Evapotranspiration and evaporation/transpiration partitioning with dual source energy balance models in agricultural lands

EvapoTranspiration (ET) is an important component of the water cycle, especially in semi-arid lands. Its quantification is crucial for a sustainable management of scarce water resources. A way to quantify ET is to exploit the available surface temperature data from remote sensing as a signature of the surface energy balance, including the latent heat flux. Remotely sensed energy balance models enable to estimate stress levels and, in turn, the water status of most continental surfaces. The evaporation and transpiration components of ET are also just as important in agricultural water management and ecosystem health monitoring. Single temperatures can be used with dual source energy balance models but rely on specific assumptions on raw levels of plant water stress to get both components out of a single source of information. Additional information from remote sensing data are thus required, either something specifically related to evaporation (such as surface water content) or transpiration (such as PRI or fluorescence). This works evaluates the SPARSE dual source energy balance model ability to compute not only total ET, but also water stress and transpiration/evaporation components. First, the theoretical limits of the ET component retrieval are assessed through a simulation experiment using both retrieval and prescribed modes of SPARSE with the sole surface temperature. A similar work is performed with an additional constraint, the topsoil surface soil moisture level, showing the significant improvement on the retrieval. Then, a flux dataset acquired over rainfed wheat is used to check the robustness of both stress levels and ET retrievals. In particular, retrieval of the evaporation and transpiration components is assessed in both conditions (forcing by the sole temperature or the combination of temperature and soil moisture). In our example, there is no significant difference in the performance of the total ET retrieval, since the evaporation rate retrieved from the sole surface temperature is already fairly close to the one we can reconstruct from observed surface soil moisture time series, but current work is underway to test it over other plots.</p

Preface paper to the Semi-Arid Land-Surface-Atmosphere (SALSA) Program special issue

The Semi-Arid Land-Surface-Atmosphere Program (SALSA) is a multi-agency, multi-national research effort that seeks to evaluate the consequences of natural and human-induced environmental change in semi-arid regions. The ultimate goal of SALSA is to advance scientific understanding of the semi-arid portion of the hydrosphere–biosphere interface in order to provide reliable information for environmental decision making. SALSA approaches this goal through a program of long-term, integrated observations, process research, modeling, assessment, and information management that is sustained by cooperation among scientists and information users. In this preface to the SALSA special issue, general program background information and the critical nature of semi-arid regions is presented. A brief description of the Upper San Pedro River Basin, the initial location for focused SALSA research follows. Several overarching research objectives under which much of the interdisciplinary research contained in the special issue was undertaken are discussed. Principal methods, primary research sites and data collection used by numerous investigators during 1997–1999 are then presented. Scientists from about 20 US, five European (four French and one Dutch), and three Mexican agencies and institutions have collaborated closely to make the research leading to this special issue a reality. The SALSA Program has served as a model of interagency cooperation by breaking new ground in the approach to large scale interdisciplinary science with relatively limited resources

Anisotropy of thermal infrared remote sensing over urban areas : assessment from airborne data and modeling approach

International audienc

High resolution surface temperature and urban thermal anisotropy simulations : validation against airborne remote sensing TIR data over Toulouse city (France).

International audienc

Simulation of the radiative behaviour of an urban quater of Marseille

International audienc

Sensitivity of thermal infrared directional anisotropy to canopy and meteorological conditions.

International audienc

Driving factors of the directional variability of thermal infrared signal in temperate regions

Land surface temperature (LST) is a good indicator of the land surface state. The measurement of LST is however prone to directional anisotropy which may severely affect the interpretation of the measurements if it is not corrected. This study aims at determining and describing the impact of various factors on anisotropy of continuous crops at mid-latitudes. The SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) model is used as a data generator of directional anisotropy since it enables exploring a very large range of meteorological, biochemical and geometrical conditions. An original indicator, the standard deviation of anisotropy in principal plane, is used in order to investigate the impact of the tested variables and parameters. We found that anisotropy is, at first order, related to seasonal trends, in relation to the amount of incident radiation and the solar zenith angle. Then the geometrical structure of the canopy modifies the anisotropy (LAI, LADF, hot spot parameter) followed by the coupling between the water status of the soil and the stress of canopy. Wind speed which is known for having a significant impact on temperature level has a very limited influence on anisotropy. An analysis of the amplitude of anisotropy in the principal and perpendicular planes (from -50 degrees to 50 degrees zenith) showed that anisotropy can reach up to 11 degrees C and similar to 3.5 degrees C respectively. The impact of satellite orbit on anisotropy is also discussed and it is found that, given the latitudes and the season, the anisotropy can severely affect measurements. This is particularly true when the satellite measurements are acquired in a configuration close to the solar principal plane, which often occur at low latitude. These results are of great help in the context of developing simple methods which could then be integrated into satellite data processing algorithms