A Two-Source Model for Estimating Evaporative Fraction (TMEF) Coupling Priestley-Taylor Formula and Two-Stage Trapezoid

Hao Sun

doi:10.3390/rs8030248

Abstract

Remotely sensed land surface temperature and fractional vegetation coverage (LST/FVC) space has been widely used in modeling and partitioning land surface evaporative fraction (EF) which is important in managing water resources. However, most of such models are based on conventional trapezoid and simply determine the wet edge as air temperature (Ta) or the lowest LST value in an image. We develop a new Two-source Model for estimating EF (TMEF) based on a two-stage trapezoid coupling with an extension of the Priestly-Taylor formula. Latent heat flux on the wet edge is calculated with the Priestly-Taylor formula, whereas that on the dry edge is set to 0. The wet and dry edges are then determined by solving radiation budget and energy balance equations. The model was evaluated by comparing with other two models that based on conventional trapezoid (i.e., the Two-source Trapezoid Model for Evapotranspiration (TTME) and a One-source Trapezoid model for EF (OTEF)) in how well they simulate and partition EF using MODIS products and field observations from HiWATER-MUSOEXE in 2012. Results show that the TMEF outperforms the other two models, where EF mean absolute relative deviations are 9.57% (TMEF), 15.03% (TTME), and 30.49% (OTEF).

Highlights

Modeling and partitioning land surface evapotranspiration (ET) are of crucial importance in managing water resource both at the farm and the irrigation project level [1,2]
The Two-source Model for estimating EF (TMEF) provides a theoretical way to determine the wet edge of land surface temperature and fractional vegetation coverage (LST/FVC) space
We present a two-source model for estimating evaporative fraction (EF), named TMEF, through coupling the two-stage trapezoidal LST/FVC space with the Priestly-Taylor formula

Summary

Introduction

Modeling and partitioning land surface evapotranspiration (ET) are of crucial importance in managing water resource both at the farm and the irrigation project level [1,2] They are essential in predicting the climatic response of ecosystem functions and processes [3,4,5]. It has been widely used to characterize the energy partition over land surfaces and to infer daily energy balance information based on mid-day remote sensing measurements [3,6,7,8,9] It is more suitable as an index for surface moisture condition or drought status than ET, because ET is a function of the land surface conditions and the surface available energy [1,10]. Yang et al (2015) compared three two-source remote sensing models of ET (i.e., the Hybrid dual-source scheme and Trapezoid framework-based ET Model (HTEM), Remote Sens. 2016, 8, 248; doi:10.3390/rs8030248 www.mdpi.com/journal/remotesensing

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Conclusion