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Irrigation, crop stress and drainage reduction under uncertainty: A scenario study

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  • Mondaca-Duarte, F.D.
  • van Mourik, S.
  • Balendonck, J.
  • Voogt, W.
  • Heinen, M.
  • van Henten, E.J.

Abstract

Two thirds of human water use is linked to agricultural practices including crop irrigation. Furthermore, excess irrigation leads to drainage problems. For this reason, reduced irrigation strategies need to be implemented to protect water resources. However, low irrigation may lead to crop water stress. A fast and inexpensive way to predict the necessary amount of irrigation required is by a model-based approach. With this approach, it is possible to explore the relation between irrigation, crop water stress and drainage. However, parameter uncertainty can reduce prediction accuracy. Therefore, the aims of this research were: (1) to develop and test a methodology that allows the analysis of uncertainty sources in irrigation strategies (2) to identify how much irrigation can be reduced while maintaining a low risk of crop stress, and (3) to explore the influence of uncertainty in soil parameters and evapotranspiration on model predictions. Results from a realistic case considered in this study indicated that, while maintaining a low risk of crop stress (<1 %), it is possible to reduce drainage (by 88 %) and water use (22 %) for a conventional irrigation strategy. This reduction is dependent on the type of risk aversion strategy and is specific for a case scenario where variations are certain.

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  • Mondaca-Duarte, F.D. & van Mourik, S. & Balendonck, J. & Voogt, W. & Heinen, M. & van Henten, E.J., 2020. "Irrigation, crop stress and drainage reduction under uncertainty: A scenario study," Agricultural Water Management, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:agiwat:v:230:y:2020:i:c:s0378377419314076
    DOI: 10.1016/j.agwat.2019.105990
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    2. Mondaca-Duarte, F.D. & Reyes-Lastiri, D. & Heinen, M. & van Henten, E.J. & van Mourik, S., 2023. "Visualization of uncertain leaching fraction and drought exposure as a function of irrigation dosage and frequency," Agricultural Water Management, Elsevier, vol. 283(C).
    3. Kafle, Kashi & Balasubramanya, Soumya, 2021. "Can Perceptions of Reduction in Physical Water Availability Affect Irrigation Behaviors? Evidence from Jordan," 2021 Conference, August 17-31, 2021, Virtual 315121, International Association of Agricultural Economists.
    4. Kayatz, Benjamin & Baroni, Gabriele & Hillier, Jon & Lüdtke, Stefan & Freese, Dirk & Wattenbach, Martin, 2024. "Supporting decision-making in agricultural water management under data scarcity using global datasets – chances, limits and potential improvements," Agricultural Water Management, Elsevier, vol. 296(C).
    5. Chen, Mengting & Cui, Yuanlai & Wang, Xiaonan & Xie, Hengwang & Liu, Fangping & Luo, Tongyuan & Zheng, Shizong & Luo, Yufeng, 2021. "A reinforcement learning approach to irrigation decision-making for rice using weather forecasts," Agricultural Water Management, Elsevier, vol. 250(C).
    6. Kafle, Kashi & Balasubramanya, Soumya, 2021. "IFAD Research Series Issues 66 - Can perceptions of reduction in physical water availability affect irrigation behaviour? Evidence from Jordan," IFAD Research Series 313230, International Fund for Agricultural Development (IFAD).
    7. Potopová, V. & Trnka, M. & Vizina, A. & Semerádová, D. & Balek, J. & Chawdhery, M.R.A. & Musiolková, M. & Pavlík, P. & Možný, M. & Štěpánek, P. & Clothier, B., 2022. "Projection of 21st century irrigation water requirements for sensitive agricultural crop commodities across the Czech Republic," Agricultural Water Management, Elsevier, vol. 262(C).

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