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Characterizing root-water-uptake of wheat under elevated CO2 concentration

Author

Listed:
  • Fan, Jinjie
  • Wu, Xun
  • Yu, Yangliu
  • Zuo, Qiang
  • Shi, Jianchu
  • Halpern, Moshe
  • Sheng, Jiandong
  • Jiang, Pingan
  • Ben-Gal, Alon

Abstract

Delineating root-water-uptake (RWU) under conditions with augmented CO2 concentrations is very important for scheduling irrigation to contend with climate change. Responses of plant growth to elevated CO2 concentration (e[CO2]) have been widely reported, while the effects of e[CO2] on RWU has hardly been studied. A hydroponic experiment of wheat (Triticum aestivum L.) with five NO3−-N concentrations (Exp. 1) was conducted to investigate and quantify the effects of e[CO2] on RWU activity. Another experiment growing wheat in soil columns with four combinations of water and N supply levels (Exp. 2) was conducted to validate the results obtained in Exp. 1, establishing a macroscopic RWU model to simulate soil water dynamics under e[CO2]. Although CO2 acclimation was observed in both experiments, plant canopy and root growth were generally stimulated under e[CO2], while transpiration consumption was not synchronously enhanced due to decreased stomatal conductance, indicating an increase in water use efficiency while a decrease in RWU activity. Potential transpiration was found more linearly related to root nitrogen mass (RNM) than root length under various CO2 concentrations, regardless of wheat growth stage, water and N supply level. Consequently, RNM density was used to drive the RWU model. The results from Exp. 1 indicated that the effects of e[CO2] on water uptake coefficient per RNM could be quantified by a recently proposed nonlinear stomatal conductance response model (R2 = 0.84, RMSE = 0.55 cm3 mg−1 d−1). The RWU model reliably simulated the dynamics of soil water transport and wheat transpiration under e[CO2] in Exp. 2 with the RMSE and relative errors mostly less than 0.03 cm3 cm−3 and 10 %, respectively. Practical application of the established RWU model for any other specific conditions is expected to benefit from optimization of parameters following choice of most appropriate stomatal conductance response model.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:agiwat:v:275:y:2023:i:c:s0378377422005522
    DOI: 10.1016/j.agwat.2022.108005
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    References listed on IDEAS

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    1. 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).
    2. Homaee, M. & Dirksen, C. & Feddes, R. A., 2002. "Simulation of root water uptake: I. Non-uniform transient salinity using different macroscopic reduction functions," Agricultural Water Management, Elsevier, vol. 57(2), pages 89-109, October.
    3. Homaee, M. & Feddes, R. A. & Dirksen, C., 2002. "Simulation of root water uptake: II. Non-uniform transient water stress using different reduction functions," Agricultural Water Management, Elsevier, vol. 57(2), pages 111-126, October.
    4. Li, Fusheng & Kang, Shaozhong & Zhang, Jianhua, 2004. "Interactive effects of elevated CO2, nitrogen and drought on leaf area, stomatal conductance, and evapotranspiration of wheat," Agricultural Water Management, Elsevier, vol. 67(3), pages 221-233, July.
    5. Wang, Lichun & Shi, Jianchu & Zuo, Qiang & Zheng, Wenjuan & Zhu, Xiangming, 2012. "Optimizing parameters of salinity stress reduction function using the relationship between root-water-uptake and root nitrogen mass of winter wheat," Agricultural Water Management, Elsevier, vol. 104(C), pages 142-152.
    6. Shi, Jianchu & Wu, Xun & Zhang, Mo & Wang, Xiaoyu & Zuo, Qiang & Wu, Xiaoguang & Zhang, Hongfei & Ben-Gal, Alon, 2021. "Numerically scheduling plant water deficit index-based smart irrigation to optimize crop yield and water use efficiency," Agricultural Water Management, Elsevier, vol. 248(C).
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