Evaporation process study through in situ and remote sensing data at Tres Quebradas Salt flat

F. Carmona, R. Rivas, A.M.G. Faramiñán, C. Mancino, M. Bayala, W. Perez


The calculation of evaporation (Ev) is a fundamental process on the planning of investment for nonmetallic mining in salt flats. Dispose to reliable estimates of evaporation allows to reduce one of the main uncertainties of the flow models in this type of basin. This paper focuses on the calculation of Ev in the Tres Quebradas salt flat, Catamarca (Argentina), applying Priestley-Taylor model whit satellite data. Study area comprises the Tres Quebradas and Verde lagoons, and a central evaporite zone. Satellite data (CERES and OLI-LandSat 8), meteorological information, brine density measurements, evaporation measurements, and spectral signatures to calculations were used. The lagoons evaporation was estimated and by means of a Class A evaporation pan validated. The evaporation control in evaporite zones also was studied using a phreatic level function. Ev values of 1302 mm year–1 and 1249 mm year–1 for the Tres Quebradas and Verde lagoons were obtained, respectively, similar to Class A evaporation pan values measured. In the case of evaporite zones, an average annual value of 152 mm year–1 was estimated, regulated by the phreatic level. In summary, an average annual of system water loss by evaporation of 1.31±0.32 m3 s–1 was obtained, where more than 80% corresponds to the Tres Quebradas and Verde lagoons, and the rest to the central evaporite zone. The results achieved are consistent and will be used as input data in the numerical flow modeling to the estimation of the lithium brine reserve of the salt flats.


evapotranspiration; CERES; brine; evaporites

Full Text:



Allen, R.G., Pereira, L.S., Raes, D., Smith, M. 1998. FAO Irrigation and Drainage Paper. p. 56. Crop evapotranspiration. Guidelines for computing crop water requirements. Food and Agricultural Organization of the United Nations, Rome. pp. 65.

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. ASCE, 133(4), 380-394. https://doi.org/10.1061/ (ASCE)0733-9437(2007)133:4(380)

Anderson, M.C., Norman, J.M., Diak, G.R., Kustas, W.P., Mecikalski, J.R. 1997. A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote sensing of environment, 60(2), 195-216. https://doi.org/10.1016/S0034-4257(96)00215-5

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. Journal of hydrology, 212- 213:198-212. https://doi.org/10.1016/S0022- 1694(98)00253-4

Cardoso-Fernandes, J., Teodoro, A.C., Lima, A. 2019. Remote sensing data in lithium (Li) exploration: A new approach for the detection of Li-bearing pegmatites. International Journal of Applied Earth Observation and Geoinformation, 76, 10-25. https://doi.org/10.1016/j.jag.2018.11.001

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., Caselles, V. 2015. Development of a general model to estimate the instantaneous, daily, and daytime net radiation with satellite data on clear-sky days. Remote Sensing of Environment. 171, 1-13. https://doi.org/10.1016/j.rse.2015.10.003

Carmona, F., Orte, P. F., Rivas, R., Wolfram, E., Kruse, E. (2018a). Development and Analysis of a New Solar Radiation Atlas for Argentina from GroundBased Measurements and CERES_SYN1deg data. Egyptian Journal of Remote Sensing and Space Science, 21(3), 211-217. https://doi.org/10.1016/j. ejrs.2017.11.003

Carmona, F., Holzman, M., Rivas, R., Degano, F., Kruse, E., Bayala, M. (2018b). Evaluación de dos modelos para la estimación de la evapotranspiración de referencia con datos CERES. Revista de Teledetección, 51, 87-98. https://doi.org/10.4995/raet.2018.9259

Dinku, T, Funk, C, Peterson, P, Maidment, R., Tadesse, T., Gadain, H., Ceccato, P. 2018. Validation of the CHIRPS satellite rainfall estimates over eastern Africa. Quarterly Journal of the Royal Meteorological Society, 144(Suppl. 1), 292- 312. https://doi.org/10.1002/qj.3244

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 Sensing of Environment, 112(3), 901-919. https://doi.org/10.1016/j.rse.2007.06.025

Grilli, A., Vidal, F. 1986. Evaporación desde Salares: Metodología para Evaluar los Recursos Hídricos Renovables. Aplicación en las Regiones I y II. Revista de la Sociedad Chilena de Ingeniería Hidráulica, V1, N° 2.

Harbaugh, A., Banta, E., Hill, M., Mcdonald. M. 2000 MODFLOW-2000. The U. S. Geological Survey modular ground-water model-user guide to modularization concepts and the ground-water flow process. US Geol. Survey. https://doi.org/10.3133/ ofr200092

Ide, F. 1978. Cubicación del yacimiento salar de Atacama. Memoria de Título (Inédito), Universidad de Chile, Departamento de Minas, 144 p.

IHLLA, (2018a). Flow numerical modeling and simulation of exploitation scenarios in Salar de Tres Quebradas, Fiambalá, Catamarca, Argentina. Informe Inédito, para LIEX S.A.

IHLLA. (2018b). Informe de las actividades de campo Salar 3Q. Informe Inédito, para LIEX S.A.

Jiang, L., Islam, S. 2001. Estimation of surface evaporation map over southern Great Plains using remote sensing data. Water resources research, 37(2), 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

Kampf, S.K., Tyler, S.T. 2006. Spatial characterization of land surface energy fluxes and uncertainty estimation at the Salar de Atacama, Northern Chile. Advances in Water Resources, 29(2), 336-354. https://doi.org/10.1016/j.advwatres.2005.02.017

Long, D., Longuevergne, L., Scanlon, B.R. 2014. Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites. Water Resources Research, 50(2), 1131-1151. https://doi.org/10.1002/2013WR014581

Manrique, A. 2014. Explotación del litio, producción y comercialización de baterías de litio en Argentina. - 1a ed. - Mar del Plata: Universidad Nacional de Mar del Plata, 2014. E-Book. ISBN 978-987-544-641-0 1. Ingeniería. I. Título CDD 620, 111 pp.

Mardones, L. 1986. Características geológicas e 1idrogeológicas del salar de Atacama. In: El litio, un nuevo recurso para Chile, (Lagos, G.; editor). Universidad de Chile, Departamento de Ingeniería en Minas, Editorial Universitaria, p. 181-216.

Mardones, L. 1998 Flux et évolution des solutions salines dans les systèmes hydrologiques des salars d’Ascotan et d’Atacama. PhD Thesis, University of Paris, Paris, France.

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 satellite-based observations. Hydrology and Earth System Sciences, 15, 453-469. https://doi.org/10.5194/hess-15-453-2011

Morel-Seytoux, H., Mermoud, A. 1989. Modèlisation et observation du flux hydrique vers la surface du sol depuis une nappe peu profonde. Hydrologie Continentale, 4(1), 11-23.

Mu, Q.Z., Zhao, M.S., Running, S.W. 2011. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sensing of Environment, 115(8), 1781-1800. https://doi. org/10.1016/j.rse.2011.02.019

Niclos, R., Rivas, R., García-Santos, V., Doña, C., Valor, E., Holzman, M., Bayala, M., Carmona, F., Ocampo, D., Soldano, A., Thibeault, M. 2016. SMOSMIRAS level 2 Soil Moisture Product Validation in croplands of the Pampean Region of Argentina. IEEE Transactions on Geoscience and Remote Sensing, 54(1), 499-512. https://doi.org/10.1109/ TGRS.2015.2460332

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 Transactions on Geoscience and Remote Sensing, 41, 493-501. https://doi.org/10.1109/TGRS.2003.811744

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

Phillip, J.R. 1957, Evaporation, and moisture and heat fields in the sol. Journal of Meteorology, 14, 354-366. https://doi.org/10.1175/1520-0469(1957)014%3C0 354:EAMAHF%3E2.0.CO;2

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.

Rivas, R., Carmona, F. 2013. Evapotranspiration in the Pampean Region using field measurements and satellite data. Physics and Chemistry of the Earth, Elsevier, Special Issue: Remote Sensing in Hydrology, 55-57, 27-34. ISSN 1474-7065. https://doi.org/10.1016/j.pce.2010.12.002

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

Shah, N., Nachabe, M., Ross, M. 2007 Extinction depth and evapotranspiration from groundwater under selected land covers. Ground Water, 45(3), 329-338. https://doi.org/10.1111/j.1745-6584.2007.00302.x

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

Tang, Q.H., Peterson, S., Cuenca, R.H., Hagimoto, Y., Lettenmaier, D.P. 2009. Satellite-based near-real-time estimation of irrigated crop water consumption. Journal of Geophysical Research: Atmospheres, 114(D05), 114. https://doi.org/10.1029/2008JD010854

Vaisala 2012, Manual User´s Vaisala Automatic AWS310.

Vidal, J. 2009 Evaporación desde napas freáticas someras en cuencas endorreicas del altiplano chileno. Tesis de Magíster en Ciencias de la Ingeniería. Universidad Católica de Chile.

Wan Z., Zhang K., Xue X.W., Hong Z., Hong Y., Gourley J.J. 2015. Water balance based actual evapotranspiration reconstruction from ground and satellite observations over the Conterminous United States. Water Resources Research, 51(8), 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. rnal of Geophysical Research: Atmospheres, 112(D15), 107. 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. Environmental Research Letters, 7(1), 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. Journal of Hydrology, 379(1-2), 92-110. https://doi.org/10.1016/j.jhydrol.2009.09.047

Zhang, K., Kimball, J. S. and Running, S. W. 2016, A review of remote sensing based actual evapotranspiration estimation. Wiley Interdisciplinary Reviews: Water, 3(6), 834-853. https://doi.org/10.1002/wat2.1168

Abstract Views

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