IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i14p11337-d1198857.html
   My bibliography  Save this article

A Comparative Analysis between Heuristic and Data-Driven Water Management Control for Precision Agriculture Irrigation

Author

Listed:
  • Leonardo D. Garcia

    (Tecnologico de Monterrey, School of Engineering and Science, Monterrey 64849, Mexico)

  • Camilo Lozoya

    (Tecnologico de Monterrey, School of Engineering and Science, Monterrey 64849, Mexico)

  • Antonio Favela-Contreras

    (Tecnologico de Monterrey, School of Engineering and Science, Monterrey 64849, Mexico)

  • Emanuele Giorgi

    (Tecnologico de Monterrey, School of Architecture, Art and Design, Monterrey 64849, Mexico)

Abstract

Modeling and control theory applied to precision agriculture irrigation systems have been essential to reduce water consumption while growing healthy crops. Specifically, implementing closed-loop control irrigation based on soil moisture measurements is an effective approach for obtaining water savings in this resource-intensive activity. To enhance this strategy, the work presented in this paper proposed a new set of water management strategies for the case in which multiple irrigation areas share a single water supply source and compared them with heuristic approaches commonly used by farmers in practice. The proposed water allocation algorithms are based on techniques used in real-time computing, such as dynamic priority and feedback scheduling. Therefore, the multi-area irrigation system is presented as a resource allocation problem with availability constraints, where water consumption represents the main optimization parameter. The obtained results show that the data-driven water allocation strategies preserve the water savings for closed-loop control systems and avoid crop water stress due to the limited access to irrigation water.

Suggested Citation

  • Leonardo D. Garcia & Camilo Lozoya & Antonio Favela-Contreras & Emanuele Giorgi, 2023. "A Comparative Analysis between Heuristic and Data-Driven Water Management Control for Precision Agriculture Irrigation," Sustainability, MDPI, vol. 15(14), pages 1-14, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11337-:d:1198857
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/14/11337/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/14/11337/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Panigrahi, B. & Panda, Sudhindra N., 2003. "Field test of a soil water balance simulation model," Agricultural Water Management, Elsevier, vol. 58(3), pages 223-240, February.
    2. Romero, R. & Muriel, J.L. & García, I. & Muñoz de la Peña, D., 2012. "Research on automatic irrigation control: State of the art and recent results," Agricultural Water Management, Elsevier, vol. 114(C), pages 59-66.
    3. Daniel Simon & Alexandre Seuret & Olivier Sename, 2017. "Real-time control systems: feedback, scheduling and robustness," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(11), pages 2368-2378, August.
    4. Bwambale, Erion & Abagale, Felix K. & Anornu, Geophrey K., 2022. "Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review," Agricultural Water Management, Elsevier, vol. 260(C).
    5. M. Safdar Munir & Imran Sarwar Bajwa & M. Asif Naeem & Bushra Ramzan, 2018. "Design and Implementation of an IoT System for Smart Energy Consumption and Smart Irrigation in Tunnel Farming," Energies, MDPI, vol. 11(12), pages 1-18, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nyakudya, Innocent Wadzanayi & Stroosnijder, Leo & Nyagumbo, Isaiah, 2014. "Infiltration and planting pits for improved water management and maize yield in semi-arid Zimbabwe," Agricultural Water Management, Elsevier, vol. 141(C), pages 30-46.
    2. Silva, Marcos Dornelas Freitas Machado e & Calijuri, Maria Lúcia & Sales, Francisco José Ferreira de & Souza, Mauro Henrique Batalha de & Lopes, Lucas Sampaio, 2014. "Integration of technologies and alternative sources of water and energy to promote the sustainability of urban landscapes," Resources, Conservation & Recycling, Elsevier, vol. 91(C), pages 71-81.
    3. Wang, Wendi & Straffelini, Eugenio & Tarolli, Paolo, 2023. "Steep-slope viticulture: The effectiveness of micro-water storage in improving the resilience to weather extremes," Agricultural Water Management, Elsevier, vol. 286(C).
    4. Mandal, Uttam Kumar & Victor, U.S. & Srivastava, N.N. & Sharma, K.L. & Ramesh, V. & Vanaja, M. & Korwar, G.R. & Ramakrishna, Y.S., 2007. "Estimating yield of sorghum using root zone water balance model and spectral characteristics of crop in a dryland Alfisol," Agricultural Water Management, Elsevier, vol. 87(3), pages 315-327, February.
    5. Pedro Garcia-Caparros & Juana Isabel Contreras & Rafael Baeza & Maria Luz Segura & Maria Teresa Lao, 2017. "Integral Management of Irrigation Water in Intensive Horticultural Systems of Almería," Sustainability, MDPI, vol. 9(12), pages 1-21, December.
    6. Hong, Minki & Lee, Sang-Hyun & Lee, Seung-Jae & Choi, Jin-Yong, 2021. "Application of high-resolution meteorological data from NCAM-WRF to characterize agricultural drought in small-scale farmlands based on soil moisture deficit," Agricultural Water Management, Elsevier, vol. 243(C).
    7. Escarabajal-Henarejos, D. & Molina-Martínez, J.M. & Fernández-Pacheco, D.G. & García-Mateos, G., 2015. "Methodology for obtaining prediction models of the root depth of lettuce for its application in irrigation automation," Agricultural Water Management, Elsevier, vol. 151(C), pages 167-173.
    8. Guilherme Jesus & Martim L. Aguiar & Pedro D. Gaspar, 2022. "Computational Tool to Support the Decision in the Selection of Alternative and/or Sustainable Refrigerants," Energies, MDPI, vol. 15(22), pages 1-20, November.
    9. Hrozencik, Aaron & Wallander, Steven & Aillery, Marcel, 2021. "Irrigation Organizations: Water Storage and Delivery Infrastructure," Economic Brief 327232, United States Department of Agriculture, Economic Research Service.
    10. Petit, Julien & García, Sílvia Mas & Molle, Bruno & Bendoula, Ryad & Ait-Mouheb, Nassim, 2022. "Methods for drip irrigation clogging detection, analysis and understanding: State of the art and perspectives," Agricultural Water Management, Elsevier, vol. 272(C).
    11. Shao, Guomin & Han, Wenting & Zhang, Huihui & Zhang, Liyuan & Wang, Yi & Zhang, Yu, 2023. "Prediction of maize crop coefficient from UAV multisensor remote sensing using machine learning methods," Agricultural Water Management, Elsevier, vol. 276(C).
    12. Chiara Bersani & Ahmed Ouammi & Roberto Sacile & Enrico Zero, 2020. "Model Predictive Control of Smart Greenhouses as the Path towards Near Zero Energy Consumption," Energies, MDPI, vol. 13(14), pages 1-17, July.
    13. Yeboah, Samuel, 2023. "Unlocking the Potential of Technological Innovations for Sustainable Agriculture in Developing Countries: Enhancing Resource Efficiency and Environmental Sustainability," MPRA Paper 118215, University Library of Munich, Germany, revised 26 Jul 2023.
    14. Ma, Ying & Feng, Shaoyuan & Song, Xianfang, 2013. "A root zone model for estimating soil water balance and crop yield responses to deficit irrigation in the North China Plain," Agricultural Water Management, Elsevier, vol. 127(C), pages 13-24.
    15. Ji, Xi-Bin & Kang, Er-Si & Chen, Ren-Sheng & Zhao, Wen-Zhi & Zhang, Zhi-Hui & Jin, Bo-Wen, 2007. "A mathematical model for simulating water balances in cropped sandy soil with conventional flood irrigation applied," Agricultural Water Management, Elsevier, vol. 87(3), pages 337-346, February.
    16. Jianqiang Deng & Xiaomin Chen & Zhenjie Du & Yong Zhang, 2011. "Soil Water Simulation and Predication Using Stochastic Models Based on LS-SVM for Red Soil Region of China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(11), pages 2823-2836, September.
    17. Li Bin & Muhammad Shahzad & Hira Khan & Muhammad Mehran Bashir & Arif Ullah & Muhammad Siddique, 2023. "Sustainable Smart Agriculture Farming for Cotton Crop: A Fuzzy Logic Rule Based Methodology," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
    18. Luis Pastor Sánchez-Fernández & Diego Alberto Flores-Carrillo & Luis Alejandro Sánchez-Pérez, 2024. "Computer Model for an Intelligent Adjustment of Weather Conditions Based on Spatial Features for Soil Moisture Estimation," Mathematics, MDPI, vol. 12(1), pages 1-33, January.
    19. Konstantina Ragazou & Alexandros Garefalakis & Eleni Zafeiriou & Ioannis Passas, 2022. "Agriculture 5.0: A New Strategic Management Mode for a Cut Cost and an Energy Efficient Agriculture Sector," Energies, MDPI, vol. 15(9), pages 1-17, April.
    20. Hrozencik, Aaron & Wallander, Steven & Aillery, Marcel, 2021. "Irrigation Organizations: Water Storage and Delivery Infrastructure," USDA Miscellaneous 314931, United States Department of Agriculture.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11337-:d:1198857. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.