Using surface temperature as a signature of the surface energy balance is a way to quantify the spatial distribution of evapotranspiration and water stress. In this work, we used the new dual-source model named Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) based on the Two Sources Energy Balance (TSEB) model rationale which solves the surface energy balance equations for the soil and the canopy. SPARSE can be used (i) to retrieve soil and vegetation stress levels from known surface temperature and (ii) to predict transpiration, soil evaporation, and surface temperature for given stress levels. The main innovative feature of SPARSE is that it allows to bound each retrieved individual flux component (evaporation and transpiration) by its corresponding potential level deduced from running the model in prescribed potential conditions, i.e., a maximum limit if the surface water availability is not limiting. The main objective of the paper is to assess the SPARSE model predictions of water stress and evapotranspiration components for its two proposed versions (the “patch” and “layer” resistances network) over 20 in situ data sets encompassing distinct vegetation and climate. Over a large range of leaf area index values and for contrasting vegetation stress levels, SPARSE showed good retrieval performances of evapotranspiration and sensible heat fluxes. For cereals, the layer version provided better latent heat flux estimates than the patch version while both models showed similar performances for sparse crops and forest ecosystems. The bounded layer version of SPARSE provided the best estimates of latent heat flux over different sites and climates. Broad tendencies of observed and retrieved stress intensities were well reproduced with a reasonable difference obtained for most of the points located within a confidence interval of 0.2. The synchronous dynamics of observed and retrieved estimates underlined that the SPARSE retrieved water stress estimates from Thermal Infra-Red data were relevant tools for stress detection.

This paper presents a comparison of two water transfer schemes implemented in land surface models: a three-layer bulk reservoir model based on the force–restore scheme (FR) and a multilayer soil diffusion scheme (DIF) relying on explicit mass-diffusive equations and a root profile. The performances of each model at simulating evapotranspiration (ET) over a 14-yr Mediterranean crop succession are compared when the standard pedotransfer estimates versus the in situ values of the soil parameters are used. The Interactions between Soil, Biosphere, and Atmosphere (ISBA) generic land surface model is employed. When the pedotransfer estimates of the soil parameters are used, the best performance scores are obtained with DIF. DIF provides more accurate simulations of soil evaporation and gravitational drainage. It is less sensitive to errors in the soil parameters compared to FR, which is strongly driven by the soil moisture at field capacity. When the in situ soil parameters are used, the performance of the FR simulations surpasses those of DIF. The use of the proper maximum available water content for the plant removes the bias in ET and soil moisture over the crop cycle with FR, while soil water stress is simulated too early and the transpiration is underestimated with DIF. Increasing the values of the root extinction coefficient and the proportion of homogeneous root distribution slightly improves the DIF performance scores. Spatiotemporal uncertainties in the soil parameters generate smaller uncertainties in ET simulated with DIF compared to FR, which highlights the robustness of DIF for large-scale applications.