Combination of satellite imagery with meteorological data for estimating reference evapotranspiration

D. Montero, F. Echeverry, F. Hernández

Abstract

The Food and Agriculture Organization of the United Nations (FAO) in its publication No. 56 of the Irrigation and Drainage Series presents the FAO Penman-Monteith procedure for the estimation of reference evapotranspiration from meteorological data, however, its calculation may be complicated in areas where there are no weather stations. This paper presents an evaluation of the potential of the Land Surface Temperature and Digital Elevation Models products derived from the MODIS and ASTER sensors, both on board the Terra EOS AM-1 satellite, for the estimation of reference evapotranspiration using the Penman-Monteith FAO-56, Hargreaves, Thornthwaite and Blaney-Criddle models. The four models were compared with the method proposed by FAO calculated with the observed data of a ground based meteorological station, finding a significant relation with the models Penman-Monteith FAO-56 and Hargreaves.


Keywords

Land surface temperature; MODIS; ASTER; reference evapotranspiration; FAO

Full Text:

PDF

References

Ackerman, S., Strabala, K., Menzel, P., Frey, R., Moeller, C., Gumley, L., Baum, B., Seemann, S., Zhang, H. 2006. Discriminating clear-sky from clouds with MODIS, Algorithm theoretical basis document (MOD35). Madison, Wisconsin: University of Wisconsin-Madison.

Allen, R. G., Pereira, L. S., Raes, D., Smith, M. 2006. Evapotranspiración del cultivo, Guías para la determinación de los requerimientos de agua de los cultivos. Roma: FAO.

Berti, A., Tardivo, G., Chiaudani, A., Rech, F., Borin, M. 2014. Assessing reference evapotranspiration by the Hargreaves method in north-eastern Italy. Agricultural Water Management, 140, 20–25. https://doi.org/10.1016/j.agwat.2014.03.015

Blaney, H. F., Criddle, W. D., 1950. Determining water requirements in irrigated areas from climatological and irrigation data. Washington, D.C.: U.S. Soil Conservation Service.

Byun, K., Waqas Liaqat, U., Choi, M. 2014. Dual-model approaches for evapotranspiration analyses over homo and heterogeneous land surface conditions. Agricultural and Forest Meteorology, 197, 169–187. https://doi.org/10.1016/j.agrformet.2014.07.001

Cai, J., Liu, Y., Lei, T., Santos Pereira, L. 2007. Estimating reference evapotranspiration with the FAO Penman–Monteith equation using daily weather forecast messages. Agricultural and Forest Meteorology, 145, 22–35. https://doi.org/10.1016/ j.agrformet.2007.04.012

Cervantes-Osornio, R., Arteaga-Ramírez, R., VázquezPeña, M. A., Ojeda-Bustamante, W., QuevedoNolasco, A. 2013. Modelos Hargreaves PriestleyTaylor y redes neuronales artificiales en la estimación de la evapotranspiración de referencia. Ingeniería Investigación y Tecnología, 14(2), 163-176. https://doi.org/10.1016/S1405-7743(13)72234-0

Cruz-Blanco, M., Gavilán, P., Santos, C., Lorite, I. J. 2014. Assessment of reference evapotranspiration using remote sensing andforecasting tools under semi-arid conditions. International Journal of Applied Earth Observation and Geoinformation, 33, 280–289. https://doi.org/10.1016/j.jag.2014.06.008

Djaman, K., Balde, A. B., Sow, A., Muller, B., Irmak, S., N’Diaye, M. K., Manneh, B., Moukoumbi, Y. D., Futakuchi, K., Saito, K. 2015. Evaluation of sixteen reference evapotranspiration methods under sahelian conditions in the Senegal River Valley. Journal of Hydrology: Regional Studies, 3, 139– 159. https://doi.org/10.1016/j.ejrh.2015.02.002

Doorenbos, J., Pruitt, W. O. 1977. Guidelines for predicting crop water requirements. Roma: FAO.

Gavilán, P., Lorite, I. J., Tornero, S., Berengena, J. 2006. Regional calibration of Hargreaves equation for estimating reference ET in a semiarid environment. Agricultural Water Management, 81(3), 257–281. https://doi.org/10.1016/j.agwat.2005.05.001

Gesch, D., Oimoen, M., Zhang, Z., Danielson, J., Meyer, D. 2012. Validation of the ASTER Global Digital Elevation Model (GDEM) Version 2 over the Conterminous United States. U.S. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B4. Melbourne, Australia, 15 Agosto – 1 Septiembre. pp 281-286. https://doi.org/10.5194/isprsarchives-XXXIX-B4-281-2012

Hargreaves, G., Samani, Z. 1982. Estimating potential evapotranspiration. Journal of the Irrigation and Drainage Division, 108(3), 225-230.

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

Jabloun, M., Sahli, A. 2008. Evaluation of FAO56 methodology for estimating reference evapotranspiration using limited climatic data Application to Tunisia. Agricultural Water Management, 95(6), 707-715. https://doi.org/ 10.1016/j.agwat.2008.01.009

Kashyap, P. S., Panda, R. K. 2001. Evaluation of evapotranspiration estimation methods and development of crop coefficients for potato crop in a sub-humid region. Agricultural Water Management, 50(1), 9-25. https://doi.org/10.1016/S0378- 3774(01)00102-0

López-Urrea, R., Martín de Santa Olalla, F., Fabeiro, C., Moratalla, A. 2006. Testing evapotranspiration equations using lysimeter observations in a semiarid climate. Agricultural Water Management, 85, 15-26. https://doi.org/10.1016/j.agwat.2006.03.014

Maeda, E. E., Wiberg, D. A., Pellikka, P. K. E. 2011. Estimating reference evapotranspiration using remote sensing and empirical models in a region with limited ground data availability in Kenya. Applied Geography, 31, 251-258. https://doi.org/10.1016/j.apgeog.2010.05.011

Manesh, S. S., Ahani, H., Rezaeian-Zadeh, M. 2014. ANN-based mapping of monthly reference crop evapotranspiration by using altitude, latitude and longitude data in Fars province, Iran. Environment, Development and Sustainability, 16(1), 103–122. https://doi.org/10.1007/s10668-013-9465-x

Martínez-Cob, A., Tejero-Juste, M. 2004. A windbased qualitative calibration of the Hargreaves ET0 estimation equation in semiarid regions. Agricultural Water Management, 64(3), 251–264. https://doi.org/10.1016/S0378-3774(03)00199-9

Maselli, F., Papale, D., Chiesi, M., Matteucci, G., Angeli, L., Raschi, A., Seufert, G. 2014. Operational monitoring of daily evapotranspiration by the combination of MODIS NDVI and ground meteorological data: Application and evaluation in Central Italy. Remote Sensing of Environment, 152, 279–290. https://doi.org/10.1016/j.rse.2014.06.021

Meyer, D. J., Tachikawa, T., Abrams, M., Crippen, R., Krieger, T., Gesch, D., Carabajal, C. 2012. Summary of the validation of the second version of the ASTER GDEM. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B4. Melbourne, Australia, 15th August – 1st September. pp 291-293. https://doi.org/10.5194/isprsarchivesXXXIX-B4-291-2012

Mildrexler, D. J., Zhao, M., Running, S. W. 2011. A global comparison between station air temperatures and MODIS land surface temperatures reveals the cooling role of forests. Journal Of Geophysical Research, 116, 1-15. https://doi.org/10.1029/2010JG001486

Nolan, R. H., Resco de Dios, V., Boer, M. M., Caccamo, G., Goulden, M. L., Bradstock, R. A. 2016. Predicting dead fine fuel moisture at regional scales using vapour pressure deficit from MODIS and gridded weather data. Remote Sensing of Environment, 174, 100–108. https://doi.org/10.1016/j.rse.2015.12.010

Rahimikhoob, A., Hosseinzadeh, M. 2014. Assessment of Blaney-Criddle Equation for Calculating Reference Evapotranspiration with NOAA/AVHRR Data. Water Resour Manage, 28(10), 3365–3375. https://doi.org/10.1007/s11269-014-0670-7

Sánchez, M., Chuvieco, E. 2000. Estimación de evapotranspiración del cultivo de referencia, ETo , a partir de imágenes NOAA-AVHRR. Revista de Teledetección, 14, 1-10. Available at: http://www.aet.org.es/?q=revista14-2 [Last access: June 2018].

Sentelhas, P. C., Gillespie, T. J., Santos, E. A. 2010. Evaluation of FAO Penman–Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada. Agricultural Water Management, 97(5), 635–644. https://doi.org/10.1016/j.agwat.2009.12.001

Thornthwaite, C. W. 1948. An Approach toward a Rational Classification of Climate. Geographical Review, 38(1), 55-94. https://doi.org/10.2307/210739

Todorovic, M., Karic, B., Pereira, L. S. 2013. Reference evapotranspiration estimate with limited weather data across a range of Mediterranean climates. Journal of Hydrology, 481, 166–176. https://doi.org/10.1016/j.jhydrol.2012.12.034

Valencia, J. M., García, C. E., Montero, D. 2017. Anomalías de vegetación asociadas con el fenómeno del ENOS en el valle geográfico del río Cauca, Colombia. Revista de Teledetección, 50, 89-99. https://doi.org/10.4995/raet.2017.7715

Vicente-Serrano, S. M., Azorin-Molina, C., SanchezLorenzo, A., Revuelto, J., López-Moreno, J. I., González-Hidalgo, J. C., Morán-Tejadam E., Espejo, F. 2014. Reference evapotranspiration variability and trends in Spain, 1961–2011. Global and Planetary Change, 121, 26–40. https://doi.org/10.1016/j.gloplacha.2014.06.005

Walter, I. A., Allen, R. G., Elliott, R., Jensen, M., Itenfisu, D., Mecham, B., Howell, T., Snyder, R., Brown, P., Echings, S., Spofford, T., Hattendorf, M., Cuenca, R. H., Wright, J. L., Martin, D. 2000. ASCE Standarized Reference Evapotranspiration Equation. In: Watershed Management and Operations Management 2000. Fort Collins, Colorado, U.S., june 20-24. pp 1-11. https://doi.org/10.1061/40499(2000)126

Zipper, S. C., Loheide, S. P. 2014. Using evapotranspiration to assess drought sensitivity on a subfield scale with HRMET, a high resolution surface energy balance model. Agricultural and Forest Meteorology, 197, 91–102. https://doi.org/10.1016/j.agrformet.2014.06.009

Zhu, W., Lü, A., Jia, S. 2013. Estimation of daily maximum and minimum air temperature using MODIS land surface temperature products. Remote Sensing of Environment, 130, 62–73. https://doi.org/10.1016/j.rse.2012.10.034

Abstract Views

1997
Metrics Loading ...

Metrics powered by PLOS ALM




 

This journal is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

Universitat Politècnica de València

Official Journal of the Spanish Association of Remote Sensing

e-ISSN: 1988-8740    ISSN: 1133-0953           https://doi.org/10.4995/raet