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Numerical modeling to optimize nitrogen fertigation with consideration of transient drought and nitrogen stress

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  • Groenveld, Thomas
  • Argaman, Amir
  • Šimůnek, Jiří
  • Lazarovitch, Naftali

Abstract

Optimization of nitrogen (N) fertigation is a formidable challenge involving complex interactions between water and N uptake and their effects on crop production. Numerical models can be useful in studying the interaction of multiple variables like those found in mechanistic simulations of N fertigation strategies. The physical aspects can often be accurately represented in soil-plant-atmosphere continuum models, while the biological factors lag due to their oversimplification. When optimizing N fertigation using numerical models, it is essential to consider the effects of N and water stresses on the plant size and corresponding feedback on potential transpiration and N uptake. The HYDRUS (2D/3D) model was modified to allow for active uptake and decay of multiple solutes and reduce potential transpiration due to a limitation in N uptake. Subsequently, we calibrated and validated the model with a dataset that consisted of 3 nitrate (NO3-) concentration and 6 irrigation levels: a total of 18 distinct treatments used to fertigate cucumber plants grown in lysimeters. The calibration was based on the treatment that received the highest N fertigation. The model was validated by testing its ability to accurately reduce potential N uptake and transpiration in water and N deficiency cases. Simulations showed that the N stress function could explain 82% of the reduction in transpiration measured in the experimental setup. The sensitivity analysis, evaluating the effects of the root shape and distribution parameters by increasing and decreasing their values by 20%, showed that these parameters had little impact on the results. Following its validation, the model was used to determine the optimal N concentration in irrigation water and the optimal N application amount to obtain maximal yield with minimal N loss. The optimal irrigation water NO3--N concentration and seasonal NO3--N application were determined to be 75 mg L−1 and 40 mg m−2, respectively.

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  • Groenveld, Thomas & Argaman, Amir & Šimůnek, Jiří & Lazarovitch, Naftali, 2021. "Numerical modeling to optimize nitrogen fertigation with consideration of transient drought and nitrogen stress," Agricultural Water Management, Elsevier, vol. 254(C).
    • Handle: RePEc:eee:agiwat:v:254:y:2021:i:c:s0378377421002365
    DOI: 10.1016/j.agwat.2021.106971
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    References listed on IDEAS

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    1. Gardenas, A.I. & Hopmans, J.W. & Hanson, B.R. & Simunek, J., 2005. "Two-dimensional modeling of nitrate leaching for various fertigation scenarios under micro-irrigation," Agricultural Water Management, Elsevier, vol. 74(3), pages 219-242, June.
    2. Shouse, Peter J. & Ayars, James E. & Simunek, Jirí, 2011. "Simulating root water uptake from a shallow saline groundwater resource," Agricultural Water Management, Elsevier, vol. 98(5), pages 784-790, March.
    3. Li, Yong & Šimůnek, Jirka & Zhang, Zhentin & Jing, Longfei & Ni, Lixiao, 2015. "Evaluation of nitrogen balance in a direct-seeded-rice field experiment using Hydrus-1D," Agricultural Water Management, Elsevier, vol. 148(C), pages 213-222.
    4. Tao, Yuan & Li, Na & Wang, Shaoli & Chen, Haorui & Guan, Xiaoyan & Ji, Mengzhe, 2021. "Simulation study on performance of nitrogen loss of an improved subsurface drainage system for one-time drainage using HYDRUS-2D," Agricultural Water Management, Elsevier, vol. 246(C).
    5. Głąb, Tomasz & Szewczyk, Wojciech & Gondek, Krzysztof & Mierzwa-Hersztek, Monika & Palmowska, Joanna & Nęcka, Krzysztof, 2020. "Optimization of turfgrass fertigation rate and frequency," Agricultural Water Management, Elsevier, vol. 234(C).
    6. Tripler, Effi & Shani, Uri & Ben-Gal, Alon & Mualem, Yechezkel, 2012. "Apparent steady state conditions in high resolution weighing-drainage lysimeters containing date palms grown under different salinities," Agricultural Water Management, Elsevier, vol. 107(C), pages 66-73.
    7. Šimůnek, Jiří & Hopmans, Jan W., 2009. "Modeling compensated root water and nutrient uptake," Ecological Modelling, Elsevier, vol. 220(4), pages 505-521.
    8. Wang, Zhen & Li, Jiusheng & Li, Yanfeng, 2014. "Simulation of nitrate leaching under varying drip system uniformities and precipitation patterns during the growing season of maize in the North China Plain," Agricultural Water Management, Elsevier, vol. 142(C), pages 19-28.
    9. Bristow, Keith L. & Šimůnek, Jirka & Helalia, Sarah A. & Siyal, Altaf A., 2020. "Numerical simulations of the effects furrow surface conditions and fertilizer locations have on plant nitrogen and water use in furrow irrigated systems," Agricultural Water Management, Elsevier, vol. 232(C).
    10. Karandish, Fatemeh & Šimůnek, Jiří, 2017. "Two-dimensional modeling of nitrogen and water dynamics for various N-managed water-saving irrigation strategies using HYDRUS," Agricultural Water Management, Elsevier, vol. 193(C), pages 174-190.
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    Cited by:

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    2. Chen, Ning & Li, Xianyue & Šimůnek, Jiří & Shi, Haibin & Zhang, Yuehong & Hu, Qi, 2022. "Quantifying inter-species nitrogen competition in the tomato-corn intercropping system with different spatial arrangements," Agricultural Systems, Elsevier, vol. 201(C).
    3. Krevh, Vedran & Filipović, Lana & Petošić, Dragutin & Mustać, Ivan & Bogunović, Igor & Butorac, Jasminka & Kisić, Ivica & Defterdarović, Jasmina & Nakić, Zoran & Kovač, Zoran & Pereira, Paulo & He, Ha, 2023. "Long-term analysis of soil water regime and nitrate dynamics at agricultural experimental site: Field-scale monitoring and numerical modeling using HYDRUS-1D," Agricultural Water Management, Elsevier, vol. 275(C).
    4. Eva Hyánková & Michal Kriška Dunajský & Ondřej Zedník & Ondřej Chaloupka & Miroslava Pumprlová Němcová, 2021. "Irrigation with Treated Wastewater as an Alternative Nutrient Source (for Crop): Numerical Simulation," Agriculture, MDPI, vol. 11(10), pages 1-20, September.

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