IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v269y2022ics0378377422002189.html
   My bibliography  Save this article

Estimation of turbulent fluxes over almond orchards using high-resolution aerial imagery with one and two-source energy balance models

Author

Listed:
  • Peddinti, Srinivasa Rao
  • Kisekka, Isaya

Abstract

Estimation of actual crop evapotranspiration (ETc) using high-resolution aerial remote sensing data is important to detect water stress, map, and manage water resources in precision agriculture. High-resolution ETc can be estimated using land surface energy balance models and remotely sensed land surface temperatures (LST) obtained using manned or unmanned aerial vehicles equipped with thermal cameras. In this study, three remote sensing ETc models were compared, i.e., Two-Source Energy Balance (TSEB) model, Mapping Evapotranspiration with Internalized Calibration (METRIC), and Surface Energy Balance Algorithm for Land (SEBAL) models. Thermal images were obtained using an airplane flying daily over almond orchards in California during the 2020 growing season. The LST images were obtained at 0.5 m spatial resolution. Model comparisons indicated that all three models produced latent heat fluxes and net radiation estimates that agreed with eddy covariance measurements in the order of TSEB (R2 of 0.89 for LE and 0.88 for Rn), METRIC (R2 of 0.81 for LE and 0.86 for Rn), and SEBAL (R2 of 0.81 for LE and 0.83 for Rn). However, METRIC and SEBAL overestimated the latent heat fluxes while underestimating the sensible heat fluxes as compared to the two-source model (TSEB). The root mean square error (RMSE) of the instantaneous latent and sensible heat fluxes were less than 38 W m−2 for TSEB, and were within 58 W m−2 for METRIC and SEBAL models. The TSEB model’s good performance can be attributed to its partitioning of surface temperature between soil, crop cover in the inter rows, and almond tree canopies. Overall, the results suggest that both one and two-source surface energy models originally developed for satellite imagery are able to estimate instantaneous turbulent fluxes and spatial variability in ETc using high-resolution imagery. In addition, systematic variations in LST due to variable rate irrigation scheduling as depicted in the high spatial resolution imagery provided confidence in the spatially distributed latent heat flux maps estimated by the energy balance models. This study shows that high-resolution aerial imagery combined with energy balance models originally developed for satellite remote sensing can be used to accurately estimate site specific ETc that is critical to achieving precision irrigation management in almond orchards and other crops.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:agiwat:v:269:y:2022:i:c:s0378377422002189
    DOI: 10.1016/j.agwat.2022.107671
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377422002189
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2022.107671?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. Peddinti, Srinivasa Rao & Kambhammettu, BVN P, 2019. "Dynamics of crop coefficients for citrus orchards of central India using water balance and eddy covariance flux partition techniques," Agricultural Water Management, Elsevier, vol. 212(C), pages 68-77.
    2. Xue, Jingyuan & Bali, Khaled M. & Light, Sarah & Hessels, Tim & Kisekka, Isaya, 2020. "Evaluation of remote sensing-based evapotranspiration models against surface renewal in almonds, tomatoes and maize," Agricultural Water Management, Elsevier, vol. 238(C).
    3. 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.
    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. Ferreira, Thomás R. & Maguire, Mitchell S. & da Silva, Bernardo B. & Neale, Christopher M.U. & Serrão, Edivaldo A.O. & Ferreira, Jéssica D. & de Moura, Magna S.B. & dos Santos, Carlos A.C. & Silva, Ma, 2023. "Assessment of water demands for irrigation using energy balance and satellite data fusion models in cloud computing: A study in the Brazilian semiarid region," Agricultural Water Management, Elsevier, vol. 281(C).
    2. Vanella, Daniela & Peddinti, Srinivasa Rao & Kisekka, Isaya, 2022. "Unravelling soil water dynamics in almond orchards characterized by soil-heterogeneity using electrical resistivity tomography," Agricultural Water Management, Elsevier, vol. 269(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. Elfarkh, Jamal & Simonneaux, Vincent & Jarlan, Lionel & Ezzahar, Jamal & Boulet, Gilles & Chakir, Adnane & Er-Raki, Salah, 2022. "Evapotranspiration estimates in a traditional irrigated area in semi-arid Mediterranean. Comparison of four remote sensing-based models," Agricultural Water Management, Elsevier, vol. 270(C).
    2. Jafari, Mohammad & Kamali, Hamidreza & Keshavarz, Ali & Momeni, Akbar, 2021. "Estimation of evapotranspiration and crop coefficient of drip-irrigated orange trees under a semi-arid climate," Agricultural Water Management, Elsevier, vol. 248(C).
    3. 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).
    4. Xue, Jingyuan & Fulton, Allan & Kisekka, Isaya, 2021. "Evaluating the role of remote sensing-based energy balance models in improving site-specific irrigation management for young walnut orchards," Agricultural Water Management, Elsevier, vol. 256(C).
    5. Liu, Meihan & Shi, Haibin & Paredes, Paula & Ramos, Tiago B. & Dai, Liping & Feng, Zhuangzhuang & Pereira, Luis S., 2022. "Estimating and partitioning maize evapotranspiration as affected by salinity using weighing lysimeters and the SIMDualKc model," Agricultural Water Management, Elsevier, vol. 261(C).
    6. 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).
    7. Longo-Minnolo, G. & Vanella, D. & Consoli, S. & Intrigliolo, D.S. & Ramírez-Cuesta, J.M., 2020. "Integrating forecast meteorological data into the ArcDualKc model for estimating spatially distributed evapotranspiration rates of a citrus orchard," Agricultural Water Management, Elsevier, vol. 231(C).
    8. Amazirh, Abdelhakim & Merlin, Olivier & Er-Raki, Salah & Bouras, Elhoussaine & Chehbouni, Abdelghani, 2021. "Implementing a new texture-based soil evaporation reduction coefficient in the FAO dual crop coefficient method," Agricultural Water Management, Elsevier, vol. 250(C).
    9. Jamshidi, Sajad & Zand-Parsa, Shahrokh & Kamgar-Haghighi, Ali Akbar & Shahsavar, Ali Reza & Niyogi, Dev, 2020. "Evapotranspiration, crop coefficients, and physiological responses of citrus trees in semi-arid climatic conditions," Agricultural Water Management, Elsevier, vol. 227(C).
    10. Sara, Ourrai & Bouchra, Aithssaine & Abdelhakim, Amazirh & Salah, Er-RAKI & Lhoussaine, Bouchaou & Frederic, Jacob & Abdelghani, Chehbouni, 2024. "Assessment of the modified two-source energy balance (TSEB) model for estimating evapotranspiration and its components over an irrigated olive orchard in Morocco," Agricultural Water Management, Elsevier, vol. 298(C).
    11. Abou Ali, Asma & Bouchaou, Lhoussaine & Er-Raki, Salah & Hssaissoune, Mohammed & Brouziyne, Youssef & Ezzahar, Jamal & Khabba, Saïd & Chakir, Adnane & Labbaci, Adnane & Chehbouni, Abdelghani, 2023. "Assessment of crop evapotranspiration and deep percolation in a commercial irrigated citrus orchard under semi-arid climate: Combined Eddy-Covariance measurement and soil water balance-based approach," Agricultural Water Management, Elsevier, vol. 275(C).
    12. Ouaadi, Nadia & Jarlan, Lionel & Khabba, Saïd & Le Page, Michel & Chakir, Adnane & Er-Raki, Salah & Frison, Pierre-Louis, 2023. "Are the C-band backscattering coefficient and interferometric coherence suitable substitutes of NDVI for the monitoring of the FAO-56 crop coefficient?," Agricultural Water Management, Elsevier, vol. 282(C).
    13. 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).
    14. Xiao, Jing & Sun, Fubao & Wang, Tingting & Wang, Hong, 2024. "Estimation and validation of high-resolution evapotranspiration products for an arid river basin using multi-source remote sensing data," Agricultural Water Management, Elsevier, vol. 298(C).
    15. Said A. Hamido & Kelly T. Morgan, 2021. "The Effect of Irrigation Rate on the Water Relations of Young Citrus Trees in High-Density Planting," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    16. Fu, Chong & Song, Xiaoyu & Li, Lanjun & Zhao, Xinkai & Meng, Pengfei & Wang, Long & Wei, Wanyin & Yang, Nan & Li, Huaiyou, 2023. "Combining the Generalized Complementary Relationship and the Modified Priestley-Taylor Equation to estimate and partition the evapotranspiration of typical plantations and grasslands in the Loess Plat," Agricultural Water Management, Elsevier, vol. 287(C).
    17. Hui Cao & Hongbo Wang & Yong Li & Abdoul Kader Mounkaila Hamani & Nan Zhang & Xingpeng Wang & Yang Gao, 2021. "Evapotranspiration Partition and Dual Crop Coefficients in Apple Orchard with Dwarf Stocks and Dense Planting in Arid Region, Aksu Oasis, Southern Xinjiang," Agriculture, MDPI, vol. 11(11), pages 1-16, November.
    18. He, Ruyan & Jin, Yufang & Jiang, Jinbao & Xu, Meng & Jia, Sen, 2022. "Sensitivity of METRIC-based tree crop evapotranspiration estimation to meteorology, land surface parameters and domain size," Agricultural Water Management, Elsevier, vol. 271(C).
    19. Ramos, Tiago B. & Darouich, Hanaa & Oliveira, Ana R. & Farzamian, Mohammad & Monteiro, Tomás & Castanheira, Nádia & Paz, Ana & Gonçalves, Maria C. & Pereira, Luís S., 2023. "Water use and soil water balance of Mediterranean tree crops assessed with the SIMDualKc model in orchards of southern Portugal," Agricultural Water Management, Elsevier, vol. 279(C).
    20. Kaneko, Teruko & Gould, Nick & Campbell, David & Snelgar, Patrick & Clearwater, Michael J., 2022. "The effect of soil type, fruit load and shaded area on ‘Hass’ avocado (Persea americana Mill.) water use and crop coefficients," Agricultural Water Management, Elsevier, vol. 264(C).

    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:269:y:2022:i:c:s0378377422002189. 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.