Derivation of Daily Evaporative Fraction Based on Temporal Variations in Surface Temperature, Air Temperature, and Net Radiation

Jing Lu,Zhao-Liang Li,Huajun Tang,Ronglin Tang

doi:10.3390/rs5105369

Abstract

Based on surface energy balance and the assumption of fairly invariant evaporative fraction (EF) during daytime, this study proposes a new parameterization scheme of directly estimating daily EF. Daily EF is parameterized as a function of temporal variations in surface temperature, air temperature, and net radiation. The proposed EF parameterization scheme can well reproduce daily EF estimates from a soil-vegetation-atmosphere transfer (SVAT) model with a root mean square error (RMSE) of 0.13 and a coefficient of determination (R2) of 0.719. When input variables from in situ measurements at the Yucheng station in North China are used, daily EF estimated by the proposed method is in good agreement with measurements from the eddy covariance system corrected by the residual energy method with an R2 of 0.857 and an RMSE of 0.119. MODIS/Aqua remotely sensed data were also applied to estimate daily EF. Though there are some inconsistencies between the remotely sensed daily EF estimates and in situ measurements due to errors in input variables and measurements, the result from the proposed parameterization scheme shows a slight improvement to SEBS-estimated EF with remotely sensed instantaneous inputs.

Highlights

Estimation of evapotranspiration (ET) using remotely sensed data has been a significant topic because of the capability of remote sensing to quickly obtain surface information at large spatial scales with less cost [1,2,3,4,5,6]
residual energy (RE) method is to assume that the imbalance energy is due to the underestimation of latent heat flux (LE) measurements, whereas BR method is to partition the imbalance energy into H and LE according to Bowen ratio [53]
On the basis of surface energy balance and the assumption of self-preservation Evaporative fraction (EF) during daytime, this study developed a new parameterization scheme for deriving daily EF

Summary

Introduction

Estimation of evapotranspiration (ET) using remotely sensed data has been a significant topic because of the capability of remote sensing to quickly obtain surface information at large spatial scales with less cost [1,2,3,4,5,6]. Current models for ET estimation from remotely sensed data, e.g., the surface energy balance system (SEBS), the surface energy balance algorithm for land (SEBAL), and two-source models, depend primarily on observations at the satellite overpass time [7,8,9,10]. Because of the influences of atmosphere, observational angular, heterogeneous surfaces, and scale issues, there are some uncertainties in retrieved surface variables from remote sensing [11,12,13]. The accuracy of ET estimates could be largely subjected to retrieval errors in remotely sensed surface variables [14,15,16]. A number of studies based on in situ measurements as well as analyses from land process modeling showed that EF exhibits a typical concave-up shape and is relatively stable during daytime [17,18,19,20,21]

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Conclusion