Performance evaluation of Satellite-based actual evapotranspiration technique
##plugins.themes.bootstrap3.article.main##
Abstract
Estimating crop evapotranspiration is vital for the calculation of irrigation water requirements. Remote sensing data have proven to be a valuable and efficient tool for estimating evapotranspiration. It has been used intensively over the past decade due to free, high temporal and spectral resolution data availability. The main aim of this study was to estimate the evapotranspiration (ET) over a selected area in El-Beheira governorate, Egypt based on the Simplified Surface Energy Balance Index (S-SEBI) using nine Landsat-8 images acquired from January to December 2020. The performance of the studied method was compared with the CROPWAT-8 model. The results revealed the acceptable accuracy of the ET estimated from S-SEBI algorithms with Landsat 8 images according to the coefficient of determination (r2 = 0.82) and root mean square error (RMSE = 0.53 mm/day). Therefore, it is recommended to use the S-SEBI to calculate the spatial evapotranspiration distribution using Landsat-8 images to provide the required information for determining irrigation water requirements and suggesting an efficient water management strategy.
##plugins.themes.bootstrap3.article.details##
##plugins.themes.bootstrap3.article.details##
Keywords
Crop evapotranspiration, CROPWAT-8 model, Remote sensing, Simplified surface energy balance index (S-SEBI)
References
Abdel Kader, M.H., Khalifa, H.E., Sheta A.S. & Ibrahim, A.A, (2015). Evapotranspiration estimation using remote sensing data and some climatic models. J. Soil Sci. and Agric. Eng., Mansoura Univ., 6 (11), 1341 – 1354.
Allen, R.G., Pereira, L.S., Raes, D. & Smith, M. (1998). Crop evapotranspiration - guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56; FAO, Rome, Italy.
Allen, R.G., Tasumi, M. & Trezza, R., (2007). Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) Model. Journal of Irrigation and Drainage Engineering, 133(4), 380–394. https://doi.org/10.1061/(ASCE)0733-9437(2007)133:4(380)
Ayyad, S., Al Zayed, I. S., Thi Ha V. T. & Ribbe, L. (2019). The Performance of Satellite-Based Actual Evapotranspiration Products and the Assessment of Irrigation Efficiency in Egypt. Water, 11(9), 1913-1922.https://doi.org/10.3390/w11091913
Basit, A., Khalil, R. Z. & Haque, S. (2018). Application of Simplified Surface Energy Balance Index (S-SEBI) for Crop Evapotranspiration using Landsat 8. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-1, 33–37.https://doi.org/10.5194/isprs-archives-XLII-1-33-2018.
Bastiaanssen, W. G. M.(2000). SEBAL-basedsensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. Journal of Hydrology, 229 (1-2), 87-100.https://doi.org/10.1016/S0022-1694(99)00202-4
Bezerra, B.G., da Silva, B.B., dos Santos, C.A.C. & Bezerra, J.R.C. (2015). Actual evapotranspiration estimation using remote sensing: comparison of SEBAL and SSEB approaches. Advances in Remote Sensing, 4, 234-247.https://doi.org/10.4236/ars.2015.43019.
Carlson, T. & Ripley, D. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment,62, 241-252. https://doi.org/10.1016/S0034-4257(97)00104-1.
Ezz, H. & Abdelwares M. (2020). Spatial and Temporal Variation of ETo ETO for EGYPT using Remote Sensing. ARPN Journal of Engineering and Applied Sciences, 15(1), 104-112. http://www.arpnjournals.org/jeas/resear ch_papers/rp_2020/jeas_0120_8073.pdf.
Foodand Agriculture Organization (2009). CROPWAT 8.0. Edited, Land and Water Development Division, Rome, Italy.
Jiang, Z., Huete, A., Chen, J., Chen, Y., Li, J., Yan, G. & Zou, Y. (2006). Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction. Remote Sensing of Environment. 101. 366-378. https://doi.org/10.1016/j.rse.2006.01.003.
Kukla, G. J. (1981). Surface Albedo. In: Berger, A. (eds) Climatic Variations and Variability: Facts and Theories. NATO Advanced Study Institutes Series, Vol 72. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-8514-8_4.
Kumar, U., Rashmi, Chatterjee, C., Raghuwanshi, N.S., (2021). Comparative evaluation of simplified surface energy balance index-based actual ET against lysimeter data in a Tropical River basin. Sustainability, 13, 13786. https://doi.org/10.3390/su132413786.
Kumar, U., Sahoo, B., Chatterjee, C. & Raghuwanshi, N. S. (2020). Evaluation of simplified surface energy balance index (S-SEBI) method for estimating actual evapotranspiration in Kangsabati Reservoir Command using Landsat 8 imagery. Journal of the Indian Society of Remote Sensing, 48(10), 1421–1432. https://doi.org/10.1007/s12524-020-01166-9.
Li, Z. L., Tang, R., Wan, Z., Bi, Y., Zhou, C., Tang, B., Yan, G. & Zhang, X. (2009). A review of current methodologies for regional evapotranspiration estimation from remotely sensed data. Sensors, 9(5), 3801-3853. https://doi.org/10.3390/s90503801.
Alves, E.R.A., de Freita, I. G. F., Gomes, H. B. , Silva, F. D. & dos Santos, M. N.(2017). Using Landsat-8 images in the estimative of surface radiation balance. Journal of Hyperspectral Remote Sensing, 7(2), 91-100.
Makar R. S., Shahin Sahar A., El-Nazer Mostafa & Wheida Ali (2022). Development of a PCA-based land use/land cover classification utilizing Sentinel-2-time series. Middle East Journal of Agriculture Research, 11(2):630-637. https://doi.org/10.36632/mejar/2022.11.2.42.
Mondal, I., Thakura, S., Deb, A. & Dea, T. K. (2022). Application of the METRIC model for mapping evapotranspiration over the Sundarban Biosphere Reserve, India. Ecological Indicators, 136, 108553. https://doi.org/10.1016/j.ecolind.2022.108553
Rawata, K.S., Singh, S.K., Bala, A. & Szabo, S., (2019). Estimation of crop evapotranspiration through spatial distributed crop coefficient in a semi-arid environment. Agric. Water Manag., 213,922-933.https://doi.org/10.1016/j.agwat.2018.12.002.
Reyes-González, A., Kjaersgaard, J., Trooien, T., Reta-Sánchez, D. G., Sánchez-Duarte, J. I., Preciado-Range, P. & Fortis-Hernández, M. (2019). Comparison of leaf area index, surface temperature, and actual evapotranspiration estimated using the METRIC model and insitu measurements. Sensors, 19(8), 1857-1878. https://doi.org/10.3390/s19081857
Rodrigues, G.C. & Braga, R.P., (2021). Estimation of daily reference evapotranspiration from NASA POWER reanalysis products in a hot summer Mediterranean climate. Agronomy, 11, 2077-2091. https://doi.org/10.3390/agronomy11102077.
Roerink, G.J., 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, 25(2), 147-157. https://doi.org/10.1016/S1464-1909(99)00128-8
Rouse, J.W., R.H. Haas, J.A. Schell & D. W. Deering(1974). Monitoring vegetation systems in the Great Plains withERTS, In: S.C. Freden, E.P. Mercanti, and M. Becker (eds) Third Earth Resources Technology Satellite–1 Syposium. Volume I: Technical Presentations, NASA SP-351, NASA, Washington, D.C., pp. 309-317
Senay, G.B., Bohms, S., Singh, R.K., Gowda, P.H., Velpuri, N.M., Alemu, H. & Verdin, J.P. (2013). Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach. Journal of the American Water Resources Association (JAWRA), 49(3), 577–591. https://doi.org/10.1111/jawr.12057
Sobrino, J. A. & Raissouni, N., (2000). Toward remote sensing methods for land cover dynamic monitoring: application to Morocco. Int. J. Remote Sens., 21(2), 353-366. https://doi.org/10.1080/014311600210876.
Sobrino, J. A., El Kharraz, J. & Li, Z. L. (2003). Surface temperature and water vapour retrieval from MODIS data. International Journal of Remote Sensing,24 (24),5161-5182. https://doi.org/10.1080/0143116031000102502
Sobrino, J. A., Raissouni, N., Olioso, A., Hasager, C. B., Belaid, M., Abdel Rahman, S. & Chehbouni, A., (2001). WATERMED - Water use efficiency in natural vegetation and agricultural areas by Remote sensing in the Mediterranean basin. In IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217), 2001, pp. 3158-3160 vol.7, Sydney, Australia, 9–13 July, 2001. https://doi.org/10.1109/IGARSS.2001.978289.
Sobrino,J. A., Jiménez-Muñoz, J. C.,Sòria, G., and Romaguera, M.,Guanter, L., Moreno J., Plaza, A. & Martínez, P. (2008). Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE Transactions on Geoscince and Remote Sensing, 46(2), 316-327. https://doi.org/10.1109/TGRS.2007.904834.
Sobrino, J.A.; Souza daRocha, N., Skokovi´c, D.,SuélenKäfer, P., López-Urrea, R., Jiménez-Muñoz, J.C. & Alves Rolim, S.B. (2021). Evapotranspiration Estimation withthe S-SEBI Method from Landsat 8Data against LysimeterMeasurements at the Barrax Site,Spain. Remote Sens., 13: 3686-3703.https://doi.org/10.3390/rs13183686.
United States Geological Survey (2019). Landsat 8 (L8), Data Users Handbook. EROS Sioux Falls, South Dakota. LSDS-1574, Version 5.0. https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/atoms/files/LSDS-1574_L8_Data_Users_Handbook-v5.0.pdf.
Vozhehova R. A., Lavrynenko Y. O., Kokovikhin S. V., Lykhovyd P. V., Biliaieva I. M., Drobitko A. V. & Nesterchuk V. V. (2018). Assessment of the CROPWAT 8.0 software reliability for evapotranspiration and crop water requirements calcu-lations. Journal of Water and Land Development. 39, 147–152. https://doi.org/10.2478/jwld-2018-0070.
Allen, R.G., Pereira, L.S., Raes, D. & Smith, M. (1998). Crop evapotranspiration - guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56; FAO, Rome, Italy.
Allen, R.G., Tasumi, M. & Trezza, R., (2007). Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) Model. Journal of Irrigation and Drainage Engineering, 133(4), 380–394. https://doi.org/10.1061/(ASCE)0733-9437(2007)133:4(380)
Ayyad, S., Al Zayed, I. S., Thi Ha V. T. & Ribbe, L. (2019). The Performance of Satellite-Based Actual Evapotranspiration Products and the Assessment of Irrigation Efficiency in Egypt. Water, 11(9), 1913-1922.https://doi.org/10.3390/w11091913
Basit, A., Khalil, R. Z. & Haque, S. (2018). Application of Simplified Surface Energy Balance Index (S-SEBI) for Crop Evapotranspiration using Landsat 8. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-1, 33–37.https://doi.org/10.5194/isprs-archives-XLII-1-33-2018.
Bastiaanssen, W. G. M.(2000). SEBAL-basedsensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. Journal of Hydrology, 229 (1-2), 87-100.https://doi.org/10.1016/S0022-1694(99)00202-4
Bezerra, B.G., da Silva, B.B., dos Santos, C.A.C. & Bezerra, J.R.C. (2015). Actual evapotranspiration estimation using remote sensing: comparison of SEBAL and SSEB approaches. Advances in Remote Sensing, 4, 234-247.https://doi.org/10.4236/ars.2015.43019.
Carlson, T. & Ripley, D. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment,62, 241-252. https://doi.org/10.1016/S0034-4257(97)00104-1.
Ezz, H. & Abdelwares M. (2020). Spatial and Temporal Variation of ETo ETO for EGYPT using Remote Sensing. ARPN Journal of Engineering and Applied Sciences, 15(1), 104-112. http://www.arpnjournals.org/jeas/resear ch_papers/rp_2020/jeas_0120_8073.pdf.
Foodand Agriculture Organization (2009). CROPWAT 8.0. Edited, Land and Water Development Division, Rome, Italy.
Jiang, Z., Huete, A., Chen, J., Chen, Y., Li, J., Yan, G. & Zou, Y. (2006). Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction. Remote Sensing of Environment. 101. 366-378. https://doi.org/10.1016/j.rse.2006.01.003.
Kukla, G. J. (1981). Surface Albedo. In: Berger, A. (eds) Climatic Variations and Variability: Facts and Theories. NATO Advanced Study Institutes Series, Vol 72. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-8514-8_4.
Kumar, U., Rashmi, Chatterjee, C., Raghuwanshi, N.S., (2021). Comparative evaluation of simplified surface energy balance index-based actual ET against lysimeter data in a Tropical River basin. Sustainability, 13, 13786. https://doi.org/10.3390/su132413786.
Kumar, U., Sahoo, B., Chatterjee, C. & Raghuwanshi, N. S. (2020). Evaluation of simplified surface energy balance index (S-SEBI) method for estimating actual evapotranspiration in Kangsabati Reservoir Command using Landsat 8 imagery. Journal of the Indian Society of Remote Sensing, 48(10), 1421–1432. https://doi.org/10.1007/s12524-020-01166-9.
Li, Z. L., Tang, R., Wan, Z., Bi, Y., Zhou, C., Tang, B., Yan, G. & Zhang, X. (2009). A review of current methodologies for regional evapotranspiration estimation from remotely sensed data. Sensors, 9(5), 3801-3853. https://doi.org/10.3390/s90503801.
Alves, E.R.A., de Freita, I. G. F., Gomes, H. B. , Silva, F. D. & dos Santos, M. N.(2017). Using Landsat-8 images in the estimative of surface radiation balance. Journal of Hyperspectral Remote Sensing, 7(2), 91-100.
Makar R. S., Shahin Sahar A., El-Nazer Mostafa & Wheida Ali (2022). Development of a PCA-based land use/land cover classification utilizing Sentinel-2-time series. Middle East Journal of Agriculture Research, 11(2):630-637. https://doi.org/10.36632/mejar/2022.11.2.42.
Mondal, I., Thakura, S., Deb, A. & Dea, T. K. (2022). Application of the METRIC model for mapping evapotranspiration over the Sundarban Biosphere Reserve, India. Ecological Indicators, 136, 108553. https://doi.org/10.1016/j.ecolind.2022.108553
Rawata, K.S., Singh, S.K., Bala, A. & Szabo, S., (2019). Estimation of crop evapotranspiration through spatial distributed crop coefficient in a semi-arid environment. Agric. Water Manag., 213,922-933.https://doi.org/10.1016/j.agwat.2018.12.002.
Reyes-González, A., Kjaersgaard, J., Trooien, T., Reta-Sánchez, D. G., Sánchez-Duarte, J. I., Preciado-Range, P. & Fortis-Hernández, M. (2019). Comparison of leaf area index, surface temperature, and actual evapotranspiration estimated using the METRIC model and insitu measurements. Sensors, 19(8), 1857-1878. https://doi.org/10.3390/s19081857
Rodrigues, G.C. & Braga, R.P., (2021). Estimation of daily reference evapotranspiration from NASA POWER reanalysis products in a hot summer Mediterranean climate. Agronomy, 11, 2077-2091. https://doi.org/10.3390/agronomy11102077.
Roerink, G.J., 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, 25(2), 147-157. https://doi.org/10.1016/S1464-1909(99)00128-8
Rouse, J.W., R.H. Haas, J.A. Schell & D. W. Deering(1974). Monitoring vegetation systems in the Great Plains withERTS, In: S.C. Freden, E.P. Mercanti, and M. Becker (eds) Third Earth Resources Technology Satellite–1 Syposium. Volume I: Technical Presentations, NASA SP-351, NASA, Washington, D.C., pp. 309-317
Senay, G.B., Bohms, S., Singh, R.K., Gowda, P.H., Velpuri, N.M., Alemu, H. & Verdin, J.P. (2013). Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach. Journal of the American Water Resources Association (JAWRA), 49(3), 577–591. https://doi.org/10.1111/jawr.12057
Sobrino, J. A. & Raissouni, N., (2000). Toward remote sensing methods for land cover dynamic monitoring: application to Morocco. Int. J. Remote Sens., 21(2), 353-366. https://doi.org/10.1080/014311600210876.
Sobrino, J. A., El Kharraz, J. & Li, Z. L. (2003). Surface temperature and water vapour retrieval from MODIS data. International Journal of Remote Sensing,24 (24),5161-5182. https://doi.org/10.1080/0143116031000102502
Sobrino, J. A., Raissouni, N., Olioso, A., Hasager, C. B., Belaid, M., Abdel Rahman, S. & Chehbouni, A., (2001). WATERMED - Water use efficiency in natural vegetation and agricultural areas by Remote sensing in the Mediterranean basin. In IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217), 2001, pp. 3158-3160 vol.7, Sydney, Australia, 9–13 July, 2001. https://doi.org/10.1109/IGARSS.2001.978289.
Sobrino,J. A., Jiménez-Muñoz, J. C.,Sòria, G., and Romaguera, M.,Guanter, L., Moreno J., Plaza, A. & Martínez, P. (2008). Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE Transactions on Geoscince and Remote Sensing, 46(2), 316-327. https://doi.org/10.1109/TGRS.2007.904834.
Sobrino, J.A.; Souza daRocha, N., Skokovi´c, D.,SuélenKäfer, P., López-Urrea, R., Jiménez-Muñoz, J.C. & Alves Rolim, S.B. (2021). Evapotranspiration Estimation withthe S-SEBI Method from Landsat 8Data against LysimeterMeasurements at the Barrax Site,Spain. Remote Sens., 13: 3686-3703.https://doi.org/10.3390/rs13183686.
United States Geological Survey (2019). Landsat 8 (L8), Data Users Handbook. EROS Sioux Falls, South Dakota. LSDS-1574, Version 5.0. https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/atoms/files/LSDS-1574_L8_Data_Users_Handbook-v5.0.pdf.
Vozhehova R. A., Lavrynenko Y. O., Kokovikhin S. V., Lykhovyd P. V., Biliaieva I. M., Drobitko A. V. & Nesterchuk V. V. (2018). Assessment of the CROPWAT 8.0 software reliability for evapotranspiration and crop water requirements calcu-lations. Journal of Water and Land Development. 39, 147–152. https://doi.org/10.2478/jwld-2018-0070.
Issue
Section
Research Articles
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This work is licensed under Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) © Author (s)
How to Cite
Performance evaluation of Satellite-based actual evapotranspiration technique. (2022). Journal of Applied and Natural Science, 14(4), 1327-1336. https://doi.org/10.31018/jans.v14i4.3967
