Skip to main content
SpringerLink
Log in

Evaluating the performance of two SEB models for estimating ET based on satellite images in arid regions

  • Original Paper
  • Published:
Arabian Journal of Geosciences Aims and scope Submit manuscript

Abstract

Surface energy balance (SEB) models are one of the most important methods for estimating evapotranspiration (ET). This study was aimed at assessing the applications of two SEB models under arid conditions. This was achieved by integrating in situ meteorological data and Landsat 8 satellite images for two consecutive years (2014 and 2015) for alfalfa cultivation in 2014 and maize cultivation in 2015. The performance of the two SEB models was evaluated by comparing the ET estimated by the SEB models and that measured using an Eddy covariance (EC) instrument. Mapping the ET at high resolution using internalized calibration (METRIC) displayed the best performance in 2014, with a coefficient of determination, R2 of 0.8, followed by the simplified surface energy balance index (S-SEBI) model (with R2 = 0.67). In addition, METRIC showed high efficiency, with a Nash Sutcliffe (NSE) model efficiency coefficient of 0.98, followed by S-SEBI, with an NSE of 0.93. Poor performance was observed in 2015 where the R2 for both METRIC and S-SEBI were 0.3 and 0.45, respectively. In addition, the NSE for METRIC decreased to 0.91. Conversely, the NSE for S-SEBI improved to 0.97. Therefore, the performance of the models was affected by instability due to soil water content (SWC) and low precipitation (62.2 mm in 2015). However, the performance of METRIC was better than that of S-SEBI. In general, METRIC is considered a good SEB model for arid regions. In addition, S-SEBI could be an adequate model for overcoming the difficulty associated with obtaining meteorological data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Al-Gaadi K, Patil V, Tola E, Madugundu R, Gowda P (2016a) Evaluation of METRIC-derived ET fluxes over irrigated alfalfa crop in desert conditions using scintillometer measurements. Arab J Geosci 9:1–12

    Google Scholar 

  • Al-Gaadi KA, Patil V, Tola E, Madugundu R, Gowda PH (2016b) Evaluation of METRIC-derived ET fluxes over irrigated alfalfa crop in desert conditions using scintillometer measurements. Arab J Geosci 9:441

    Google Scholar 

  • Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration-guidelines for computing crop water requirements-Fao irrigation and drainage paper 56 Fao, Rome 300:D05109

  • Allen R, Tasumi M, Trezza R, Waters R, Bastiaanssen W (2002a) SEBAL (surface energy balance algorithms for land) advance training and users manual–Idaho implementation, version 1:97

  • Allen RG, Morse A, Tasumi M, Trezza R, Bastiaanssen W, Wright JL, Kramber W (2002b) Evapotranspiration from a satellite-based surface energy balance for the Snake plain aquifer in Idaho. In: Proc. USCID conference, USCID

  • Allen RG, Tasumi M, Morse A, Trezza R (2005) A Landsat-based energy balance and evapotranspiration model in Western US water rights regulation and planning. Irrig Drain Syst 19:251–268

    Google Scholar 

  • Allen RG et al (2007a) Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—applications. J Irrig Drain Eng 133:395–406

    Google Scholar 

  • Allen RG, Tasumi M, Trezza R (2007b) Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—model. J Irrig Drain Eng 133:380–394

    Google Scholar 

  • Allen R, Irmak A, Trezza R, Hendrickx JM, Bastiaanssen W, Kjaersgaard J (2011) Satellite-based ET estimation in agriculture using SEBAL and METRIC. Hydrol Process 25:4011–4027

    Google Scholar 

  • Allen RG et al (2013) Automated Calibration of the METRIC-Landsat Evapotranspiration Process. J Am Water Resour Assoc 49:563–576

    Google Scholar 

  • Antonopoulos VZ, Antonopoulos AV (2017) Daily reference evapotranspiration estimates by artificial neural networks technique and empirical equations using limited input climate variables. Comput Electron Agric 132:86–96

    Google Scholar 

  • Bastiaanssen WGM (1995) Regionalization of surface flux densities and moisture indicators in composite terrain. A remote sensing approach under clear skies in Mediterranean climates. Vol 109. SC-DLO

  • Bastiaanssen W (2000) SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. J Hydrol 229:87–100

    Google Scholar 

  • Bastiaanssen W, Menenti M, Feddes R, Holtslag A (1998a) A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation. J Hydrol 212:198–212

    Google Scholar 

  • Bastiaanssen W, Pelgrum H, Wang J, Ma Y, Moreno J, Roerink G, Van der Wal T (1998b) A remote sensing surface energy balance algorithm for land (SEBAL).: part 2: validation. J Hydrol 212:213–229

    Google Scholar 

  • Bhattarai N, Shaw SB, Quackenbush LJ, Im J, Niraula R (2016) Evaluating five remote sensing based single-source surface energy balance models for estimating daily evapotranspiration in a humid subtropical climate. Int J Appl Earth Obs Geoinf 49:75–86

    Google Scholar 

  • Biudes MS, Machado NG, de Morais Danelichen VH, Souza MC, Vourlitis GL, de Souza Nogueira J (2014) Ground and remote sensing-based measurements of leaf area index in a transitional forest and seasonal flooded forest in Brazil. Int J Biometeorol 58:1181–1193

    Google Scholar 

  • Burnett B (2007) A procedure for estimating Total evapotranspiration using satellite-based vegetation indices with separate estimates from bare soil. Ms. Thesis, University of Idaho, Moscow, Idaho

  • Cai X, Sharma BR (2010) Integrating remote sensing, census and weather data for an assessment of rice yield, water consumption and water productivity in the indo-Gangetic river basin. Agric Water Manag 97:309–316

    Google Scholar 

  • Çakir R, Kanburoglu-Çebi U, Altintas S, Ozdemir A (2017) Irrigation scheduling and water use efficiency of cucumber grown as a spring-summer cycle crop in solar greenhouse. Agric Water Manag 180:78–87

    Google Scholar 

  • Carlson TN, Ripley DA (1997) On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sens Environ 62:241–252

    Google Scholar 

  • Caselles V, Artigao M, Hurtado E, Coll C, Brasa A (1998) Mapping actual evapotranspiration by combining Landsat TM and NOAA-AVHRR images: application to the Barrax area, Albacete Spain. Remote Sens Environ 63:1–10

    Google Scholar 

  • Cetin M (2015) Using GIS analysis to assess urban green space in terms of accessibility: case study in Kutahya. Int J Sust Dev World 22:420–424

    Google Scholar 

  • Cetin M, Adiguzel F, Kaya O, Sahap A (2018a) Mapping of bioclimatic comfort for potential planning using GIS in Aydin. Environ Dev Sustain 20:361–375

    Google Scholar 

  • Cetin M, Zeren I, Sevik H, Cakir C, Akpinar H (2018b) A study on the determination of the natural park’s sustainable tourism potential. Environ Monit Assess 190:167

    Google Scholar 

  • Chirouze J et al. (2014) Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate. Hydrol Earth Syst Sci Discuss 1165–1188

    Google Scholar 

  • Courault D, Seguin B, Olioso A (2005) Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches. Irrig Drain Syst 19:223–249

    Google Scholar 

  • French AN, Hunsaker DJ, Thorp KR (2015) Remote sensing of evapotranspiration over cotton using the TSEB and METRIC energy balance models. Remote Sens Environ 158:281–294

    Google Scholar 

  • Gokmen M, Vekerdy Z, Verhoef A, Verhoef W, Batelaan O, Van der Tol C (2012) Integration of soil moisture in SEBS for improving evapotranspiration estimation under water stress conditions. Remote Sens Environ 121:261–274

    Google Scholar 

  • Gonzalez-Dugo M, Neale C, Mateos L, Kustas W, Prueger J, Anderson M, Li F (2009) A comparison of operational remote sensing-based models for estimating crop evapotranspiration. Agric For Meteorol 149:1843–1853

    Google Scholar 

  • Gowda PH, Chávez JL, Howell TA, Marek TH, New LL (2008) Surface energy balance based evapotranspiration mapping in the Texas high plains. Sensors 8:5186–5201

    Google Scholar 

  • Hemakumara H, Chandrapala L, Moene AF (2003) Evapotranspiration fluxes over mixed vegetation areas measured from large aperture scintillometer. Agric Water Manag 58:109–122

    Google Scholar 

  • Irmak A, Ratcliffe I, Ranade P, Hubbard K, Singh RK, Kamble B, Kjaersgaard J (2011) Estimation of land surface evapotranspiration with a satellite remote sensing procedure. Great Plains Res 21:73–88

    Google Scholar 

  • Kalma JD, McVicar TR, McCabe MF (2008) Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data. Surv Geophys 29:421–469

    Google Scholar 

  • Kang S et al (2017) Improving agricultural water productivity to ensure food security in China under changing environment: from research to practice. Agric Water Manag 179:5–17

    Google Scholar 

  • Kustas W, Norman J (1996) Use of remote sensing for evapotranspiration monitoring over land surfaces. Hydrol Sci J 41:495–516

    Google Scholar 

  • Kustas W, Perry E, Doraiswamy P, Moran M (1994) Using satellite remote sensing to extrapolate evapotranspiration estimates in time and space over a semiarid rangeland basin. Remote Sens Environ 49:275–286

    Google Scholar 

  • Li Z-L et al (2009) A review of current methodologies for regional evapotranspiration estimation from remotely sensed data. Sensors 9:3801–3853

    Google Scholar 

  • Lian J, Huang M (2016) Comparison of three remote sensing based models to estimate evapotranspiration in an oasis-desert region. Agric Water Manag 165:153–162

    Google Scholar 

  • Liaqat UW, Choi M (2015) Surface energy fluxes in the Northeast Asia ecosystem: SEBS and METRIC models using Landsat satellite images. Agric For Meteorol 214:60–79

    Google Scholar 

  • Liu SM, Xu ZW, Wang W, Jia Z, Zhu M, Bai J, Wang J (2011) A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem. Hydrol Earth Syst Sci 15:1291–1306

    Google Scholar 

  • Madugundu R, Al-Gaadi KA, Tola E, Kayad AG, Hassaballa AA, Patil VC (2017) Seasonal dynamics of surface energy fluxes over a center-pivot irrigated cropland in Saudi Arabia. J Environ Biol 38:743

    Google Scholar 

  • Mahmoud SH, Gan TY (2019) Irrigation water management in arid regions of Middle East: assessing spatio-temporal variation of actual evapotranspiration through remote sensing techniques and meteorological data. Agric Water Manag 212:35–47

    Google Scholar 

  • Mauser W, Schädlich S (1998) Modelling the spatial distribution of evapotranspiration on different scales using remote sensing data. J Hydrol 212:250–267

    Google Scholar 

  • Meneti M, Choudhary B (1993) Parameterization of land surface evapotranspiration using a location dependent potential evapotranspiration and surface temperature range. Exchange Processes at the land Surface for a Range of Space and time series, Bolle, HJ, Feddes, RA, and Kalma, JD International Association of Hydrological Sciences Publication 212:561–568

  • Merlin O, Chirouze J, Olioso A, Jarlan L, Chehbouni G, Boulet G (2014) An image-based four-source surface energy balance model to estimate crop evapotranspiration from solar reflectance/thermal emission data (SEB-4S). Agric For Meteorol 184:188–203

    Google Scholar 

  • Monin AS, Obukhov AM (1954) Basic laws of turbulent mixing in the surface layer of the atmosphere. Contrib Geophys Inst Acad Sci USSR 151:e187

    Google Scholar 

  • Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50:885–900

    Google Scholar 

  • Nakai T, Shimoyama K (2012) Ultrasonic anemometer angle of attack errors under turbulent conditions. Agric For Meteorol 162:14–26

    Google Scholar 

  • NASA (2016) Climatology Resource for Agroclimatology. http://power.larc.nasa.gov/common/AgroclimatologyMethodology/Agro1d0_Methodology_Content.html. Accessed 28 Feb 2017

  • Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part I—A discussion of principles. J Hydrol 10:282–290

    Google Scholar 

  • Norman J, Kustas W, Humes K (1995) Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature. Agric For Meteorol 77:263–293

    Google Scholar 

  • Numata I, Khand K, Kjaersgaard J, Cochrane MA, Silva SS (2017) Evaluation of Landsat-based METRIC modeling to provide high-spatial resolution evapotranspiration estimates for Amazonian forests. Remote Sens 9:46

    Google Scholar 

  • Peddinti SR, KBVN P, Sawant SA (2018) Evaluation of two energy balance models for estimating evapotranspiration in the semi-arid region of India

  • Qualls RJ, Brutsaert W (1996) Evaluation of Spatially Distributed Ground-Based and Remotely Sensed Data to Estimate Spatially Distributed Sensible Heat Fluxes. Water Resour Res 32:2489–2495

    Google Scholar 

  • Roerink G, Su Z, Menenti M (2000) S-SEBI: a simple remote sensing algorithm to estimate the surface energy balance physics and chemistry of the earth. Part B: Hydrology, Oceans and Atmosphere. Physics and Chemistry of the Earth 25:147–157

    Google Scholar 

  • Saadi S et al (2018) Assessment of actual evapotranspiration over a semiarid heterogeneous land surface by means of coupled low-resolution remote sensing data with an energy balance model: comparison to extra-large aperture scintillometer measurements. Hydrol Earth Syst Sci 22:2187–2209

    Google Scholar 

  • Senay GB, Budde M, Verdin JP, Melesse AM (2007) A coupled remote sensing and simplified surface energy balance approach to estimate actual evapotranspiration from irrigated fields. Sensors 7:979–1000

    Google Scholar 

  • Senay GB, Budde ME, Verdin JP (2011) Enhancing the Simplified Surface Energy Balance (SSEB) approach for estimating landscape ET: Validation with the METRIC model. Agric Water Manag 98:606–618

    Google Scholar 

  • Silva BBD, Braga AC, Braga CC, Oliveira LMMD, Montenegro SMGL, Barbosa Junior B (2016) Procedures for calculation of the albedo with OLI-Landsat 8 images: Application to the Brazilian semi-arid. Revista Brasileira de Engenharia Agrícola e Ambiental 20:3–8

    Google Scholar 

  • Singh RK, Irmak A (2011) Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes. Hydrol Sci J 56:895–906

    Google Scholar 

  • Singh RK, Senay GB (2015) Comparison of four different energy balance models for estimating evapotranspiration in the Midwestern United States. Water 8:9

    Google Scholar 

  • Sobrino J, El Kharraz J, Li Z-L (2003) Surface temperature and water vapour retrieval from MODIS data. Int J Remote Sens 24:5161–5182

    Google Scholar 

  • Song L, Liu S, Kustas WP, Zhou J, Xu Z, Xia T, Li M (2016) Application of remote sensing-based two-source energy balance model for mapping field surface fluxes with composite and component surface temperatures. Agric For Meteorol 230:8–19

    Google Scholar 

  • Stewart B, Lal R (2018) Increasing world average yields of cereal crops: It's all about water advances in agronomy

  • Sutanto S, Wenninger J, Coenders-Gerrits A, Uhlenbrook S (2012) Partitioning of evaporation into transpiration, soil evaporation and interception: a comparison between isotope measurements and a HYDRUS-1D model. Hydrol Earth Syst Sci 16:2605–2616

    Google Scholar 

  • Tasumi M, Trezza R, Allen RG, Wright JL (2005) Operational aspects of satellite-based energy balance models for irrigated crops in the semi-arid US. Irrig Drain Syst 19:355–376

    Google Scholar 

  • USGS (2015) satellite image. https://ers.cr.usgs.gov/login/. Accessed 11/11/2015 2015

  • USGS (2018) NDVI, the Foundation for Remote Sensing Phenology. https://phenology.cr.usgs.gov/ndvi_foundation.php

  • Valayamkunnath P, Sridhar V, Zhao W, Allen RG (2018) Intercomparison of surface energy fluxes, soil moisture, and evapotranspiration from eddy covariance, large-aperture scintillometer, and modeling across three ecosystems in a semiarid climate. Agric For Meteorol 248:22–47

    Google Scholar 

  • Van der Kwast J et al (2009) Evaluation of the surface energy balance system (SEBS) applied to ASTER imagery with flux-measurements at the SPARC 2004 site (Barrax, Spain). Hydrol Earth Syst Sci Discuss 6:1165–1196

    Google Scholar 

  • Wagle P, Bhattarai N, Gowda PH, Kakani VG (2017) Performance of five surface energy balance models for estimating daily evapotranspiration in high biomass sorghum. ISPRS J Photogramm Remote Sens 128:192–203

    Google Scholar 

  • Walter IA et al. (2000) ASCE’s standardized reference evapotranspiration equation. In: Proc. of the Watershed Management 2000 Conference

  • Waters R, Allen R, Bastiaanssen W, Tasumi M, Trezza R (2002) SEBAL surface energy balance algorithms for land Idaho implementation advanced training and users manual, Idaho, USA

  • Yang Y et al (2018) Intercomparison of Three Two-Source Energy Balance Models for Partitioning Evaporation and Transpiration in Semiarid Climates. Remote Sens 10:1149

    Google Scholar 

  • Zanter K (2016) Landsat 8 (L8) data users handbook Landsat science official website

  • Zhan C, Yin J, Wang F, Dong Q (2015) Regional estimation and validation of remotely sensed evapotranspiration in China. Catena 133:35–42

    Google Scholar 

  • Zhao J, Olivas PC, Kunwor S, Malone SL, Staudhammer CL, Starr G, Oberbauer SF (2018) Comparison of sensible heat flux measured by large aperture scintillometer and eddy covariance in a seasonally-inundated wetland. Agric For Meteorol 259:345–354

    Google Scholar 

  • Elkatoury et al (2019) Estimating Evapotranspiration Using Coupled Remote Sensing and Three SEB Models in an Arid Region. Environ Process 1-25

Download references

Funding

The project was financially supported by King Saud University, Vice Deanship of Research Chairs.

Author information

Authors and Affiliations

  1. Alamoudi Water Research Chair, King Saud University, Riyadh, 11451, Kingdom of Saudi Arabia

    Ahmed Elkatoury & A. A. Alazba

  2. Agricultural Engineering Department, King Saud University, Riyadh, 11451, Kingdom of Saudi Arabia

    A. A. Alazba & Amr Abdelbary

  3. Agricultural Engineering Department, Ain Shams University, Cairo, 11241, Egypt

    Amr Abdelbary

Authors
  1. Ahmed Elkatoury
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. A. Alazba
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Amr Abdelbary
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ahmed Elkatoury.

Additional information

Responsible Editor: Marouane Temimi

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Elkatoury, A., Alazba, A. & Abdelbary, A. Evaluating the performance of two SEB models for estimating ET based on satellite images in arid regions. Arab J Geosci 13, 74 (2020). https://doi.org/10.1007/s12517-019-5019-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-019-5019-3

Keywords

Search

Navigation