An image-based four-source surface energy balance model to estimate crop evapotranspiration from solar reflectance/thermal emission data (SEB-4S)

Abstract

A remote sensing-based surface energy balance model is developed to explicitly represent the energy fluxes of four surface components of agricultural fields including bare soil, unstressed green vegetation, non-transpiring green vegetation, and standing senescent vegetation. Such a four-source representation (SEB-4S) is achieved by a consistent physical interpretation of the edges and vertices of the polygon (named T−fvg polygon) obtained by plotting surface temperature (T) as a function of fractional green vegetation (fvg) and the polygon (named T−α polygon) obtained by plotting T as a function of surface albedo (α). To test the performance of SEB-4S, a T−α image-based model and a T−fvg image-based model are implemented as benchmarks. The three models are tested over a 16km by 10km irrigated area in northwestern Mexico during the 2007–2008 agricultural season. Input data are composed of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) thermal infrared, Formosat-2 shortwave, and station-based meteorological data. The fluxes simulated by SEB-4S, the T−α image-based model, and the T−fvg image-based model are compared on seven ASTER overpass dates with the in situ measurements collected at six locations within the study domain. The evapotranspiration simulated by SEB-4S is significantly more accurate and robust than that predicted by the models based on a single (either T−fvg or T−α) polygon. The improvement provided with SEB-4S reaches about 100Wm−2 at low values and about 100Wm−2 at the seasonal peak of evapotranspiration as compared with both the T−α and T−fvg image-based models. SEB-4S can be operationally applied to irrigated agricultural areas using high-resolution solar/thermal remote sensing data, and has potential to further integrate microwave-derived soil moisture as additional constraint on surface soil energy and water fluxes.