IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i6p739-d1401089.html
   My bibliography  Save this article

Modeling Irrigation of Tomatoes with Saline Water in Semi-Arid Conditions Using Hydrus-1D

Author

Listed:
  • Sabri Kanzari

    (National Institute of Rural Engineering, Waters, and Forestry, University of Carthage, Ariana 2080, Tunisia)

  • Jiří Šimůnek

    (Department of Environmental Sciences, University of California Riverside, Riverside, CA 92507, USA)

  • Issam Daghari

    (National Institute of Agronomy, University of Carthage, Tunis 1082, Tunisia)

  • Anis Younes

    (Institut Terre et Environnement de Strasbourg, Université de Strasbourg, CNRS, ENGEES, UMR 7063, 67084 Strasbourg, France)

  • Khouloud Ben Ali

    (National Institute of Rural Engineering, Waters, and Forestry, University of Carthage, Ariana 2080, Tunisia)

  • Sana Ben Mariem

    (National Institute of Rural Engineering, Waters, and Forestry, University of Carthage, Ariana 2080, Tunisia)

  • Samir Ghannem

    (National Institute of Rural Engineering, Waters, and Forestry, University of Carthage, Ariana 2080, Tunisia
    Faculty of Sciences of Bizerte (FSB), University of Carthage, Jarzouna 7021, Tunisia)

Abstract

In arid and semi-arid regions like Tunisia, irrigation water is typically saline, posing a risk of soil and crop salinization and yield reduction. This research aims to study the combined effects of soil matric and osmotic potential stresses on tomato root water uptake. Plants were grown in pot and field experiments in loamy-clay soils and were irrigated with three different irrigation water qualities: 0, 3.5, and 7 dS/m. The Hydrus-1D model was used to simulate the combined dynamics of subsurface soil water and salts. Successful calibration and validation of the model against measured water and salt profiles enabled the examination of the combined effects of osmotic and matric potential stresses on root water uptake. Relative yields, indirectly estimated from actual and potential transpiration, indicated that the multiplicative stress response model effectively simulated the measured yields and the impact of saline water irrigation on crop yields. The experimental and modeling results provide information to aid in determining the salinity levels conducive to optimal crop growth. The findings indicate that the selected salinity levels affect tomato growth to varying degrees. Specifically, the salinity levels conducive to optimal tomato growth were between 0 and 3.5 dS/m, with a significant growth reduction above this salinity level. The gradual salinization of the root zone further evidenced this effect. The scenario considering a temperature increase of 2 °C had no significant impact on crop yields in the pot and field experiments.

Suggested Citation

  • Sabri Kanzari & Jiří Šimůnek & Issam Daghari & Anis Younes & Khouloud Ben Ali & Sana Ben Mariem & Samir Ghannem, 2024. "Modeling Irrigation of Tomatoes with Saline Water in Semi-Arid Conditions Using Hydrus-1D," Land, MDPI, vol. 13(6), pages 1-16, May.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:6:p:739-:d:1401089
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/6/739/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/13/6/739/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Jingang & Chen, Jing & He, Pingru & Chen, Dan & Dai, Xiaoping & Jin, Qiu & Su, Xiaoyue, 2022. "The optimal irrigation water salinity and salt component for high-yield and good-quality of tomato in Ningxia," Agricultural Water Management, Elsevier, vol. 274(C).
    2. Kumar, P. & Sarangi, A. & Singh, D.K. & Parihar, S.S. & Sahoo, R.N., 2015. "Simulation of salt dynamics in the root zone and yield of wheat crop under irrigated saline regimes using SWAP model," Agricultural Water Management, Elsevier, vol. 148(C), pages 72-83.
    3. Zhang, Junwei & Xiang, Lingxiao & Zhu, Chenxi & Li, Wuqiang & Jing, Dan & Zhang, Lili & Liu, Yong & Li, Tianlai & Li, Jianming, 2023. "Evaluating the irrigation schedules of greenhouse tomato by simulating soil water balance under drip irrigation," Agricultural Water Management, Elsevier, vol. 283(C).
    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. Li, Jingang & He, Pingru & Chen, Jing & Hamad, Amar Ali Adam & Dai, Xiaoping & Jin, Qiu & Ding, Siyu, 2023. "Tomato performance and changes in soil chemistry in response to salinity and Na/Ca ratio of irrigation water," Agricultural Water Management, Elsevier, vol. 285(C).
    2. Liu, Bingxia & Wang, Shiqin & Kong, Xiaole & Liu, Xiaojing & Sun, Hongyong, 2019. "Modeling and assessing feasibility of long-term brackish water irrigation in vertically homogeneous and heterogeneous cultivated lowland in the North China Plain," Agricultural Water Management, Elsevier, vol. 211(C), pages 98-110.
    3. Chengfu Yuan & Shaoyuan Feng & Zailin Huo & Quanyi Ji, 2019. "Simulation of Saline Water Irrigation for Seed Maize in Arid Northwest China Based on SWAP Model," Sustainability, MDPI, vol. 11(16), pages 1-14, August.
    4. Cheng, Minghui & Wang, Haidong & Fan, Junliang & Wang, Xiukang & Sun, Xin & Yang, Ling & Zhang, Shaohui & Xiang, Youzhen & Zhang, Fucang, 2021. "Crop yield and water productivity under salty water irrigation: A global meta-analysis," Agricultural Water Management, Elsevier, vol. 256(C).
    5. Sun, Lei & Li, Bo & Yao, Mingze & Niu, Dongshuang & Gao, Manman & Mao, Lizhen & Xu, Zhanyang & Wang, Tieliang & Wang, Jingkuan, 2023. "Optimising water and nitrogen management for greenhouse tomatoes in Northeast China using EWM−TOPSIS−AISM model," Agricultural Water Management, Elsevier, vol. 290(C).
    6. Wang, Xiaodong & Tian, Wei & Zheng, Wende & Shah, Sadiq & Li, Jianshe & Wang, Xiaozhuo & Zhang, Xueyan, 2023. "Quantitative relationships between salty water irrigation and tomato yield, quality, and irrigation water use efficiency: A meta-analysis," Agricultural Water Management, Elsevier, vol. 280(C).
    7. Wang, Xiangping & Liu, Guangming & Yang, Jingsong & Huang, Guanhua & Yao, Rongjiang, 2017. "Evaluating the effects of irrigation water salinity on water movement, crop yield and water use efficiency by means of a coupled hydrologic/crop growth model," Agricultural Water Management, Elsevier, vol. 185(C), pages 13-26.
    8. Li, Na & Xi, Hui & Zhou, Yang & Yu, Man & Hu, Zhenhua & Chen, Xijing, 2023. "Drip fertigation with food waste biogas effluent in a humid area is possible but challenging due to increased soil soluble sodium," Agricultural Water Management, Elsevier, vol. 290(C).
    9. Yu, Qihua & Kang, Shaozhong & Hu, Shunjun & Zhang, Lu & Zhang, Xiaotao, 2021. "Modeling soil water-salt dynamics and crop response under severely saline condition using WAVES: Searching for a target irrigation volume for saline water irrigation," Agricultural Water Management, Elsevier, vol. 256(C).
    10. Chen, Shuai & Mao, Xiaomin & Barry, David Andrew & Yang, Jian, 2019. "Model of crop growth, water flow, and solute transport in layered soil," Agricultural Water Management, Elsevier, vol. 221(C), pages 160-174.
    11. Dou, Zhiyao & Feng, Hanlong & Zhang, Hao & Abdelghany, Ahmed Elsayed & Zhang, Fucang & Li, Zhijun & Fan, Junliang, 2023. "Silicon application mitigated the adverse effects of salt stress and deficit irrigation on drip-irrigated greenhouse tomato," Agricultural Water Management, Elsevier, vol. 289(C).
    12. Xu, Xu & Sun, Chen & Neng, Fengtian & Fu, Jing & Huang, Guanhua, 2018. "AHC: An integrated numerical model for simulating agroecosystem processes—Model description and application," Ecological Modelling, Elsevier, vol. 390(C), pages 23-39.
    13. Lei, Guoqing & Zeng, Wenzhi & Yu, Jin & Huang, Jiesheng, 2023. "A comparison of physical-based and machine learning modeling for soil salt dynamics in crop fields," Agricultural Water Management, Elsevier, vol. 277(C).
    14. Hassanli, Mohammad & Ebrahimian, Hamed & Mohammadi, Ehsan & Rahimi, Amirreza & Shokouhi, Amirhossein, 2016. "Simulating maize yields when irrigating with saline water, using the AquaCrop, SALTMED, and SWAP models," Agricultural Water Management, Elsevier, vol. 176(C), pages 91-99.
    15. Zhang, Junwei & Xiang, Lingxiao & Liu, Yuxin & Jing, Dan & Zhang, Lili & Liu, Yong & Li, Wuqiang & Wang, Xiaoyan & Li, Tianlai & Li, Jianming, 2024. "Optimizing irrigation schedules of greenhouse tomato based on a comprehensive evaluation model," Agricultural Water Management, Elsevier, vol. 295(C).
    16. Genxiang Feng & Zhanyu Zhang & Zemin Zhang, 2019. "Evaluating the Sustainable Use of Saline Water Irrigation on Soil Water-Salt Content and Grain Yield under Subsurface Drainage Condition," Sustainability, MDPI, vol. 11(22), pages 1-18, November.

    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:jlands:v:13:y:2024:i:6:p:739-:d:1401089. 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.