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Inter-relationships between water depletion and temperature differential in row crop canopies in a sub-humid climate

Author

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  • Singh, Jasreman
  • Ge, Yufeng
  • Heeren, Derek M.
  • Walter-Shea, Elizabeth
  • Neale, Christopher M.U.
  • Irmak, Suat
  • Woldt, Wayne E.
  • Bai, Geng
  • Bhatti, Sandeep
  • Maguire, Mitchell S.

Abstract

Irrigation has a great impact on global food security as it contributes to the majority of the world’s agricultural food supply. It is essential to judiciously utilize water resources through efficient irrigation management since the majority of U.S. groundwater aquifers are rapidly depleting. Thus, quantification of the relationships between water depletion and environmental factors is important for understanding crop response to varying levels of water stresses that depletion can cause. The objectives of this research were to: 1) investigate the relationship between root zone water depletion (Drw) and canopy temperature differential (ΔT) at different ranges of Drw; and 2) develop upper (water stressed) and lower (non-water stressed) baselines for quantification of crop water stress index (CWSI) in a sub-humid climate. The research was conducted over maize and soybean during 2018, 2019, and 2020 growing seasons. Sensor node stations comprising of an infrared thermometer and three soil water sensors were installed at various sites over maize and soybean fields. ΔT tends to increase with the increase in Drw when the range of Drw includes values greater than 170 mm for maize and values greater than 160 mm for soybean. The results indicate that ΔT and Drw are unrelated until a soil-water depletion threshold is attained, and these Drw threshold values could be considered as indicators to trigger irrigation for efficient agricultural water management. To the best of the authors’ knowledge, the research is the first to develop upper and lower CWSI baselines for east-central Nebraska. The baselines developed in this study could facilitate the quantification of CWSI for irrigation scheduling of maize and soybean in east-Central Nebraska. Future work should aim to investigate the potential in using Drw and/or ΔT to determine efficient water allocation and if a threshold CWSI could be used for timing of irrigation to prevent yield loss.

Suggested Citation

  • Singh, Jasreman & Ge, Yufeng & Heeren, Derek M. & Walter-Shea, Elizabeth & Neale, Christopher M.U. & Irmak, Suat & Woldt, Wayne E. & Bai, Geng & Bhatti, Sandeep & Maguire, Mitchell S., 2021. "Inter-relationships between water depletion and temperature differential in row crop canopies in a sub-humid climate," Agricultural Water Management, Elsevier, vol. 256(C).
  • Handle: RePEc:eee:agiwat:v:256:y:2021:i:c:s0378377421003267
    DOI: 10.1016/j.agwat.2021.107061
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    1. Tubaileh, Azzam. S. & Sammis, Theodore W. & Lugg, David G., 1986. "Utilization of thermal infrared thermometry for detection of water stress in spring barley," Agricultural Water Management, Elsevier, vol. 12(1-2), pages 75-85, October.
    2. Bhatti, Sandeep & Heeren, Derek M. & Barker, J. Burdette & Neale, Christopher M.U. & Woldt, Wayne E. & Maguire, Mitchell S. & Rudnick, Daran R., 2020. "Site-specific irrigation management in a sub-humid climate using a spatial evapotranspiration model with satellite and airborne imagery," Agricultural Water Management, Elsevier, vol. 230(C).
    3. Singh, J. & Lo, T. & Rudnick, D.R. & Dorr, T.J. & Burr, C.A. & Werle, R. & Shaver, T.M. & Muñoz-Arriola, F., 2018. "Performance assessment of factory and field calibrations for electromagnetic sensors in a loam soil," Agricultural Water Management, Elsevier, vol. 196(C), pages 87-98.
    4. Geerts, Sam & Raes, Dirk, 2009. "Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas," Agricultural Water Management, Elsevier, vol. 96(9), pages 1275-1284, September.
    5. Hellerstein, Daniel & Vilorio, Dennis, 2019. "Agricultural Resources and Environmental Indicators, 2019," Economic Information Bulletin 288293, United States Department of Agriculture, Economic Research Service.
    6. Candogan, Burak Nazmi & Sincik, Mehmet & Buyukcangaz, Hakan & Demirtas, Cigdem & Goksoy, Abdurrahim Tanju & Yazgan, Senih, 2013. "Yield, quality and crop water stress index relationships for deficit-irrigated soybean [Glycine max (L.) Merr.] in sub-humid climatic conditions," Agricultural Water Management, Elsevier, vol. 118(C), pages 113-121.
    7. DeJonge, Kendall C. & Taghvaeian, Saleh & Trout, Thomas J. & Comas, Louise H., 2015. "Comparison of canopy temperature-based water stress indices for maize," Agricultural Water Management, Elsevier, vol. 156(C), pages 51-62.
    8. Varble, J.L. & Chávez, J.L., 2011. "Performance evaluation and calibration of soil water content and potential sensors for agricultural soils in eastern Colorado," Agricultural Water Management, Elsevier, vol. 101(1), pages 93-106.
    9. Barker, J. Burdette & Heeren, Derek M. & Neale, Christopher M.U. & Rudnick, Daran R., 2018. "Evaluation of variable rate irrigation using a remote-sensing-based model," Agricultural Water Management, Elsevier, vol. 203(C), pages 63-74.
    10. O'Shaughnessy, Susan A. & Evett, Steven R. & Colaizzi, Paul D. & Howell, Terry A., 2012. "A crop water stress index and time threshold for automatic irrigation scheduling of grain sorghum," Agricultural Water Management, Elsevier, vol. 107(C), pages 122-132.
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    Cited by:

    1. Bhatti, Sandeep & Heeren, Derek M. & Evett, Steven R. & O’Shaughnessy, Susan A. & Rudnick, Daran R. & Franz, Trenton E. & Ge, Yufeng & Neale, Christopher M.U., 2022. "Crop response to thermal stress without yield loss in irrigated maize and soybean in Nebraska," Agricultural Water Management, Elsevier, vol. 274(C).
    2. Katimbo, Abia & Rudnick, Daran R. & DeJonge, Kendall C. & Lo, Tsz Him & Qiao, Xin & Franz, Trenton E. & Nakabuye, Hope Njuki & Duan, Jiaming, 2022. "Crop water stress index computation approaches and their sensitivity to soil water dynamics," Agricultural Water Management, Elsevier, vol. 266(C).
    3. Nakabuye, Hope Njuki & Rudnick, Daran & DeJonge, Kendall C. & Lo, Tsz Him & Heeren, Derek & Qiao, Xin & Franz, Trenton E. & Katimbo, Abia & Duan, Jiaming, 2022. "Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment," Agricultural Water Management, Elsevier, vol. 274(C).

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