Evaluation of two models using CERES data for reference evapotranspiration estimation

F. Carmona, M. Holzman, R. Rivas, M.F. Degano, E. Kruse, M. Bayala


Evapotranspiration is the most important variable in the Pampas plain. Information provided by sensors onboard satellite missions allows represent the spatial and temporal variability of evapotranspiration, which cannot be achieved using only measurements of weather stations. In this work, the Priestley and Taylor (PT) and FAO Penman Monteith (FAO PM) equations were adapted to estimate the reference evapotranspiration, ET0 , using only CERES satellite products (SYN1 and CldTypHist). In order to evaluate the reference evapotranspiration from CERES, a comparison with in situ measurements was conducted. We used ET data provided by the Oficina de Riesgo Agropecuario, corresponding to 24 stations placed in the Pampean Region of Argentina (2001-2016). Results showed very good agreement between the estimates with CERES products and in situ values, with errors between ±0.8 and ±1.1 mm d–and r2  greater than 0.75  at daily scale, and errors between ±14  and ±19  mm month–1  and r2   greater than 0.9, at monthly scale better results were obtained with adapted model FAO PM than PT. Finally, ET0 monthly maps for the Pampean Region of Argentina were elaborated, which allowed knowing the temporal-spatial variation in the validation area. In conclusion, the methods presented here are a suitable alternative to estimate the reference evapotranspiration without requiring ground measurements.


CERES; remote sensing; reference evapotranspiration

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Aliaga, V.S., Ferrelli, F., Piccolo, M.C. 2017. Regionalization of climate over the Argentine Pampas. International Journal of Climatology, 37, 1237-1247. https://doi.org/10.1002/joc.5079

Allen R.G., Tasumi M., Trezza R. 2007. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) - model. J. Irrig. Drain. Eng. ASCE, 133, 380-394. https://doi. org/10.1061/(ASCE)0733-9437(2007)133:4(380)

Allen, R.G., Pereira, L.S., Raes, D., Smith, M. 1998. FAO Irrigation and Drainage Paper No. 56: Crop Evapotranspiration. (F.W. Resources, Ed.), Irrigation and Drainage. Fao. Retrieved from http://www.kimberly.uidaho.edu/water/fao56/ fao56.pdf

Anderson M.C., Norman J.M., Diak G.R., Kustas W.P., Mecikalski J.R. 1997. A twosource time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sens Environ, 60, 195-216. https://doi.org/10.1016/S0034-4257(96)00215-5

ASCE - EWRI. 2005. The ASCE standardized reference evapotranspiration equation. ASCE-EWRI Standardization of Reference Evapotranspiration Task Comm. Report, January, 2005. http:// www.kimberly.uidaho.edu/water/asceewri/ ascestzdetmain2005.pdf.

Bastiaanssen W.G.M., Menenti M., Feddes R.A., Holtslag A.A.M. 1998. A remote sensing surface energy balance algorithm for land (SEBAL): 1. Formulation. J. Hydrol, 212-213, 198-212. https://doi.org/10.1016/S0022-1694(98)00253-4

Carmona, F., Rivas, R., Ocampo, D., Schirmbeck, J., Holzman, M. 2011. Sensores para la medición y validación de variables hidrológicas a escalas local y regional a partir del balance de energía. Aqua-LAC, Revista del programa hidrológico internacional para América Latina y el Caribe, 3, 26-36.

Carmona, F., Rivas, R., Caselles, V. 2013. Estimate of the alpha parameter in an oat crop under rain-fed conditions. Hydrological Processes, 27(19), 2834- 2839. https://doi.org/10.1002/hyp.9415

Carmona, F., Rivas, R., Kruse, E. 2017. Estimating daily net radiation in the FAO Penman-Monteith method. Theoretical and Applied Climatology, 129(1-2), 89- 95. https://doi.org/10.1007/s00704-016-1761-6

Carmona, F., Orte, P.F., Rivas, R., Wolfram, E., Kruse, E. 2017. Development and Analysis of a New Solar Radiation Atlas for Argentina from Ground-Based Measurements and CERES_SYN1deg data. Egyptian Journal of Remote Sensing and Space Science. (In press). https://doi.org/10.1016/j.ejrs.2017.11.003

Degano, M.F. 2017. Evaluación del producto de evapotranspiración global MOD16 con medidas in situ en la región de la Pampa Húmeda, Argentina. Tesis de Maestría. Repositorio DigitalCIC. Facultad de Física, Universidad de Valencia. Disponible en https://digital.cic.gba.gob.ar/ handle/11746/7085

Degano F., Rivas R., Sánchez Tomás J.M., Carmona F., Niclós R. 2018. Assessment of the Potential Evapotranspiration MODIS Product Using Ground Measurements in the Pampas. Proceedings of the 2018 IEEE ARGENCON conference. https://doi.org/10.1109/ARGENCON.2018.8646143

Fisher J.B., Tu K.P., Baldocchi D.D. 2008. Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUX- NET sites. Remote Sens. Environ., 112, 901-919. https://doi.org/10.1016/j.rse.2007.06.025

Hashimoto, H., Dungan, J.L., White, M.A., Yang, F., Michaelis, A.R., Running, S.W., Nemani, R.R. 2008. Satellite-based estimation of surface vapor pressure deficits using MODIS land surface temperature data. Remote Sensing of Environment, 112(1), 142-155. https://doi.org/10.1016/j.rse.2007.04.016

Jensen, M., Burman, R., Allen, R. 1990. Evapotranspiration and irrigation water requirements. Am Soc Civ Eng (ASCE) Manual 70, 332.

Jiang L., Islam S. 2001. Estimation of surface evaporation map over southern Great Plains using remote sensing data. Water Resour. Res., 37, 329-340. https://doi.org/10.1029/2000WR900255

Jiang, B., Liang, S., Ma, H., Zhang, X., Xiao, Z., Zhao, X., Jia, K., Yao, Y., Jia, A. 2016. GLASS daytime allwave net radiation product: Algorithm development and preliminary validation. Remote Sensing, 8(3), 222. https://doi.org/10.3390/rs8030222

Kitoh, A., Kusunoki, S., Nakaegawa, T. 2011. Climate change projections over South America in the late 21st century with the 20 and 60 km mesh Meteorological Research Institute atmospheric general circulation model (MRI-AGCM). Journal of Geophysical Research Atmospheres, 116(6), 1-21. https://doi.org/10.1029/2010JD014920

Long D., Longuevergne L., Scanlon B.R. 2014. Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites. Water Resour. Res., 50, 1131-1151. https://doi.org/10.1002/2013WR014581

Martínez, G., Gutiérrez, M.A., Messineo, P.G., Kaufmann, C.A., Rafuse, D.J. 2016. Subsistence strategies in Argentina during the late Pleistocene and early Holocene. Quaternary Science Reviews, 144, 51-65. https://doi.org/10.1016/j.quascirev.2016.05.014

Miralles D.G., Holmes T.R.H., De Jeu R.A.M., Gash J.H., Meesters A.G.C.A., Dolman A.J. 2011. Global land-surface evaporation estimated from satellitebased observations. Hydrol. Earth Syst Sci., 15, 453-469. https://doi.org/10.5194/hess-15-453-2011

Mu Q., Heinsch F.A., Zhao M., Running S.W. 2007. Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote. Sens. Environ., 111, 519-536. https://doi.org/10.1016/j.rse.2007.04.015

Mu Q.Z., Zhao M.S., Running S.W. 2011. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens Environ, 115, 1781-1800. https://doi.org/10.1016/j.rse.2011.02.019

Nishida K., Nemani R.R., Glassy JM, Running S.W. 2003. Development of an evapotranspiration index from aqua/MODIS for monitoring surface moisture status. IEEE Trans Geosci. Remote Sens., 41, 493- 501. https://doi.org/10.1109/TGRS.2003.811744

Ocampo, D., Rivas, R. 2013. Estimación de la radiación neta diaria a partir de Modelos de Regresión Lineal Múltiple. Revista Chapingo, Serie Ciencias Forestales y del Ambiente, 19(2), 263-271. https://doi.org/10.5154/r.rchscfa.2012.04.031

Penman, H.L. 1948. Natural Evaporation from Open Water, Bare Soil and Grass. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 193(1032), 120-145. https://doi.org/10.1098/rspa.1948.0037

Pereyra, F. 2003. Ecorregiones de la Argentina. SEGEMAR. ISSN 0328-2325.

Priestley, C.H.B., Taylor, R.J. 1972. On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters. Monthly Weather Review, 100(2), 81-92. https://doi.org/10.1175/1520- 0493(1972)100%3C0081:OTAOSH%3E2.3.CO;2

Rivas, R.E., Carmona, F. 2013. Evapotranspiration in the Pampean Region using field measurements and satellite data. Physics and Chemistry of the Earth, Parts A/B/C, 55-57, 27-34. https://doi.org/10.1016/j.pce.2010.12.002

Rivas, R., Caselles, V. 2004. A simplified equation to estimate spatial reference evaporation from remote sensing-based surface temperature and local meteorological data. Remote Sensing of Environment, 93, 68-76. https://doi.org/10.1016/j.rse.2004.06.021

Sánchez, J.M., Scavone, G., Caselles, V., Valor, E., Copertino, V.A., Telesca, V. 2008. Monitoring daily evapotranspiration at a regional scale from LandsatTM and ETM+ data: Application to the Basilicata region. Journal of Hydrology, 351(1-2), 58-70. https://doi.org/10.1016/j.jhydrol.2007.11.041

Scian, B., Labraga, J.C., Reimers, W., Frumento, O. 2006. Characteristics of large-scale atmospheric circulation related to extreme monthly rainfall anomalies in the Pampa region, Argentina, under non-ENSO conditions. Theoretical and Applied Climatology, 85(1-2), 89-106. https://doi.org/10.1007/s00704-005-0182-8

Smith, G.L., Priestley, K.J., Loeb, N.G., Wielicki, B.A., Charlock, T.P., Minnis, P., Doelling, D.R., Rutan, D.A. 2011. Clouds and Earth Radiant Energy System (CERES), a review: Past, present and future. Advances in Space Research, 48(2), 254-263. https://doi.org/10.1016/j.asr.2011.03.009

Soegaard, H., Boegh, E. 1995. Estimation of evapotranspiration from a millet crop in the Sahel combining sap flow, leaf area index and eddy correlation technique. Journal of Hydrology, 166(3-4), 265-282. https://doi.org/10.1016/0022-1694(94)05094-E

Tang Q.H., Peterson S., Cuenca R.H., Hagimoto Y., Lettenmaier D.P. 2009. Satellite-based nearreal-time estimation of irrigated crop water consumption. J. Geophys. Res. Atmos., 114, D05114. https://doi.org/10.1029/2008JD010854

Wan Z., Zhang K., Xue X.W., Hong Z., Hong Y., Gourley J.J. 2015. Water balance based actual evapotranspi- ration reconstruction from ground and satellite obser- vations over the Conterminous United States. Water Resour. Res., 51, 6485-6499. https://doi.org/10.1002/2015WR017311

Wang K.C., Wang P., Li Z.Q., Cribb M., Sparrow M. 2007. A simple method to estimate actual evapotranspiration from a combination of net radiation, vegetation index, and temperature. J. Geophys. Res. Atmos., 112, D15107. https://doi.org/10.1029/2006JD008351

Zeng Z.Z., Piao S.L., Lin X., Yin G.D., Peng S.S., Ciais P., Myneni R.B. 2012. Global evapotranspiration over the past three decades: estimation based on the water balance equation combined with empirical models. Environ. Res. Lett., 7, 014026, https://doi.org/10.1088/1748-9326/7/1/014026.

Zhang K., Kimball J.S., Mu Q., Jones L.A., Goetz S.J., Running S.W. 2009. Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005. J. Hydrol., 379, 92-110. https://doi.org/10.1016/j.jhydrol.2009.09.047

Zhang, K., Kimball, J.S., Running, S.W. 2016. A review of remote sensing based actual evapotranspiration estimation. WIREs Water, 3, 834-853. https://doi.org/10.1002/wat2.1168

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