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Quantifying soybean evapotranspiration using an eddy covariance approach

Author

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  • Anapalli, Saseendran S.
  • Fisher, Daniel K.
  • Reddy, Krishna N.
  • Wagle, Pradeep
  • Gowda, Prasanna H.
  • Sui, Ruixiu

Abstract

Quantification of evapotranspiration (ETc) from crops is critical in irrigation scheduling in agriculture. In a pioneering study, in the Mississippi (MS) Delta region, we quantified ETc from soybean (Glycine max L.) using the eddy covariance (EC) approach (ETe). We also monitored ETc using a residual energy balance (EB) approach (ETb) and compared the fluxes. The unclosed energy fluxes in the EC were post-analysis closed using the Bowen ratio (BR) and latent heat (LH) methods. The measurements were conducted in a 35-ha clay soil planted to irrigated soybean in the lower MS Delta in 2016. The crop reached physiological maturity in 126 days after emergence (DAE). Maximum LAI was 5.7 and average grain yield was 4900 kg ha−1. The EC showed an energy balance closure of about 88% on a 30 min and 90% on a daily flux accumulation. The ETe was 18.2, 6.8, and 15.9% lower than ETb, and ETe corrected using BR (ETebr) and LH (ETele) approaches, respectively. Average soybean seasonal ETe, ETb, ETebr, and ETele were 422, 499, 451, and 490 mm, respectively. Seasonal reference-crop evapotranspiration for alfalfa (ETo) and grass (ETr) were 470 and 547 mm, respectively. Daily ETe, ETb, ETebr, ETele, ETo, and ETr averaged across the whole season were 4.4, 5.2, 4.7, 5.1, 4.9, and 5.7 mm, respectively. For scheduling irrigations, based on grass and alfalfa reference crop ET calculated from weather data, averages of the ETe, ETb, ETebr, and ETele daily estimates were used in deriving crop coefficients (Kc). The Kc for grass reference varied between 0.56 and 1.29 and for alfalfa reference varied between 0.56 and 1.02. The information developed will be useful for scheduling irrigations in the MS Delta region, and the methodology developed can be adapted for generating similar information elsewhere.

Suggested Citation

  • Anapalli, Saseendran S. & Fisher, Daniel K. & Reddy, Krishna N. & Wagle, Pradeep & Gowda, Prasanna H. & Sui, Ruixiu, 2018. "Quantifying soybean evapotranspiration using an eddy covariance approach," Agricultural Water Management, Elsevier, vol. 209(C), pages 228-239.
    • Handle: RePEc:eee:agiwat:v:209:y:2018:i:c:p:228-239
    DOI: 10.1016/j.agwat.2018.07.023
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    1. Uddin, J. & Hancock, N.H. & Smith, R.J. & Foley, J.P., 2013. "Measurement of evapotranspiration during sprinkler irrigation using a precision energy budget (Bowen ratio, eddy covariance) methodology," Agricultural Water Management, Elsevier, vol. 116(C), pages 89-100.
    2. Anapalli, Saseendran S. & Green, Timothy R. & Reddy, Krishna N. & Gowda, Prasanna H. & Sui, Ruixiu & Fisher, Daniel K. & Moorhead, Jerry E. & Marek, Gary W., 2018. "Application of an energy balance method for estimating evapotranspiration in cropping systems," Agricultural Water Management, Elsevier, vol. 204(C), pages 107-117.
    3. Payero, José O. & Irmak, Suat, 2013. "Daily energy fluxes, evapotranspiration and crop coefficient of soybean," Agricultural Water Management, Elsevier, vol. 129(C), pages 31-43.
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    2. Anapalli, Saseendran S. & Fisher, Daniel K. & Reddy, Krishna N. & Rajan, Nithya & Pinnamaneni, Srinivasa Rao, 2019. "Modeling evapotranspiration for irrigation water management in a humid climate," Agricultural Water Management, Elsevier, vol. 225(C).
    3. Anapalli, Saseendran S. & Pinnamaneni, Srinivasa R. & Reddy, Krishna N. & Sui, Ruixiu & Singh, Gurbir, 2022. "Investigating soybean (Glycine max L.) responses to irrigation on a large-scale farm in the humid climate of the Mississippi Delta region," Agricultural Water Management, Elsevier, vol. 262(C).
    4. Anapalli, Saseendran S. & Fisher, Daniel K. & Pinnamaneni, Srinivasa Rao & Reddy, Krishna N., 2020. "Quantifying evapotranspiration and crop coefficients for cotton (Gossypium hirsutum L.) using an eddy covariance approach," Agricultural Water Management, Elsevier, vol. 233(C).
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    6. Granata, Francesco, 2019. "Evapotranspiration evaluation models based on machine learning algorithms—A comparative study," Agricultural Water Management, Elsevier, vol. 217(C), pages 303-315.
    7. Granata, Francesco & Di Nunno, Fabio, 2021. "Forecasting evapotranspiration in different climates using ensembles of recurrent neural networks," Agricultural Water Management, Elsevier, vol. 255(C).
    8. Anapalli, Saseendran S. & Pinnamaneni, Srinivasa R. & Chastain, Daryl R. & Reddy, Krishna N. & Simmons, Clyde Douglas, 2023. "Eddy covariance quantification of carbon and water dynamics in twin-row vs. single-row planted corn," Agricultural Water Management, Elsevier, vol. 281(C).
    9. Machakaire, A.T.B. & Steyn, J.M. & Franke, A.C., 2021. "Assessing evapotranspiration and crop coefficients of potato in a semi-arid climate using Eddy Covariance techniques," Agricultural Water Management, Elsevier, vol. 255(C).

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