IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v274y2022ics0378377422005194.html
   My bibliography  Save this article

Two source energy balance maize evapotranspiration estimates using close-canopy mobile infrared sensors and upscaling methods under variable water stress conditions

Author

Listed:
  • Katimbo, Abia
  • Rudnick, Daran R.
  • Liang, Wei-zhen
  • DeJonge, Kendall C.
  • Lo, Tsz Him
  • Franz, Trenton E.
  • Ge, Yufeng
  • Qiao, Xin
  • Kabenge, Isa
  • Nakabuye, Hope Njuki
  • Duan, Jiaming

Abstract

Mobile infrared thermometers (IRTs) mounted on moving platforms provide one-time-of-day radiometric measurements (Tr), which can be used to calculate instantaneous actual evapotranspiration (ETa) using the two-source energy balance (TSEB) model. However, irrigation scheduling decisions utilize daily ETa estimates, hence the need for time scaling. This study evaluated different upscaling methods to calculate daily maize ETa using one-time-of day Tr under varying water stress conditions. Mobile IRTs were mounted on a high clearance mobile sensing platform and collected Tr in remote locations under full, deficit and rainfed conditions. Seven scaling methods via two pathways were employed to obtain daily ETa. First pathway was scaling one-time-of-day Tr (SC) whereas the second pathway involved use of six upscaling methods of instantaneous ETa including: original and modified evaporative factor ((EF)o, (EF)m) as well as crop coefficient ((Kc)o, (Kc)m), direct canopy resistance (Direct- rc), and solar radiation ratio (Rn/Rs); and all were compared to a neutron-based soil water balance (SWB) determined ETa. From the results, SC outperformed other methods in comparison to SWB ETa across all the selected treatments with smaller discrepancies and lower RMSE (0.9–1.7 mm d−1 vs. 0.7–4.3 mm d−1 for other methods). Furthermore, methods including SC, (EF)o, (EF)m, and Rn/Rs had their daily average ETa values in close agreement to SWB ETa with mean ETa differences ranging between 0.2 and 1.6 mm d−1. Overall, SC method performed better in fully irrigated maize (r2 = 0.52, RMSE = 0.9 mm d−1) than in deficit irrigated maize ( r2 = 0.48, RMSE = 1.4 mm d−1) but worst in rainfed maize (r2 = 0.16, RMSE = 1.7 mm d−1). This implies that SC is more suited for irrigated rather than rainfed settings. Importantly, the choice of any method depends on data requirements, irrigation water management strategy, and ETa estimation accuracy.

Suggested Citation

  • Katimbo, Abia & Rudnick, Daran R. & Liang, Wei-zhen & DeJonge, Kendall C. & Lo, Tsz Him & Franz, Trenton E. & Ge, Yufeng & Qiao, Xin & Kabenge, Isa & Nakabuye, Hope Njuki & Duan, Jiaming, 2022. "Two source energy balance maize evapotranspiration estimates using close-canopy mobile infrared sensors and upscaling methods under variable water stress conditions," Agricultural Water Management, Elsevier, vol. 274(C).
  • Handle: RePEc:eee:agiwat:v:274:y:2022:i:c:s0378377422005194
    DOI: 10.1016/j.agwat.2022.107972
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377422005194
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2022.107972?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. O’Shaughnessy, Susan A. & Evett, Steven R. & Colaizzi, Paul D., 2015. "Dynamic prescription maps for site-specific variable rate irrigation of cotton," Agricultural Water Management, Elsevier, vol. 159(C), pages 123-138.
    2. Payero, J.O. & Tarkalson, D.D. & Irmak, S. & Davison, D. & Petersen, J.L., 2009. "Effect of timing of a deficit-irrigation allocation on corn evapotranspiration, yield, water use efficiency and dry mass," Agricultural Water Management, Elsevier, vol. 96(10), pages 1387-1397, October.
    3. Rudnick, D.R. & Irmak, S. & Djaman, K. & Sharma, V., 2017. "Impact of irrigation and nitrogen fertilizer rate on soil water trends and maize evapotranspiration during the vegetative and reproductive periods," Agricultural Water Management, Elsevier, vol. 191(C), pages 77-84.
    4. Diarra, A. & Jarlan, L. & Er-Raki, S. & Le Page, M. & Aouade, G. & Tavernier, A. & Boulet, G. & Ezzahar, J. & Merlin, O. & Khabba, S., 2017. "Performance of the two-source energy budget (TSEB) model for the monitoring of evapotranspiration over irrigated annual crops in North Africa," Agricultural Water Management, Elsevier, vol. 193(C), pages 71-88.
    5. Han, Ming & Zhang, Huihui & DeJonge, Kendall C. & Comas, Louise H. & Gleason, Sean, 2018. "Comparison of three crop water stress index models with sap flow measurements in maize," Agricultural Water Management, Elsevier, vol. 203(C), pages 366-375.
    6. 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).
    7. Yan, Haofang & Li, Mi & Zhang, Chuan & Zhang, Jianyun & Wang, Guoqing & Yu, Jianjun & Ma, Jiamin & Zhao, Shuang, 2022. "Comparison of evapotranspiration upscaling methods from instantaneous to daytime scale for tea and wheat in southeast China," Agricultural Water Management, Elsevier, vol. 264(C).
    8. Colaizzi, Paul D. & O’Shaughnessy, Susan A. & Evett, Steve R. & Mounce, Ryan B., 2017. "Crop evapotranspiration calculation using infrared thermometers aboard center pivots," Agricultural Water Management, Elsevier, vol. 187(C), pages 173-189.
    9. O’Shaughnessy, Susan A. & Kim, Minyoung & Andrade, Manuel A. & Colaizzi, Paul D. & Evett, Steven R., 2020. "Site-specific irrigation of grain sorghum using plant and soil water sensing feedback - Texas High Plains," Agricultural Water Management, Elsevier, vol. 240(C).
    10. 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.
    11. Kullberg, Emily G. & DeJonge, Kendall C. & Chávez, José L., 2017. "Evaluation of thermal remote sensing indices to estimate crop evapotranspiration coefficients," Agricultural Water Management, Elsevier, vol. 179(C), pages 64-73.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Feng, Jiaojiao & Wang, Weizhen & Che, Tao & Xu, Feinan, 2023. "Performance of the improved two-source energy balance model for estimating evapotranspiration over the heterogeneous surface," Agricultural Water Management, Elsevier, vol. 278(C).

    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. 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).
    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. 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).
    4. Zhang, Liyuan & Zhang, Huihui & Zhu, Qingzhen & Niu, Yaxiao, 2023. "Further investigating the performance of crop water stress index for maize from baseline fluctuation, effects of environmental factors, and variation of critical value," Agricultural Water Management, Elsevier, vol. 285(C).
    5. Zhang, Liyuan & Zhang, Huihui & Han, Wenting & Niu, Yaxiao & Chávez, José L. & Ma, Weitong, 2021. "The mean value of gaussian distribution of excess green index: A new crop water stress indicator," Agricultural Water Management, Elsevier, vol. 251(C).
    6. Shao, Guomin & Han, Wenting & Zhang, Huihui & Zhang, Liyuan & Wang, Yi & Zhang, Yu, 2023. "Prediction of maize crop coefficient from UAV multisensor remote sensing using machine learning methods," Agricultural Water Management, Elsevier, vol. 276(C).
    7. Ezenne, G.I. & Jupp, Louise & Mantel, S.K. & Tanner, J.L., 2019. "Current and potential capabilities of UAS for crop water productivity in precision agriculture," Agricultural Water Management, Elsevier, vol. 218(C), pages 158-164.
    8. Zhang, Liyuan & Zhang, Huihui & Han, Wenting & Niu, Yaxiao & Chávez, José L. & Ma, Weitong, 2022. "Effects of image spatial resolution and statistical scale on water stress estimation performance of MGDEXG: A new crop water stress indicator derived from RGB images," Agricultural Water Management, Elsevier, vol. 264(C).
    9. Bretreger, David & Yeo, In-Young & Hancock, Greg, 2022. "Quantifying irrigation water use with remote sensing: Soil water deficit modelling with uncertain soil parameters," Agricultural Water Management, Elsevier, vol. 260(C).
    10. Fan, Yubing & Himanshu, Sushil K. & Ale, Srinivasulu & DeLaune, Paul B. & Zhang, Tian & Park, Seong C. & Colaizzi, Paul D. & Evett, Steven R. & Baumhardt, R. Louis, 2022. "The synergy between water conservation and economic profitability of adopting alternative irrigation systems for cotton production in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 262(C).
    11. Zhang, Yu & Han, Wenting & Zhang, Huihui & Niu, Xiaotao & Shao, Guomin, 2023. "Evaluating maize evapotranspiration using high-resolution UAV-based imagery and FAO-56 dual crop coefficient approach," Agricultural Water Management, Elsevier, vol. 275(C).
    12. Anzhen Qin & Dongfeng Ning & Zhandong Liu & Sen Li & Ben Zhao & Aiwang Duan, 2021. "Determining Threshold Values for a Crop Water Stress Index-Based Center Pivot Irrigation with Optimum Grain Yield," Agriculture, MDPI, vol. 11(10), pages 1-16, October.
    13. Amazirh, Abdelhakim & Er-Raki, Salah & Ojha, Nitu & Bouras, El houssaine & Rivalland, Vincent & Merlin, Olivier & Chehbouni, Abdelghani, 2022. "Assimilation of SMAP disaggregated soil moisture and Landsat land surface temperature to improve FAO-56 estimates of ET in semi-arid regions," Agricultural Water Management, Elsevier, vol. 260(C).
    14. Ekinzog, Elmer Kanjo & Schlerf, Martin & Kraft, Martin & Werner, Florian & Riedel, Angela & Rock, Gilles & Mallick, Kaniska, 2022. "Revisiting crop water stress index based on potato field experiments in Northern Germany," Agricultural Water Management, Elsevier, vol. 269(C).
    15. Cheng, Minghan & Sun, Chengming & Nie, Chenwei & Liu, Shuaibing & Yu, Xun & Bai, Yi & Liu, Yadong & Meng, Lin & Jia, Xiao & Liu, Yuan & Zhou, Lili & Nan, Fei & Cui, Tengyu & Jin, Xiuliang, 2023. "Evaluation of UAV-based drought indices for crop water conditions monitoring: A case study of summer maize," Agricultural Water Management, Elsevier, vol. 287(C).
    16. Olivera-Guerra, Luis & Merlin, Olivier & Er-Raki, Salah & Khabba, Saïd & Escorihuela, Maria Jose, 2018. "Estimating the water budget components of irrigated crops: Combining the FAO-56 dual crop coefficient with surface temperature and vegetation index data," Agricultural Water Management, Elsevier, vol. 208(C), pages 120-131.
    17. Allakonon, M. Gloriose B. & Zakari, Sissou & Tovihoudji, Pierre G. & Fatondji, A. Sènami & Akponikpè, P.B. Irénikatché, 2022. "Grain yield, actual evapotranspiration and water productivity responses of maize crop to deficit irrigation: A global meta-analysis," Agricultural Water Management, Elsevier, vol. 270(C).
    18. Peddinti, Srinivasa Rao & Kisekka, Isaya, 2022. "Estimation of turbulent fluxes over almond orchards using high-resolution aerial imagery with one and two-source energy balance models," Agricultural Water Management, Elsevier, vol. 269(C).
    19. El-Naggar, A.G. & Hedley, C.B. & Horne, D. & Roudier, P. & Clothier, B.E., 2020. "Soil sensing technology improves application of irrigation water," Agricultural Water Management, Elsevier, vol. 228(C).
    20. Marek, Gary & Gowda, Prasanna & Marek, Thomas & Auvermann, Brent & Evett, Steven & Colaizzi, Paul & Brauer, David, 2016. "Estimating preseason irrigation losses by characterizing evaporation of effective precipitation under bare soil conditions using large weighing lysimeters," Agricultural Water Management, Elsevier, vol. 169(C), pages 115-128.

    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:eee:agiwat:v:274:y:2022:i:c:s0378377422005194. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    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.