Author(s): Jonathan Ruíz-Delgado, Juan Diego Giraldo Osorio, Cristihian Bayona-Rodriguez, Hernán Mauricio Romero

Linked Author(s): Juan Diego Giraldo Osorio

Keywords: Evapotranspiration; Land surface temperature (LST); Remote sensing; Eddy covariance; Uncertainty;

Abstract: Evapotranspiration estimation is a very important input for the estimation of the water requirement of crops, in particular those of high economic interest, such as oil palm, object of study of this research. Based on the above, there is a need for evaluating different inputs for crop evapotranspiration (ET) estimation, as well as to better understand the role of crops in the hydrological cycle and their contribution to the atmosphere as a particular agrosystem. Therefore, the evaluation of different inputs and methods is required for improving ET estimation. Consequently, this work will use information from two main sources: remote sensing, which provides a spatial measurement of ET, and an Eddy Covariance system (EC) installed in an oil palm plantation. This will allow to obtain temporal information about water flows in this crop. However, ET measurement techniques with remote sensing demand high meteorological information for the specific day of capturing satellite images. In Colombia, the Oil Palm Research Center (Cenipalma) owns an oil palm plantation equipped with the EC system that measures the necessary flows and variables to fine-tune ET estimations in oil palm crops. The main objective of this research is to validate a remote-sensing-based method for the estimation of space-time distribution of ET in oil palm crops. These estimates will be compared with those obtained by the EC system, while fine-tuning results by including the meteorological variables measured by the EC for the day of satellite images capturing.

DOI: https://doi.org/10.3850/38WC092019-1513

Year: 2019