Estimating Evapotranspiration from an Improved Two-Source Energy Balance Model Using ASTER Satellite Imagery

Qifeng Zhuang,Bingfang Wu

doi:10.3390/w7126653

Abstract

Reliably estimating the turbulent fluxes of latent and sensible heat at the Earth’s surface by remote sensing is important for research on the terrestrial hydrological cycle. This paper presents a practical approach for mapping surface energy fluxes using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images from an improved two-source energy balance (TSEB) model. The original TSEB approach may overestimate latent heat flux under vegetative stress conditions, as has also been reported in recent research. We replaced the Priestley-Taylor equation used in the original TSEB model with one that uses plant moisture and temperature constraints based on the PT-JPL model to obtain a more accurate canopy latent heat flux for model solving. The collected ASTER data and field observations employed in this study are over corn fields in arid regions of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) area, China. The results were validated by measurements from eddy covariance (EC) systems, and the surface energy flux estimates of the improved TSEB model are similar to the ground truth. A comparison of the results from the original and improved TSEB models indicates that the improved method more accurately estimates the sensible and latent heat fluxes, generating more precise daily evapotranspiration (ET) estimate under vegetative stress conditions.

Highlights

Modeling surface energy fluxes on a regional scale is essential for assessing energy and mass exchanges between the hydrosphere, atmosphere, and biosphere
The numerous surface energy balance (SEB) algorithms that have been developed in the past few decades generally include one-source models, such as SEBAL [2], METRIC [3], and SEBS [4], and multi-source models, such as two-source energy balance (TSEB) [5] and SEB-4S [1]
The ASTER images have a spatial resolution of 90 m for the thermal infrared bands and the scale of the thermal ground-based measurements is approximately 10 m [16], the comparison shows reasonable variation, with a determination coefficient

Summary

Introduction

Modeling surface energy fluxes on a regional scale is essential for assessing energy and mass exchanges between the hydrosphere, atmosphere, and biosphere. Evapotranspiration (ET) is a major component of the processes and models for predicting soil water availability, forecasting rainfall, and monitoring drought, water balance, and global climate change [1]. ET is difficult to measure and predict, especially on a regional scale. Remote sensing techniques have been widely used to estimate surface energy fluxes in recent years because they provide numerous parameters necessary for surface energy balance (SEB) models, such as the land surface temperature, surface albedo, and vegetation index at various spatiotemporal resolutions. The one-source models treat the vegetation and soil as one “big leaf” with identical temperature and aerodynamic resistance for heat transfer at the same height

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