Using Remote Sensing to Estimate Evapotranspiration from Terrestrial Ecosystems at Different Scales

Abstract

【Background and objective】 Evapotranspiration is an important component in the hydrological cycle and provides a nexus between water, carbon and surface energy exchanges in terrestrial systems. It is difficult to measure in situ at large scales. Remote sensing can plug this gap and has seen rapid application over the past three decades. The purpose of this paper is to test the feasibility of remote sensing to estimate evapotranspiration at provincial and sub-provincial scales in Guangxi province of China. 【Method】 We established a model to calculate evapotranspiration using remote sensing data first and then compared it with ground-true data. It was then used to estimate the net irrigation water measured at different scales using a regression model. Based on the correlation coefficient between the measurements and estimations at different scales, we found the optimal scale for application of the model and established an accurate and effective method to estimate net irrigation water using remote sensing data. 【Result】 There is a linear correlation between net irrigation water and the remote sensing evapotranspiration at both provincial and sub-provincial scale, and the correlation coefficient was higher than 0.8. Comparison with measured results revealed that the errors of the evapotranspiration estimated using the remote sensing data was less than 0.5% at provincial and sub- provincial scales. 【Conclusion】 At large scales, remote sensing provides a reliable alternative to estimate evapotranspiration and be used to help improve irrigation and agricultural managements.

Keywords

• remote sensing evapotranspiration
• spatial scales
• net irrigation water measurement
• the strictest water management