IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v260y2022ics0378377421005679.html
   My bibliography  Save this article

Assimilation of SMAP disaggregated soil moisture and Landsat land surface temperature to improve FAO-56 estimates of ET in semi-arid regions

Author

Listed:
  • Amazirh, Abdelhakim
  • Er-Raki, Salah
  • Ojha, Nitu
  • Bouras, El houssaine
  • Rivalland, Vincent
  • Merlin, Olivier
  • Chehbouni, Abdelghani

Abstract

Accurate estimation of evapotranspiration (ET) is of crucial importance in water science and hydrological process understanding especially in semi-arid/arid areas since ET represents more than 85% of the total water budget. FAO-56 is one of the widely used formulations to estimate the actual crop evapotranspiration (ETc act) due to its operational nature and since it represents a reasonable compromise between simplicity and accuracy. In this vein, the objective of this paper was to examine the possibility of improving ETc act estimates through remote sensing data assimilation. For this purpose, remotely sensed soil moisture (SM) and Land surface temperature (LST) data were simultaneously assimilated into FAO-dualKc. Surface SM observations were assimilated into the soil evaporation (Es) component through the soil evaporation coefficient, and LST data were assimilated into the actual crop transpiration (Tc act) component through the crop stress coefficient. The LST data were used to estimate the water stress coefficient (Ks) as a proxy of LST (LSTproxy). The FAO-Ks was corrected by assimilating LSTproxy derived from Landsat data based on the variances of predicted errors on Ks estimates from FAO-56 model and thermal-derived Ks. The proposed approach was tested over a semi-arid area in Morocco using first, in situ data collected during 2002–2003 and 2015–2016 wheat growth seasons over two different fields and then, remotely sensed data derived from disaggregated Soil Moisture Active Passive (SMAP) SM and Landsat-LST sensors were used. Assimilating SM data leads to an improvement of the ETc act model prediction: the root mean square error (RMSE) decreased from 0.98 to 0.65 mm/day compared to the classical FAO-dualKc using in situ SM. Moreover, assimilating both in situ SM and LST data provided more accurate results with a RMSE error of 0.55 mm/day. By using SMAP-based SM and Landsat-LST, results also improved in comparison with standard FAO and reached a RMSE of 0.73 mm/day against eddy-covariance ETc act measurements.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:agiwat:v:260:y:2022:i:c:s0378377421005679
    DOI: 10.1016/j.agwat.2021.107290
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377421005679
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2021.107290?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. French, Andrew N. & Hunsaker, Douglas J. & Sanchez, Charles A. & Saber, Mazin & Gonzalez, Juan Roberto & Anderson, Ray, 2020. "Satellite-based NDVI crop coefficients and evapotranspiration with eddy covariance validation for multiple durum wheat fields in the US Southwest," Agricultural Water Management, Elsevier, vol. 239(C).
    2. 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).
    3. Liu, Yujie & Luo, Yi, 2010. "A consolidated evaluation of the FAO-56 dual crop coefficient approach using the lysimeter data in the North China Plain," Agricultural Water Management, Elsevier, vol. 97(1), pages 31-40, January.
    4. 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.
    5. Alberto, Ma. Carmelita R. & Quilty, James R. & Buresh, Roland J. & Wassmann, Reiner & Haidar, Sam & Correa, Teodoro Q. & Sandro, Joseph M., 2014. "Actual evapotranspiration and dual crop coefficients for dry-seeded rice and hybrid maize grown with overhead sprinkler irrigation," Agricultural Water Management, Elsevier, vol. 136(C), pages 1-12.
    6. Molden, David & Oweis, Theib & Steduto, Pasquale & Bindraban, Prem & Hanjra, Munir A. & Kijne, Jacob, 2010. "Improving agricultural water productivity: Between optimism and caution," Agricultural Water Management, Elsevier, vol. 97(4), pages 528-535, April.
    7. Ko, Jonghan & Piccinni, Giovanni & Marek, Thomas & Howell, Terry, 2009. "Determination of growth-stage-specific crop coefficients (Kc) of cotton and wheat," Agricultural Water Management, Elsevier, vol. 96(12), pages 1691-1697, December.
    8. 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.
    9. Allen, Richard G. & Pereira, Luis S. & Howell, Terry A. & Jensen, Marvin E., 2011. "Evapotranspiration information reporting: I. Factors governing measurement accuracy," Agricultural Water Management, Elsevier, vol. 98(6), pages 899-920, April.
    10. Mohamed Kharrou & Michel Le Page & Ahmed Chehbouni & Vincent Simonneaux & Salah Er-Raki & Lionel Jarlan & Lahcen Ouzine & Said Khabba & Ghani Chehbouni, 2013. "Assessment of Equity and Adequacy of Water Delivery in Irrigation Systems Using Remote Sensing-Based Indicators in Semi-Arid Region, Morocco," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(13), pages 4697-4714, October.
    11. Walker, Elisabet & García, Gabriel A. & Venturini, Virginia & Carrasco, Aylen, 2019. "Regional evapotranspiration estimates using the relative soil moisture ratio derived from SMAP products," Agricultural Water Management, Elsevier, vol. 216(C), pages 254-263.
    12. Piccinni, Giovanni & Ko, Jonghan & Marek, Thomas & Howell, Terry, 2009. "Determination of growth-stage-specific crop coefficients (KC) of maize and sorghum," Agricultural Water Management, Elsevier, vol. 96(12), pages 1698-1704, December.
    13. Tasumi, Masahiro, 2019. "Estimating evapotranspiration using METRIC model and Landsat data for better understandings of regional hydrology in the western Urmia Lake Basin," Agricultural Water Management, Elsevier, vol. 226(C).
    14. Er-Raki, S. & Chehbouni, A. & Guemouria, N. & Duchemin, B. & Ezzahar, J. & Hadria, R., 2007. "Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region," Agricultural Water Management, Elsevier, vol. 87(1), pages 41-54, January.
    15. Pereira, L.S. & Paredes, P. & Jovanovic, N., 2020. "Soil water balance models for determining crop water and irrigation requirements and irrigation scheduling focusing on the FAO56 method and the dual Kc approach," Agricultural Water Management, Elsevier, vol. 241(C).
    16. Paredes, P. & Rodrigues, G.C. & Alves, I. & Pereira, L.S., 2014. "Partitioning evapotranspiration, yield prediction and economic returns of maize under various irrigation management strategies," Agricultural Water Management, Elsevier, vol. 135(C), pages 27-39.
    17. 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.
    18. 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.
    19. Pereira, L.S. & Paredes, P. & Hunsaker, D.J. & López-Urrea, R. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method," Agricultural Water Management, Elsevier, vol. 243(C).
    20. Drerup, Philipp & Brueck, Holger & Scherer, Heinrich W., 2017. "Evapotranspiration of winter wheat estimated with the FAO 56 approach and NDVI measurements in a temperate humid climate of NW Europe," Agricultural Water Management, Elsevier, vol. 192(C), pages 180-188.
    21. 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. 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. Wang, Weishu & Rong, Yao & Zhang, Chenglong & Wang, Chaozi & Huo, Zailin, 2024. "Data assimilation of soil moisture and leaf area index effectively improves the simulation accuracy of water and carbon fluxes in coupled farmland hydrological model," Agricultural Water Management, Elsevier, vol. 291(C).
    3. 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).

    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. Pereira, L.S. & Paredes, P. & Hunsaker, D.J. & López-Urrea, R. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method," Agricultural Water Management, Elsevier, vol. 243(C).
    2. Qiu, Rangjian & Li, Longan & Liu, Chunwei & Wang, Zhenchang & Zhang, Baozhong & Liu, Zhandong, 2022. "Evapotranspiration estimation using a modified crop coefficient model in a rotated rice-winter wheat system," Agricultural Water Management, Elsevier, vol. 264(C).
    3. 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).
    4. 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).
    5. 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.
    6. 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).
    7. Zhao, Nana & Liu, Yu & Cai, Jiabing & Paredes, Paula & Rosa, Ricardo D. & Pereira, Luis S., 2013. "Dual crop coefficient modelling applied to the winter wheat–summer maize crop sequence in North China Plain: Basal crop coefficients and soil evaporation component," Agricultural Water Management, Elsevier, vol. 117(C), pages 93-105.
    8. Muniandy, Josilva M. & Yusop, Zulkifli & Askari, Muhamad, 2016. "Evaluation of reference evapotranspiration models and determination of crop coefficient for Momordica charantia and Capsicum annuum," Agricultural Water Management, Elsevier, vol. 169(C), pages 77-89.
    9. Liu, Meihan & Paredes, Paula & Shi, Haibin & Ramos, Tiago B. & Dou, Xu & Dai, Liping & Pereira, Luis S., 2022. "Impacts of a shallow saline water table on maize evapotranspiration and groundwater contribution using static water table lysimeters and the dual Kc water balance model SIMDualKc," Agricultural Water Management, Elsevier, vol. 273(C).
    10. Qiu, Rangjian & Liu, Chunwei & Cui, Ningbo & Wu, Youjie & Wang, Zhenchang & Li, Gen, 2019. "Evapotranspiration estimation using a modified Priestley-Taylor model in a rice-wheat rotation system," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    11. Aouade, G. & Ezzahar, J. & Amenzou, N. & Er-Raki, S. & Benkaddour, A. & Khabba, S. & Jarlan, L., 2016. "Combining stable isotopes, Eddy Covariance system and meteorological measurements for partitioning evapotranspiration, of winter wheat, into soil evaporation and plant transpiration in a semi-arid reg," Agricultural Water Management, Elsevier, vol. 177(C), pages 181-192.
    12. 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).
    13. 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).
    14. Xu, Gaoping & Xue, Xuzhang & Wang, Pu & Yang, Zhaoshun & Yuan, Wenya & Liu, Xiufeng & Lou, Chenjun, 2018. "A lysimeter study for the effects of different canopy sizes on evapotranspiration and crop coefficient of summer maize," Agricultural Water Management, Elsevier, vol. 208(C), pages 1-6.
    15. Miao, Qingfeng & Rosa, Ricardo D. & Shi, Haibin & Paredes, Paula & Zhu, Li & Dai, Jiaxin & Gonçalves, José M. & Pereira, Luis S., 2016. "Modeling water use, transpiration and soil evaporation of spring wheat–maize and spring wheat–sunflower relay intercropping using the dual crop coefficient approach," Agricultural Water Management, Elsevier, vol. 165(C), pages 211-229.
    16. 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).
    17. Drerup, Philipp & Brueck, Holger & Scherer, Heinrich W., 2017. "Evapotranspiration of winter wheat estimated with the FAO 56 approach and NDVI measurements in a temperate humid climate of NW Europe," Agricultural Water Management, Elsevier, vol. 192(C), pages 180-188.
    18. Pereira, L.S. & Paredes, P. & Jovanovic, N., 2020. "Soil water balance models for determining crop water and irrigation requirements and irrigation scheduling focusing on the FAO56 method and the dual Kc approach," Agricultural Water Management, Elsevier, vol. 241(C).
    19. Darouich, Hanaa & Karfoul, Razan & Ramos, Tiago B. & Moustafa, Ali & Shaheen, Baraa & Pereira, Luis S., 2021. "Crop water requirements and crop coefficients for jute mallow (Corchorus olitorius L.) using the SIMDualKc model and assessing irrigation strategies for the Syrian Akkar region," Agricultural Water Management, Elsevier, vol. 255(C).
    20. 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).

    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:260:y:2022:i:c:s0378377421005679. 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.