IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i4p532-d1365149.html
   My bibliography  Save this article

Modeling and Analysis of Rice Root Water Uptake under the Dual Stresses of Drought and Waterlogging

Author

Listed:
  • Jie Huang

    (Hubei Water Resources Research Institute, Wuhan 430070, China
    Hubei Provincial Water Saving Research Center, Wuhan 430070, China)

  • Wei Dong

    (Hubei Water Resources Research Institute, Wuhan 430070, China
    Hubei Provincial Water Saving Research Center, Wuhan 430070, China)

  • Luguang Liu

    (Hubei Water Resources Research Institute, Wuhan 430070, China
    Hubei Provincial Water Saving Research Center, Wuhan 430070, China)

  • Tiesong Hu

    (State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China)

  • Shaobin Pan

    (Hubei Water Resources Research Institute, Wuhan 430070, China
    Hubei Provincial Water Saving Research Center, Wuhan 430070, China)

  • Xiaowei Yang

    (Hubei Water Resources Research Institute, Wuhan 430070, China
    Hubei Provincial Water Saving Research Center, Wuhan 430070, China)

  • Jianan Qin

    (Hubei Water Resources Research Institute, Wuhan 430070, China
    Hubei Provincial Water Saving Research Center, Wuhan 430070, China)

Abstract

The development of an accurate root water-uptake model is pivotal for evaluating crop evapotranspiration; understanding the combined effect of drought and waterlogging stresses; and optimizing water use efficiency, namely, crop yield [kg/ha] per unit of ET [mm]. Existing models often lack quantitative approaches to depicting crop root water uptake in scenarios of concurrent drought and waterlogging moisture stresses. Addressing this as our objective; we modified the Feddes root water-uptake model by revising the soil water potential response threshold and by introducing a novel method to calculate root water-uptake rates under simultaneous drought and waterlogging stresses. Then, we incorporated a water stress lag effect coefficient, φ W s , that investigated the combined effect of historical drought and waterlogging stress events based on the assumption that the normalized influence weight of each past stress event decreases with an increase in the time interval before simulation as an exponential function of the decay rate. Further, we tested the model parameters and validated the results obtained with the modified model using data from three years (2016–2018) of rice ( Oryza sativa , L ) trails with pots in Bengbu, China. The modified Feddes model significantly improved precision by 9.6% on average when calculating relative transpiration rates, particularly post-stress recovery, and by 5.8% on average when simulating soil moisture fluctuations during drought periods. The root mean square error of relative transpiration was reduced by 60.8%, and soil water was reduced by 55.1%. By accounting for both the accumulated impact of past moisture stress and current moisture conditions in rice fields, the modified model will be useful in quantifying rice transpiration and rice water use efficiency in drought–waterlogging-prone areas in southern China.

Suggested Citation

  • Jie Huang & Wei Dong & Luguang Liu & Tiesong Hu & Shaobin Pan & Xiaowei Yang & Jianan Qin, 2024. "Modeling and Analysis of Rice Root Water Uptake under the Dual Stresses of Drought and Waterlogging," Agriculture, MDPI, vol. 14(4), pages 1-19, March.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:4:p:532-:d:1365149
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/4/532/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/14/4/532/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Albasha, Rami & Mailhol, Jean-Claude & Cheviron, Bruno, 2015. "Compensatory uptake functions in empirical macroscopic root water uptake models – Experimental and numerical analysis," Agricultural Water Management, Elsevier, vol. 155(C), pages 22-39.
    2. Wu, Xun & Zuo, Qiang & Shi, Jianchu & Wang, Lichun & Xue, Xuzhang & Ben-Gal, Alon, 2020. "Introducing water stress hysteresis to the Feddes empirical macroscopic root water uptake model," Agricultural Water Management, Elsevier, vol. 240(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. Wang, Tianshu & Xu, Yanqi & Zuo, Qiang & Shi, Jianchu & Wu, Xun & Liu, Lining & Sheng, Jiandong & Jiang, Pingan & Ben-Gal, Alon, 2023. "Evaluating and improving soil water and salinity stress response functions for root water uptake," Agricultural Water Management, Elsevier, vol. 287(C).
    2. Liu, Lining & Wang, Tianshu & Wang, Lichun & Wu, Xun & Zuo, Qiang & Shi, Jianchu & Sheng, Jiandong & Jiang, Pingan & Chen, Quanjia & Ben-Gal, Alon, 2022. "Plant water deficit index-based irrigation under conditions of salinity," Agricultural Water Management, Elsevier, vol. 269(C).
    3. Margarita A. Petoussi & Nicolas Kalogerakis, 2023. "Mathematical Modeling of Pilot Scale Olive Mill Wastewater Phytoremediation Units," Sustainability, MDPI, vol. 15(11), pages 1-36, May.
    4. Fabio V. Difonzo & Costantino Masciopinto & Michele Vurro & Marco Berardi, 2021. "Shooting the Numerical Solution of Moisture Flow Equation with Root Water Uptake Models: A Python Tool," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2553-2567, June.
    5. Fan, Jinjie & Wu, Xun & Yu, Yangliu & Zuo, Qiang & Shi, Jianchu & Halpern, Moshe & Sheng, Jiandong & Jiang, Pingan & Ben-Gal, Alon, 2023. "Characterizing root-water-uptake of wheat under elevated CO2 concentration," Agricultural Water Management, Elsevier, vol. 275(C).
    6. Mailhol, J.-C. & Albasha, R. & Cheviron, B. & Lopez, J.-M. & Ruelle, P. & Dejean, C., 2018. "The PILOTE-N model for improving water and nitrogen management practices: Application in a Mediterranean context," Agricultural Water Management, Elsevier, vol. 204(C), pages 162-179.
    7. Mishari A. Alnaim & Magdy S. Mohamed & Maged Mohammed & Muhammad Munir, 2022. "Effects of Automated Irrigation Systems and Water Regimes on Soil Properties, Water Productivity, Yield and Fruit Quality of Date Palm," Agriculture, MDPI, vol. 12(3), pages 1-21, February.
    8. Aixia, Ren & Weifeng, Zhao & Anwar, Sumera & Wen, Lin & Pengcheng, Ding & Ruixuan, Hao & Peiru, Wang & Rong, Zhong & Jin, Tong & Zhiqiang, Gao & Min, Sun, 2022. "Effects of tillage and seasonal variation of rainfall on soil water content and root growth distribution of winter wheat under rainfed conditions of the Loess Plateau, China," Agricultural Water Management, Elsevier, vol. 268(C).
    9. Jha, Shiva K. & Gao, Yang & Liu, Hao & Huang, Zhongdong & Wang, Guangshuai & Liang, Yueping & Duan, Aiwang, 2017. "Root development and water uptake in winter wheat under different irrigation methods and scheduling for North China," Agricultural Water Management, Elsevier, vol. 182(C), pages 139-150.
    10. Xufeng Li & Juanjuan Ma & Xihuan Sun & Lijian Zheng & Ruixia Chen & Jianglong An, 2023. "Estimating the Effects of Deficit Irrigation on Water Absorption and Utilization of Tomatoes Grown in Greenhouse with Hydrus-1D Model," Sustainability, MDPI, vol. 15(4), pages 1-17, February.
    11. Uniyal, Bhumika & Dietrich, Jörg, 2019. "Modifying Automatic Irrigation in SWAT for Plant Water Stress scheduling," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    12. Liu, Lining & Zuo, Qiang & Shi, Jianchu & Wu, Xun & Wei, Congmin & Sheng, Jiandong & Jiang, Pingan & Chen, Quanjia & Ben-Gal, Alon, 2023. "Balancing economic benefits and environmental repercussions based on smart irrigation by regulating root zone water and salinity dynamics," Agricultural Water Management, Elsevier, vol. 285(C).
    13. Appels, Willemijn M. & Karimi, Rezvan, 2021. "Analysis of soil wetting patterns in subsurface drip irrigation systems – Indoor alfalfa experiments," Agricultural Water Management, Elsevier, vol. 250(C).

    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:jagris:v:14:y:2024:i:4:p:532-:d:1365149. 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.