IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v288y2023ics037837742300327x.html
   My bibliography  Save this article

Water uptake rates over olive orchards using Sentinel-1 synthetic aperture radar data

Author

Listed:
  • El Hajj, Marcel M.
  • Johansen, Kasper
  • Almashharawi, Samer K.
  • McCabe, Matthew F.

Abstract

The water uptake rate is a key parameter for improving irrigation efficiency and represents an indicator of tree health and yield. Here, we investigate the potential of C-band Synthetic Aperture Radar (SAR) data acquired by Sentinel-1 to estimate and map the water uptake rate across a very high-density olive orchard (5.3 km2 of olive plots) in the hot and arid desert climate of Saudi Arabia. The SAR predictor variables for water uptake rate estimation were the difference between the SAR backscattering of a given image acquired during the year (ti) and the average SAR backscattering in the second-half of January (t0), which corresponds to the point when the uptake rate was closest to zero. Random forest regression and multi-linear regression models were used to explore the relationship between the SAR predictor variables and in situ water uptake rate, inferred from twelve sap flow meters that were installed across six plots and collected over two years (2020 and 2021). The trained random forest regression model provided an improved estimate of water uptake rate with correlation coefficient (R2) of 0.87 and root mean square error (RMSE) of 0.13 L.h−1 compared with the multi-linear regression model (R2 = 0.74, RMSE = 0.18 L.h−1). Using the random forest regression, the water uptake rate was mapped at the plot level for three years (2019, 2020, and 2021) at a temporal resolution of 6 days. Consistent with expectations, the results show that the average uptake rate over the mapped area co-varied with vapor pressure deficit (R2 = 0.82). The analysis provides a first exploration of exploiting SAR data to infer the water uptake rate across commercial scale orchards, offering important insights that can be useful for improved water management and irrigation control.

Suggested Citation

  • El Hajj, Marcel M. & Johansen, Kasper & Almashharawi, Samer K. & McCabe, Matthew F., 2023. "Water uptake rates over olive orchards using Sentinel-1 synthetic aperture radar data," Agricultural Water Management, Elsevier, vol. 288(C).
    • Handle: RePEc:eee:agiwat:v:288:y:2023:i:c:s037837742300327x
    DOI: 10.1016/j.agwat.2023.108462
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037837742300327X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2023.108462?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. González-Dugo, M.P. & Escuin, S. & Cano, F. & Cifuentes, V. & Padilla, F.L.M. & Tirado, J.L. & Oyonarte, N. & Fernández, P. & Mateos, L., 2013. "Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. II. Application on basin scale," Agricultural Water Management, Elsevier, vol. 125(C), pages 92-104.
    2. C. Cammalleri & G. Ciraolo & M. Minacapilli & G. Rallo, 2013. "Evapotranspiration from an Olive Orchard using Remote Sensing-Based Dual Crop Coefficient Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(14), pages 4877-4895, November.
    3. Rousseaux, M. Cecilia & Figuerola, Patricia I. & Correa-Tedesco, Guillermo & Searles, Peter S., 2009. "Seasonal variations in sap flow and soil evaporation in an olive (Olea europaea L.) grove under two irrigation regimes in an arid region of Argentina," Agricultural Water Management, Elsevier, vol. 96(6), pages 1037-1044, June.
    4. Mateos, L. & González-Dugo, M.P. & Testi, L. & Villalobos, F.J., 2013. "Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. I. Method validation," Agricultural Water Management, Elsevier, vol. 125(C), pages 81-91.
    5. 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).
    6. Er-Raki, S. & Chehbouni, A. & Hoedjes, J. & Ezzahar, J. & Duchemin, B. & Jacob, F., 2008. "Improvement of FAO-56 method for olive orchards through sequential assimilation of thermal infrared-based estimates of ET," Agricultural Water Management, Elsevier, vol. 95(3), pages 309-321, March.
    7. Nicolas, E. & Torrecillas, A. & Ortuno, M.F. & Domingo, R. & Alarcon, J.J., 2005. "Evaluation of transpiration in adult apricot trees from sap flow measurements," Agricultural Water Management, Elsevier, vol. 72(2), pages 131-145, March.
    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. Rouault, Pierre & Courault, Dominique & Flamain, Fabrice & Pouget, Guillaume & Doussan, Claude & Lopez-Lozano, Raul & McCabe, Matthew & Debolini, Marta, 2024. "High-resolution satellite imagery to assess orchard characteristics impacting water use," Agricultural Water Management, Elsevier, vol. 295(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. Pôças, I. & Calera, A. & Campos, I. & Cunha, M., 2020. "Remote sensing for estimating and mapping single and basal crop coefficientes: A review on spectral vegetation indices approaches," Agricultural Water Management, Elsevier, vol. 233(C).
    2. Mokhtari, Ali & Noory, Hamideh & Vazifedoust, Majid & Bahrami, Mahdi, 2018. "Estimating net irrigation requirement of winter wheat using model- and satellite-based single and basal crop coefficients," Agricultural Water Management, Elsevier, vol. 208(C), pages 95-106.
    3. Jovanovic, N. & Pereira, L.S. & Paredes, P. & Pôças, I. & Cantore, V. & Todorovic, M., 2020. "A review of strategies, methods and technologies to reduce non-beneficial consumptive water use on farms considering the FAO56 methods," Agricultural Water Management, Elsevier, vol. 239(C).
    4. Wang, Tianxin & Melton, Forrest S. & Pôças, Isabel & Johnson, Lee F. & Thao, Touyee & Post, Kirk & Cassel-Sharma, Florence, 2021. "Evaluation of crop coefficient and evapotranspiration data for sugar beets from landsat surface reflectances using micrometeorological measurements and weighing lysimetry," Agricultural Water Management, Elsevier, vol. 244(C).
    5. Luis Santos Pereira, 2017. "Water, Agriculture and Food: Challenges and Issues," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 2985-2999, August.
    6. Mokhtari, Ali & Noory, Hamideh & Vazifedoust, Majid & Palouj, Mojtaba & Bakhtiari, Atousa & Barikani, Elham & Zabihi Afrooz, Ramezan Ali & Fereydooni, Fatemeh & Sadeghi Naeni, Ali & Pourshakouri, Farr, 2019. "Evaluation of single crop coefficient curves derived from Landsat satellite images for major crops in Iran," Agricultural Water Management, Elsevier, vol. 218(C), pages 234-249.
    7. Campos, Isidro & Balbontín, Claudio & González-Piqueras, Jose & González-Dugo, Maria P. & Neale, Christopher M.U. & Calera, Alfonso, 2016. "Combining a water balance model with evapotranspiration measurements to estimate total available soil water in irrigated and rainfed vineyards," Agricultural Water Management, Elsevier, vol. 165(C), pages 141-152.
    8. Salgado, Ramiro & Mateos, Luciano, 2021. "Evaluation of different methods of estimating ET for the performance assessment of irrigation schemes," Agricultural Water Management, Elsevier, vol. 243(C).
    9. Mahmoud, Shereif H. & Gan, Thian Yew, 2019. "Irrigation water management in arid regions of Middle East: Assessing spatio-temporal variation of actual evapotranspiration through remote sensing techniques and meteorological data," Agricultural Water Management, Elsevier, vol. 212(C), pages 35-47.
    10. Teixeira, Antônio & Leivas, Janice & Struiving, Tiago & Reis, João & Simão, Fúlvio, 2021. "Energy balance and irrigation performance assessments in lemon orchards by applying the SAFER algorithm to Landsat 8 images," Agricultural Water Management, Elsevier, vol. 247(C).
    11. 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).
    12. Yousaf, Wasif & Awan, Wakas Karim & Kamran, Muhammad & Ahmad, Sajid Rashid & Bodla, Habib Ullah & Riaz, Mohammad & Umar, Muhammad & Chohan, Khurram, 2021. "A paradigm of GIS and remote sensing for crop water deficit assessment in near real time to improve irrigation distribution plan," Agricultural Water Management, Elsevier, vol. 243(C).
    13. Consoli, S. & Vanella, D., 2014. "Mapping crop evapotranspiration by integrating vegetation indices into a soil water balance model," Agricultural Water Management, Elsevier, vol. 143(C), pages 71-81.
    14. Carpintero, E. & Mateos, L. & Andreu, A. & González-Dugo, M.P., 2020. "Effect of the differences in spectral response of Mediterranean tree canopies on the estimation of evapotranspiration using vegetation index-based crop coefficients," Agricultural Water Management, Elsevier, vol. 238(C).
    15. Campos, Isidro & Neale, Christopher M.U. & Suyker, Andrew E. & Arkebauer, Timothy J. & Gonçalves, Ivo Z., 2017. "Reflectance-based crop coefficients REDUX: For operational evapotranspiration estimates in the age of high producing hybrid varieties," Agricultural Water Management, Elsevier, vol. 187(C), pages 140-153.
    16. Garrido-Rubio, Jesús & González-Piqueras, Jose & Campos, Isidro & Osann, Anna & González-Gómez, Laura & Calera, Alfonso, 2020. "Remote sensing–based soil water balance for irrigation water accounting at plot and water user association management scale," Agricultural Water Management, Elsevier, vol. 238(C).
    17. 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).
    18. Kaplan, Gregoriy & Fine, Lior & Lukyanov, Victor & Malachy, Nitzan & Tanny, Josef & Rozenstein, Offer, 2023. "Using Sentinel-1 and Sentinel-2 imagery for estimating cotton crop coefficient, height, and Leaf Area Index," Agricultural Water Management, Elsevier, vol. 276(C).
    19. Consoli, S. & Licciardello, F. & Vanella, D. & Pasotti, L. & Villani, G. & Tomei, F., 2016. "Testing the water balance model criteria using TDR measurements, micrometeorological data and satellite-based information," Agricultural Water Management, Elsevier, vol. 170(C), pages 68-80.
    20. Berbel, J. & Mateos, L., 2014. "Does investment in irrigation technology necessarily generate rebound effects? A simulation analysis based on an agro-economic model," Agricultural Systems, Elsevier, vol. 128(C), pages 25-34.

    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:288:y:2023:i:c:s037837742300327x. 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.