Abstract
Actual evapotranspiration (ETa) represents crop water consumption in consideration, the water conserved in plant tissue structure representing about 1% or less. Many researchers understood the importance of ETa, and they did their best to measure or calculate ETa. Tens of experimental and mathematical models were used to calculate evapotranspiration in last century. Many weather, plant, and soil parameters were inserted in these models. Most of these models were acceptable for local scale and used for certain climate. Only a very few models were used on a global scale but need a lot of parameters and well-distributed weather stations. The crop pattern was the main obstacle to using these models on a large scale. The early satellite age was the beginning of the development of global-scale models through using satellite images to calculate ETa and manage crop water consumption. Triangle and crop water stress index (CWSI) methods were used and developed in the 1970s and the 1980s, respectively. In 1990s and beginning of 2000s, the SEBAL and SEBS models represent a new step in the way of evapotranspiration development models. In the last decade, METRIC, ETLook, Alexi, and ET watch models were developed to fill the gaps of SEBAL and SEBS models. Researchers around the world still try to modify these models to improve the results.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Buffum BC (1892) Irrigation and duty of water. Wyo Agric Exp Bull 8
Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration: guidelines for computing crop water requirements. United Nations Food and Agriculture Organization, irrigation and drainage paper no. 56. FAO, Rome
Lebon E, Dumas V, Pieri P, Schultz HR (2003) Modelling the seasonal dynamics of the soil water balance of vineyards. Funct Plant Biol 30(6):699–710
El-Shirbeny MA, Aboelghar MA, Arafat SM, El-Gindy AGM (2014) Assessment of the mutual impact between climate and vegetation cover using NOAA-AVHRR and Landsat data in Egypt. Arab J Geosci 7(4):1287–1296
El-Shirbeny MA, Saleh NH, Ali AM (2014) Estimation of potential crop evapotranspiration using remote sensing techniques. In: Proceedings of the 10th international conference of AARSE, pp 460–468
Hu G, Jia L, Menenti M (2015) Comparison of MOD16 and LSA-SAF MSG evapotranspiration products over Europe for 2011. Remote Sens Environ 156:510–526
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
Rwasoka DT, Gumindoga W, Gwenzi J (2011) Estimation of actual evapotranspiration using the Surface Energy Balance System (SEBS) algorithm in the Upper Manyame catchment in Zimbabwe. Phys Chem Earth 36:736–746
Tadesse T, Senay GB, Berhan G, Regassa T, Beyen S (2015) Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: a case study for Ethiopia. Int J Appl Earth Obs Geoinf 40:39–54
Wojtowicz M, Wojtowicz A, Piekarczyk J (2016) Application of remote sensing methods in agriculture. Commun Biometry Crop Sci 11:31–50
Oki T, Kanae S (2006) Global hydrological cycles and world water resources. Science 313:1068–1072
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
Ghulam A, Li Z, Qin Q, Yimit h, Wang J (2008) Estimating crop water stress with ETM+ NIR and SWIR data. Agric For Meteorol 148:1679–1695
Tasumi M, Allen RG (2007) Satellite-based ET mapping to assess variation in ET with timing of crop development. Agric Water Manag 88:54–62
Choudhury BJ (1997) Global pattern of potential evaporation calculated from the Penman Monteith equation using satellite and assimilated data. Remote Sens Environ 61(1):64–81
Moran MS, Clarke TR, Inoue Y, Vidal A (1994) Estimating crop water deficit using the relation between surface air temperature and spectral vegetation index. Remote Sens Environ 49:246–263
Bastiaanssen WGM, Roest CWJ, Pelgrum H, Abdel Khalek MA (1992) Monitoring of the irrigation performance on the basis on actual evapotranspiration: comparison of satellite data and simulation model results. In: Feyen J, Mwendera E, Badji M (eds) Advances in planning, design and management of irrigation systems as related to sustainable land use. Center for Irrigation Engineering and ECOWARM, Leuven, pp 473–483
Dibella CM, Rebella CM, paruelo JM (2000) Evapotranspiration estimates using NOAA AVHRR imagery in the Pampa region of Argentina. Int J Remote Sens 21(4):791–797
Ray SS, Dadhwal VK (2001) Estimation of evapotranspiration of irrigation command area using remote sensing and GIS. Agric Water Manag 49:239–249
Kerdiles H, Groundena M, Rodrignes R, Seguin B (1996) Forest mapping using NOAA-AVHRR data in the Pampean region, Argentina. Agric For Meteorol 79:157–182
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
Alderfasi AA, Nielsen DC (2001) Use of crop water stress index for monitoring water status and scheduling irrigation in wheat. Agric Water Manag 47(1):69–75
Li L, Nielsen DC, Yu Q, Ma L, Ahuja LR (2010) Evaluating the crop water stress index and its correlation with latent heat and CO2 fluxes over winter wheat and maize in the North China plain. Agric Water Manag 97(8):1146–1155
Méndez-Barroso LA, Garatuza-Payán J, Vivoni ER (2008) Quantifying water stress on wheat using remote sensing in the Yaqui Valley, Sonora, Mexico. Agric Water Manag 95(6):725–736
Yuan G, Luo Y, Sun X, Tang D (2004) Evaluation of a crop water stress index for detecting water stress in winter wheat in the North China Plain. Agric Water Manag 64:29–40
Jackson RD, Idso SB, Reginato RJ, Pinter JR (1981) Canopy temperature as a crop water stress indicator. Water Resour 17:1133–1138
Choudhury BJ (1983) Simulating the effects of weather variables and soil water potential on a corn crop canopy temperature. Agric Meteorol 29:169–182
Hiler EA, Clark RN (1971) Stress day index to characterize effects of water stress on crop yields. Transa Hydrol (210-VI-NEH)
Erdem Y, Sehirali S, Erdem T, Kenar D (2006) Determination of crop water stress index for irrigation scheduling of bean (Phaseolus vulgaris L.). Turk J Agric For 30:195–202
Garcia M, Fernández N, VillagarcÃa L, Domingo F, Puigdefábregas J, Sandholt I (2014) Accuracy of the temperature–vegetation dryness index using MODIS under water-limited vs. energy-limited evapotranspiration conditions. Remote Sens Environ 149:100–117
Clarke TR (1997) An empirical approach for detecting crop water stress using multi-spectral airborne sensors. Horticult Technol 7:9–16
El-Shirbeny MA, Ali AM, Mohamed ES, Abutaleb K, Bauomy EM (2017) Monitoring of actual evapotranspiration using remotely sensed data under modern irrigation systems. J Geograph Environ Earth Sci Int 12(4):1–12
Rana G, Katerji N (2000) Measurement and estimation of actual evapotranspiration in the field under Mediterranean climate: a review. Eur J Agron 13:125–153
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 consumption of wheat crops in semi-arid regions. Agric Water Manag 87:41–54
Dardanelli JL, Ritchie JT, Calmon M, Andrianiand JM, Collino DJ (2004) An empirical model for root water uptake. Field Crop Res 87:59–71
Kustas WP, Norman JM (1999) Evaluation of soil and vegetation heat flux predictions using a simple twosource model with radiometric temperatures for partial canopy cover. Agric For Meteorol 94:13–29
Kiehl JT, Trenberth KE (1997) Earth’s annual global mean energy budget. Bull Am Meteorol Soc 78:197–208
Su Z (2002) The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrol Earth Syst Sci 6(1):85–99
Bastiaanssen WGM, Menenti M, Feddes RA, Holtslag AAM (1998) A remote sensing surface energy balance algorithm for land (SEBAL) 1. Formulation. J Hydrol 212–213:198–212
Bastiaanssen WGM, Pelgrum J, Wang YM, Moreno JF, Roerink GJ, van der Wal T (1998) A remote sensing surface energy balance algorithm for land (SEBAL) Part 2: validation. J Hydrol 212–213:213–229
Bastiaanssen WGM (2000) SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. J Hydrol (Amst) 229:87–100
Allen RG, Tasumi M, Trezza R (2007) Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) model. J Irrig Drain Eng 133(4):380–393
Wu BF, Xiong J, Yan N (2008) ETWatch for monitor regional evapotranspiration with remote sensing. Adv Water Sci 19(5):671–678
Wu BF, Xiong J, Yan N (2011) ETWatch: models and methods. J Remote Sens 15(2):224–230
Menenti M, Choudhury B (1993) Parameterization of land surface evaporation by means of location dependent potential evaporation and surface temperature range. In: Bolle HJ, Feddes RA, Kalma JD (eds) Exchange processes at the land surface for a range of space and time scales, vol 212. IAHS, Oxfordshire, pp 561–568
Verhoef W (1996) Application of harmonic analysis of NDVI time series (HANTS). In: Azzali S, Menenti M (eds) Fourier analysis of temporal NDVI in the Southern African and American continents. DLO Win and Staring Centre, Report, 108, Wageningen, pp 19–24
Pelgrum H (1992) Mapping areal surface energy balances during daytime using Meteosat data. Internal note 195. DLO Winand Staring Centre, Wageningen, p 50
Abdel-Gawad ST, Abdel Khalek MA, Boels D, El-Quosy DE, Roest CWJ, Rijtema PE, Smit MFR (1991) Analysis of water management in the Eastern Nile Delta. Reuse Report 30. DLO Winand Staring Center, Wageningen, p 245
Mu Q, Zhao M, Running SW (2011) Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens Environ 115(8):1781–1800
Mu Q, Heinsch FA, Zhao M, Running SW (2007) Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote Sens Environ 111:519–536
Monteith JL (1965) Evaporation and environment. In: Fogg BD (ed) The state and movement of water in living organism, symposium of the society of experimental biology, vol 19. Cambridge University Press, Cambridge, pp 205–234
El-Shirbeny MA, Alsersy MAM, Saleh NH, Abu-Taleb KA (2015) Changes in irrigation water consumption in the Nile Delta of Egypt assessed by remote sensing. Arab J Geosci 8:10509–10519
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
El-Shirbeny, M.A., Mohamed, E.S., Negm, A. (2018). Estimation of Crops Water Consumptions Using Remote Sensing with Case Studies from Egypt. In: Negm, A.M. (eds) Conventional Water Resources and Agriculture in Egypt. The Handbook of Environmental Chemistry, vol 74. Springer, Cham. https://doi.org/10.1007/698_2018_305
Download citation
DOI: https://doi.org/10.1007/698_2018_305
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-95064-8
Online ISBN: 978-3-319-95065-5
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)