A remote sensing‐based three‐source energy balance model to improve global estimations of evapotranspiration in semi‐arid tree‐grass ecosystems

Abstract

It is well documented that energy balance and other remote sensing‐based evapotranspiration (ET) models face greater uncertainty over water‐limited tree‐grass ecosystems (TGEs), representing nearly 1/6th of the global land surface. Their dual vegetation strata, the grass‐dominated understory and tree‐dominated overstory, make for distinct structural, physiological and phenological characteristics, which challenge models compared to more homogeneous and energy‐limited ecosystems. Along with this, the contribution of grasses and trees to total transpiration (T), along with their different climatic drivers, is still largely unknown nor quantified in TGEs. This study proposes a thermal‐based three‐source energy balance (3SEB) model, accommodating an additional vegetation source within the well‐known two‐source energy balance (TSEB) model. The model was implemented at both tower and continental scales using eddy‐covariance (EC) TGE sites, with variable tree canopy cover and rainfall (P) regimes and Meteosat Second Generation (MSG) images. 3SEB robustly simulated latent heat (LE) and related energy fluxes in all sites (Tower: LE RMSD ~60 W/m2; MSG: LE RMSD ~90 W/m2), improving over both TSEB and seasonally changing TSEB (TSEB‐2S) models. In addition, 3SEB inherently partitions water fluxes between the tree, grass and soil sources. The modelled T correlated well with EC T estimates (r > .76), derived from a machine learning ET partitioning method. The T/ET was found positively related to both P and leaf area index, especially compared to the decomposed grass understory T/ET. However, trees and grasses had contrasting relations with respect to monthly P. These results demonstrate the importance in decomposing total ET into the different vegetation sources, as they have distinct climatic drivers, and hence, different relations to seasonal water availability. These promising results improved ET and energy flux estimations over complex TGEs, which may contribute to enhance global drought monitoring and understanding, and their responses to climate change feedbacks.

Application of a remote-sensing three-source energy balance model to improve evapotranspiration partitioning in vineyards

“…Burchard-Levine et al ( 2022 ) developed a remote-sensing-based three-source energy balance model (3SEB), which adds a vegetation source to the widely used two-source energy balance (TSEB) model (Kustas and Norman 1999a , b ; Norman et al 1995 ). 3SEB was developed to account for the multiple and contrasting vegetation layers in heterogeneous landscapes, such as tree-grass or savanna ecosystems.…”

“…For a discussion on the different multi-source representations (e.g., series vs parallel), the reader is referred to Kustas and Norman ( 1999a , b ) and Lhomme et al ( 2012 ). Rn is estimated through the radiative transfer model (RTM) adapted from the model described in Chapter 15 of Campbell and Norman ( 1998 ) and detailed in section S1 of supplementary information of Burchard-Levine et al ( 2022 ). G is estimated as the ratio of Rn reaching the soil (i.e., 0.35 ).…”

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Fig. 1 The three- source energy balance (3SEB) model framework (adapted from Burchard-Levine et al 2022 ) and its main inputs, including radiometric land surface temperature (LST) and air temperature (TA), and resistance schemes to estimate the sensible heat flux of the overstory vegetation (Hov), understory vegetation (Hun), and soil (Hsoil) sources. Refer to the text for the definition of other symbols

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“…2 ) are conserved under realistic daytime conditions (i.e., no daytime condensation nor negative LE). Refer to Burchard-Levine et al ( 2022 ) or the source code ( https://github.com/VicenteBurchard/3SEB ) for model details and specifications.…”

“…The 3SEB model, developed in Burchard-Levine et al ( 2022 ), added a vegetation source (overstory vegetation + understory vegetation + soil) to the TSEB model. 3SEB was originally designed for tree-grass agro-forests or savanna ecosystems, which have distinct overstory and understory vegetation.…”