IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v230y2020ics0378377419314076.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377419314076
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2019.105990?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gholamhoseini, M. & AghaAlikhani, M. & Modarres Sanavy, S.A.M. & Mirlatifi, S.M., 2013. "Interactions of irrigation, weed and nitrogen on corn yield, nitrogen use efficiency and nitrate leaching," Agricultural Water Management, Elsevier, vol. 126(C), pages 9-18.
    2. Pinto, Victor Meriguetti & Reichardt, Klaus & van Dam, Jos & Lier, Quirijn de Jong van & Bruno, Isabeli Pereira & Durigon, Angelica & Dourado-Neto, Durval & Bortolotto, Rafael Pivotto, 2015. "Deep drainage modeling for a fertigated coffee plantation in the Brazilian savanna," Agricultural Water Management, Elsevier, vol. 148(C), pages 130-140.
    3. Hack-ten Broeke, M. J. D., 2001. "Irrigation management for optimizing crop production and nitrate leaching on grassland," Agricultural Water Management, Elsevier, vol. 49(2), pages 97-114, July.
    4. Hu, Qiuli & Yang, Yonghui & Han, Shumin & Yang, Yanmin & Ai, Zhipin & Wang, Jiusheng & Ma, Fengyun, 2017. "Identifying changes in irrigation return flow with gradually intensified water-saving technology using HYDRUS for regional water resources management," Agricultural Water Management, Elsevier, vol. 194(C), pages 33-47.
    5. Mun, S. & Sassenrath, G.F. & Schmidt, A.M. & Lee, N. & Wadsworth, M.C. & Rice, B. & Corbitt, J.Q. & Schneider, J.M. & Tagert, M.L. & Pote, J. & Prabhu, R., 2015. "Uncertainty analysis of an irrigation scheduling model for water management in crop production," Agricultural Water Management, Elsevier, vol. 155(C), pages 100-112.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Zhongwei Liang & Tao Zou & Yupeng Zhang & Jinrui Xiao & Xiaochu Liu, 2022. "Sprinkler Drip Infiltration Quality Prediction for Moisture Space Distribution Using RSAE-NPSO," Agriculture, MDPI, vol. 12(5), pages 1-32, May.
    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. 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).
    5. 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).
    6. 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).
    7. 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).

    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. Hu, Qiuli & Zhao, Ying & Hu, Xinlong & Qi, Ji & Suo, Lizhu & Pan, Yinghua & Song, Bing & Chen, Xiaobing, 2022. "Effect of saline land reclamation by constructing the “Raised Field -Shallow Trench” pattern on agroecosystems in Yellow River Delta," Agricultural Water Management, Elsevier, vol. 261(C).
    2. Galioto, Francesco & Battilani, Adriano, 2021. "Agro-economic simulation for day by day irrigation scheduling optimisation," Agricultural Water Management, Elsevier, vol. 248(C).
    3. Li, Jungai & Liu, Hongbin & Wang, Hongyuan & Luo, Jiafa & Zhang, Xuejun & Liu, Zhaohui & Zhang, Yitao & Zhai, Limei & Lei, Qiuliang & Ren, Tianzhi & Li, Yan & Bashir, Muhammad Amjad, 2018. "Managing irrigation and fertilization for the sustainable cultivation of greenhouse vegetables," Agricultural Water Management, Elsevier, vol. 210(C), pages 354-363.
    4. Niu, G. & Li, Y.P. & Huang, G.H. & Liu, J. & Fan, Y.R., 2016. "Crop planning and water resource allocation for sustainable development of an irrigation region in China under multiple uncertainties," Agricultural Water Management, Elsevier, vol. 166(C), pages 53-69.
    5. Shahrokhnia, Mohammad Hossein & Sepaskhah, Ali Reza, 2016. "Effects of irrigation strategies, planting methods and nitrogen fertilization on yield, water and nitrogen efficiencies of safflower," Agricultural Water Management, Elsevier, vol. 172(C), pages 18-30.
    6. Liu, Jing & Bi, Xiaoqing & Ma, Maoting & Jiang, Lihua & Du, Lianfeng & Li, Shunjiang & Sun, Qinping & Zou, Guoyuan & Liu, Hongbin, 2019. "Precipitation and irrigation dominate soil water leaching in cropland in Northern China," Agricultural Water Management, Elsevier, vol. 211(C), pages 165-171.
    7. Hamidreza Kamali & Shahrokh Zand-Parsa, 2017. "Estimation of Sugar Beet Yield and its Dry Matter Partitioning Under Different Irrigation and Nitrogen Levels," Modern Applied Science, Canadian Center of Science and Education, vol. 11(1), pages 143-143, September.
    8. Bastiaanssen, W.G.M. & Allen, R.G. & Droogers, P. & D'Urso, G. & Steduto, P., 2007. "Twenty-five years modeling irrigated and drained soils: State of the art," Agricultural Water Management, Elsevier, vol. 92(3), pages 111-125, September.
    9. Jia, Xucun & Shao, Lijie & Liu, Peng & Zhao, Bingqiang & Gu, Limin & Dong, Shuting & Bing, So Hwat & Zhang, Jiwang & Zhao, Bin, 2014. "Effect of different nitrogen and irrigation treatments on yield and nitrate leaching of summer maize (Zea mays L.) under lysimeter conditions," Agricultural Water Management, Elsevier, vol. 137(C), pages 92-103.
    10. Feki, Mouna & Ravazzani, Giovanni & Ceppi, Alessandro & Mancini, Marco, 2018. "Influence of soil hydraulic variability on soil moisture simulations and irrigation scheduling in a maize field," Agricultural Water Management, Elsevier, vol. 202(C), pages 183-194.
    11. Zhicheng Qu & Yunzhao Li & Junbao Yu & Jisong Yang & Miao Yu & Di Zhou & Xuehong Wang & Zhikang Wang & Yang Yu & Yuanqing Ma & Yuhan Zou & Yue Ling, 2022. "Influence of Gate Dams on Yellow River Delta Wetlands," Land, MDPI, vol. 11(5), pages 1-18, May.
    12. Hu, Qiuli & Yang, Yonghui & Han, Shumin & Wang, Jiusheng, 2019. "Degradation of agricultural drainage water quantity and quality due to farmland expansion and water-saving operations in arid basins," Agricultural Water Management, Elsevier, vol. 213(C), pages 185-192.
    13. Liu, Wei & Fu, Qiang & Meng, Jun & Li, Tianxiao & Cheng, Kun, 2019. "Simulation and analysis of return flow at the field scale in the northern rice irrigation area of China," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    14. Guillaume Adeux & Simon Giuliano & Stéphane Cordeau & Jean-Marie Savoie & Lionel Alletto, 2017. "Low-Input Maize-Based Cropping Systems Implementing IWM Match Conventional Maize Monoculture Productivity and Weed Control," Agriculture, MDPI, vol. 7(9), pages 1-17, September.
    15. Hui, Xin & Zhao, He & Zhang, Haohui & Wang, Wentao & Wang, Jingjing & Yan, Haijun, 2023. "Specific power or droplet shear stress: Which is the primary cause of soil erosion under low-pressure sprinklers?," Agricultural Water Management, Elsevier, vol. 286(C).
    16. Lee, Dogil & Merrick, Jason & Rath, Sagarika & Dukes, Michael & Kaplan, David & Graham, Wendy, 2024. "Groundwater impacts of adding carrot to corn-peanut rotations in North Florida," Agricultural Water Management, Elsevier, vol. 294(C).
    17. Du, Huiying & Gao, Wenxuan & Li, Jiajia & Shen, Shizhou & Wang, Feng & Fu, Li & Zhang, Keqiang, 2019. "Effects of digested biogas slurry applicationmixed with irrigation water on nitrate leaching during wheat-maize rotation in the North China Plain," Agricultural Water Management, Elsevier, vol. 213(C), pages 882-893.
    18. Guo, Jinjin & Fan, Junliang & Xiang, Youzhen & Zhang, Fucang & Yan, Shicheng & Zhang, Xueyan & Zheng, Jing & Li, Yuepeng & Tang, Zijun & Li, Zhijun, 2022. "Coupling effects of irrigation amount and nitrogen fertilizer type on grain yield, water productivity and nitrogen use efficiency of drip-irrigated maize," Agricultural Water Management, Elsevier, vol. 261(C).
    19. Kopper, Sarah A. & Jayne, Thomas S. & Snapp, Sieglinde S., 2020. "Sifting through the weeds: Understanding heterogeneity in fertilizer and labor response in Central Malawi," Ecological Economics, Elsevier, vol. 169(C).
    20. Gilbert C. Sigua & Kenneth C. Stone & Phil J. Bauer & Ariel A. Szogi, 2020. "Efficacy of Supplemental Irrigation and Nitrogen Management on Enhancing Nitrogen Availability and Urease Activity in Soils with Sorghum Production," Sustainability, MDPI, vol. 12(20), pages 1-15, October.

    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:eee:agiwat:v:230:y:2020:i:c:s0378377419314076. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    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.