. Traditionally, these types of problems were solved using heuristic methods. However, a direct-solution algorithm would produce faster and more accurate solutions. The aim of this work was to develop a direct-solution algorithm capable of determining the crop planning (area and volume of water per crop) that maximizes the profitability of an irrigation farm. The data required by the algorithm include the total cultivable area of the farm and the amount of available irrigation water as well as the “gross margin vs. irrigation depth” functions of the considered crops. Cultivating one or two crops is the way to reach higher profitability, but this strategy is not suitable from an agricultural point of view (i.e., crop rotation, diseases, weather risks, regulations of agricultural policies, etc.). Due to this algorithm must be compatible with the MOPECO model, a methodology has been developed to allow its implementation in this model. The objective of this software is to maximize the profitability of irrigation farms by incorporating a more efficient use of irrigation water using regulated deficit irrigation techniques. The current version of this model uses genetic algorithms for determining optimal crop planning, which are time consuming. For a hypothetical 100ha farm, considering 10 different crops and 11 scenarios of water availability, the developed algorithm adapted to MOPECO achieved gross margins around 0.5% lower than LINGO, and 1.1% higher than genetic algorithms, decreasing the calculation time requirements by between 50 and 100 and approximately 2000 times, respectively. Another relevant result is the fact that the algorithm may be used manually, by drawing the tangent lines between the gross margin curves, for reaching the optimal combinations of irrigation depth and, indirectly, the cultivable area of each crop. Moreover, the algorithm allows to understand the relationships among crops, which may advise users in the determination of the optimal solution under real conditions. This methodology also highlights the importance of using regulated deficit irrigation techniques when managing irrigation farms with a low supply of irrigation water. The developed algorithm may also be useful in the optimization of other production processes.

Suggested Citation

  • López-Mata, E. & Orengo-Valverde, J.J. & Tarjuelo, J.M. & Martínez-Romero, A. & Domínguez, A., 2016. "Development of a direct-solution algorithm for determining the optimal crop planning of farms using deficit irrigation," Agricultural Water Management, Elsevier, vol. 171(C), pages 173-187.
    • Handle: RePEc:eee:agiwat:v:171:y:2016:i:c:p:173-187
    DOI: 10.1016/j.agwat.2016.03.015
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    13. Domínguez, A. & Martínez-Romero, A. & Leite, K.N. & Tarjuelo, J.M. & de Juan, J.A. & López-Urrea, R., 2013. "Combination of typical meteorological year with regulated deficit irrigation to improve the profitability of garlic growing in central spain," Agricultural Water Management, Elsevier, vol. 130(C), pages 154-167.
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    1. Martínez-Romero, A. & Domínguez, A. & Landeras, G., 2019. "Regulated deficit irrigation strategies for different potato cultivars under continental Mediterranean-Atlantic conditions," Agricultural Water Management, Elsevier, vol. 216(C), pages 164-176.
    2. Domínguez, Alfonso & Schwartz, Robert C. & Pardo, José J. & Guerrero, Bridget & Bell, Jourdan M. & Colaizzi, Paul D. & Louis Baumhardt, R., 2022. "Center pivot irrigation capacity effects on maize yield and profitability in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 261(C).
    3. López-Urrea, R. & Domínguez, A. & Pardo, J.J. & Montoya, F. & García-Vila, M. & Martínez-Romero, A., 2020. "Parameterization and comparison of the AquaCrop and MOPECO models for a high-yielding barley cultivar under different irrigation levels," Agricultural Water Management, Elsevier, vol. 230(C).
    4. Wu, Hui & Li, Xiaojuan & Lu, Hongna & Tong, Ling & Kang, Shaozhong, 2023. "Crop acreage planning for economy- resource- efficiency coordination: Grey information entropy based uncertain model," Agricultural Water Management, Elsevier, vol. 289(C).
    5. Cervantes-Gaxiola, Maritza E. & Sosa-Niebla, Erik F. & Hernández-Calderón, Oscar M. & Ponce-Ortega, José M. & Ortiz-del-Castillo, Jesús R. & Rubio-Castro, Eusiel, 2020. "Optimal crop allocation including market trends and water availability," European Journal of Operational Research, Elsevier, vol. 285(2), pages 728-739.
    6. Domínguez, A. & Martínez-Navarro, A. & López-Mata, E. & Tarjuelo, J.M. & Martínez-Romero, A., 2017. "Real farm management depending on the available volume of irrigation water (part I): Financial analysis," Agricultural Water Management, Elsevier, vol. 192(C), pages 71-84.
    7. Martínez-Romero, A. & Martínez-Navarro, A. & Pardo, J.J. & Montoya, F. & Domínguez, A., 2017. "Real farm management depending on the available volume of irrigation water (part II): Analysis of crop parameters and harvest quality," Agricultural Water Management, Elsevier, vol. 192(C), pages 58-70.
    8. López-Mata, E. & Tarjuelo, J.M. & Orengo-Valverde, J.J. & Pardo, J.J. & Domínguez, A., 2019. "Irrigation scheduling to maximize crop gross margin under limited water availability," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    9. Martínez-Romero, A. & López-Urrea, R. & Montoya, F. & Pardo, J.J. & Domínguez, A., 2021. "Optimization of irrigation scheduling for barley crop, combining AquaCrop and MOPECO models to simulate various water-deficit regimes," Agricultural Water Management, Elsevier, vol. 258(C).

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