IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v250y2021ics0378377421001281.html
   My bibliography  Save this article

Assessment of automated evapotranspiration estimates obtained using the GP-SEBAL algorithm for dry forest vegetation (Caatinga) and agricultural areas in the Brazilian semiarid region

Author

Listed:
  • Lima, Carlos Eduardo Santos de
  • Costa, Valéria Sandra de Oliveira
  • Galvíncio, Josiclêda Domiciano
  • Silva, Richarde Marques da
  • Santos, Celso Augusto Guimarães

Abstract

Real evapotranspiration (ETr) plays a key role in water balance, especially for dry forest vegetation (Caatinga) and irrigated agricultural areas, as is the case in the Petrolina region located in the Brazilian semiarid region (BSAR). Population growth increases the need for food and the use of water resources, which are scarcer in semiarid regions. Thus, knowledge of the energy balance (EB) and radiative balance are indispensable for the management of water resources, especially in irrigated agricultural areas. Currently, one of the biggest challenges in the application of algorithms for estimating ETr based on satellite images is the calibration of the EB. The goal of this study was to evaluate the applicability of Geographic Resources Analysis Support System (GRASS) Python surface EB algorithm for land (GP-SEBAL) to calculate ETr for Caatinga vegetation and agricultural areas in the BSAR. GP-SEBAL was applied to two images from Landsat 8 obtained in 2013 and compared with manual SEBAL and observed data. In this study, kappa coefficient accuracy was used to compare the ground truth data and predicted land use and land cover. The performance of algorithms in determining the EB components, land-surface temperature (LST), net radiation (Rn), soil heat flux (G), latent heat flux (LE), sensible heat flux (H), and ETr were compared with statistical indices and uncertainty percentages (PUs) were calculated. In addition, a sensitivity analysis using a deviation of 30 W/m2 with an interval of 5 W/m2 was used to analyze the sensitivity of ETr. The results showed a strong correlation between GP-SEBAL and manual SEBAL for ETr, LST, Rn, LH, and H. The values suggest the regularity of estimating the EB in an automated manner. The results indicate a small PU difference in the estimated ETr values calculated using GP-SEBAL and SEBAL for two images of 10.87% and 20.11% for Caatinga vegetation and 15.01% and 35.16% for agriculture, respectively. We conclude that GP-SEBAL is an efficient automated algorithm for estimating ETr that uses a less complex process with a lower incidence of errors and considerably faster execution time than classical applications of SEBAL.

Suggested Citation

  • Lima, Carlos Eduardo Santos de & Costa, Valéria Sandra de Oliveira & Galvíncio, Josiclêda Domiciano & Silva, Richarde Marques da & Santos, Celso Augusto Guimarães, 2021. "Assessment of automated evapotranspiration estimates obtained using the GP-SEBAL algorithm for dry forest vegetation (Caatinga) and agricultural areas in the Brazilian semiarid region," Agricultural Water Management, Elsevier, vol. 250(C).
    • Handle: RePEc:eee:agiwat:v:250:y:2021:i:c:s0378377421001281
    DOI: 10.1016/j.agwat.2021.106863
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377421001281
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2021.106863?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. Xiang, Keyu & Li, Yi & Horton, Robert & Feng, Hao, 2020. "Similarity and difference of potential evapotranspiration and reference crop evapotranspiration – a review," Agricultural Water Management, Elsevier, vol. 232(C).
    2. Teixeira, A.H. de C. & Bastiaanssen, W.G.M. & Bassoi, L.H., 2007. "Crop water parameters of irrigated wine and table grapes to support water productivity analysis in the Sao Francisco river basin, Brazil," Agricultural Water Management, Elsevier, vol. 94(1-3), pages 31-42, December.
    3. 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).
    4. Cunha, Elias Rodrigues da & Santos, Celso Augusto Guimarães & Silva, Richarde Marques da & Bacani, Vitor Matheus & Pott, Arnildo, 2021. "Future scenarios based on a CA-Markov land use and land cover simulation model for a tropical humid basin in the Cerrado/Atlantic forest ecotone of Brazil," Land Use Policy, Elsevier, vol. 101(C).
    5. Mhawej, Mario & Elias, Georgie & Nasrallah, Ali & Faour, Ghaleb, 2020. "Dynamic calibration for better SEBALI ET estimations: Validations and recommendations," Agricultural Water Management, Elsevier, vol. 230(C).
    6. Mhawej, Mario & Caiserman, Arnaud & Nasrallah, Ali & Dawi, Ali & Bachour, Roula & Faour, Ghaleb, 2020. "Automated evapotranspiration retrieval model with missing soil-related datasets: The proposal of SEBALI," Agricultural Water Management, Elsevier, vol. 229(C).
    7. Zhang, Zhenyu & Li, Xiaoyu & Liu, Lijuan & Wang, Yugang & Li, Yan, 2020. "Influence of mulched drip irrigation on landscape scale evapotranspiration from farmland in an arid area," Agricultural Water Management, Elsevier, vol. 230(C).
    8. Rahimzadegan, Majid & Janani, AdelehalSadat, 2019. "Estimating evapotranspiration of pistachio crop based on SEBAL algorithm using Landsat 8 satellite imagery," Agricultural Water Management, Elsevier, vol. 217(C), pages 383-390.
    Full references (including those not matched with items on IDEAS)

    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. Sabzchi-Dehkharghani, Hamed & Nazemi, Amir Hossein & Sadraddini, Ali Ashraf & Majnooni-Heris, Abolfazl & Biswas, Asim, 2021. "Recognition of different yield potentials among rain-fed wheat fields before harvest using remote sensing," Agricultural Water Management, Elsevier, vol. 245(C).
    2. Mhawej, Mario & Nasrallah, Ali & Abunnasr, Yaser & Fadel, Ali & Faour, Ghaleb, 2021. "Better irrigation management using the satellite-based adjusted single crop coefficient (aKc) for over sixty crop types in California, USA," Agricultural Water Management, Elsevier, vol. 256(C).
    3. Wei, Jun & Cui, Yuanlai & Zhou, Sihang & Luo, Yufeng, 2022. "Regional water-saving potential calculation method for paddy rice based on remote sensing," Agricultural Water Management, Elsevier, vol. 267(C).
    4. 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).
    5. Allam, Mona & Mhawej, Mario & Meng, Qingyan & Faour, Ghaleb & Abunnasr, Yaser & Fadel, Ali & Xinli, Hu, 2021. "Monthly 10-m evapotranspiration rates retrieved by SEBALI with Sentinel-2 and MODIS LST data," Agricultural Water Management, Elsevier, vol. 243(C).
    6. Mhawej, Mario & Elias, Georgie & Nasrallah, Ali & Faour, Ghaleb, 2020. "Dynamic calibration for better SEBALI ET estimations: Validations and recommendations," Agricultural Water Management, Elsevier, vol. 230(C).
    7. Wei, Jun & Cui, Yuanlai & Luo, Yufeng, 2023. "Rice growth period detection and paddy field evapotranspiration estimation based on an improved SEBAL model: Considering the applicable conditions of the advection equation," Agricultural Water Management, Elsevier, vol. 278(C).
    8. Phogat, V. & Skewes, M.A. & McCarthy, M.G. & Cox, J.W. & Šimůnek, J. & Petrie, P.R., 2017. "Evaluation of crop coefficients, water productivity, and water balance components for wine grapes irrigated at different deficit levels by a sub-surface drip," Agricultural Water Management, Elsevier, vol. 180(PA), pages 22-34.
    9. Cunha, Angélica Carvalho & Filho, Luís Roberto Almeida Gabriel & Tanaka, Adriana Aki & Goes, Bruno Cesar & Putti, Fernando Ferrari, 2021. "Influence Of The Estimated Global Solar Radiation On The Reference Evapotranspiration Obtained Through The Penman-Monteith Fao 56 Method," Agricultural Water Management, Elsevier, vol. 243(C).
    10. Williams, Larry E. & Levin, Alexander D. & Fidelibus, Matthew W., 2022. "Crop coefficients (Kc) developed from canopy shaded area in California vineyards," Agricultural Water Management, Elsevier, vol. 271(C).
    11. Shan Jiang & Jian Zhou & Guojie Wang & Qigen Lin & Ziyan Chen & Yanjun Wang & Buda Su, 2022. "Cropland Exposed to Drought Is Overestimated without Considering the CO 2 Effect in the Arid Climatic Region of China," Land, MDPI, vol. 11(6), pages 1-21, June.
    12. Cai, Ximing & Yang, Yi-Chen E. & Ringler, Claudia & Zhao, Jianshi & You, Liangzhi, 2011. "Agricultural water productivity assessment for the Yellow River Basin," Agricultural Water Management, Elsevier, vol. 98(8), pages 1297-1306, May.
    13. Masoud Derakhshandeh & Mustafa Tombul, 2022. "Calibration of METRIC Modeling for Evapotranspiration Estimation Using Landsat 8 Imagery Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(1), pages 315-339, January.
    14. Wang, Yahui & Li, Sien & Qin, Shujing & Guo, Hui & Yang, Danni & Lam, Hon-Ming, 2020. "How can drip irrigation save water and reduce evapotranspiration compared to border irrigation in arid regions in northwest China," Agricultural Water Management, Elsevier, vol. 239(C).
    15. Ning He & Wenxian Guo & Hongxiang Wang & Long Yu & Siyuan Cheng & Lintong Huang & Xuyang Jiao & Wenxiong Chen & Haotong Zhou, 2023. "Temporal and Spatial Variations in Landscape Habitat Quality under Multiple Land-Use/Land-Cover Scenarios Based on the PLUS-InVEST Model in the Yangtze River Basin, China," Land, MDPI, vol. 12(7), pages 1-19, July.
    16. Bastidas-Obando, E. & Bastiaanssen, W.G.M. & Jarmain, C., 2017. "Estimation of transpiration fluxes from rainfed and irrigated sugarcane in South Africa using a canopy resistance and crop coefficient model," Agricultural Water Management, Elsevier, vol. 181(C), pages 94-107.
    17. Zheng Wang & Yue Huang & Tie Liu & Chanjuan Zan & Yunan Ling & Chenyu Guo, 2022. "Analysis of the Water Demand-Supply Gap and Scarcity Index in Lower Amu Darya River Basin, Central Asia," IJERPH, MDPI, vol. 19(2), pages 1-18, January.
    18. 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).
    19. Shirin Moradi & Thomas Heinze & Jasmin Budler & Thanushika Gunatilake & Andreas Kemna & Johan Alexander Huisman, 2021. "Combining Site Characterization, Monitoring and Hydromechanical Modeling for Assessing Slope Stability," Land, MDPI, vol. 10(4), pages 1-23, April.
    20. Hadi Eskandari Damaneh & Hassan Khosravi & Khalil Habashi & Hamed Eskandari Damaneh & John P. Tiefenbacher, 2022. "The impact of land use and land cover changes on soil erosion in western Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(3), pages 2185-2205, February.

    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:250:y:2021:i:c:s0378377421001281. 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.