Understanding and characterizing land surface-atmosphere exchange and feedbacks

This project uses three different and complementary approaches to quantify local to regional evapotranspiration and surface energy balance partitioning. The first approach uses the semi- physical-, Penman-Monteith equation combined with the complementary relationship and thermal remote sensing to derive high resolution estimates of evapotranspiration. The second approach uses hydro-meteorological simulations of the WRF-NOAH-MP model system down to scales of 100 m to study the effects of soil-vegetation-atmosphere feedbacks and mesoscale circulations on regional evapotranspiration with unprecedented detail. The third approach uses the thermodynamic limit on convective exchange to infer the magnitude of soil-vegetation-atmosphere interactions, atmospheric mixing processes, and local to regional evapotranspiration patterns. A dedicated field campaign performing micrometeorological measurements of the surface energy balance and the CAOS field observations will be used to evaluate these methods. The WRF-NOAH-MP model is also applied for quantitative precipitation forecasting by assimilating polarization radar data to improve initial water budget components. These approaches are evaluated in a joint synthesis activity regarding surface energy balance estimates from local to catchment scale and their closure assumptions. The synthesis of these three approaches of vastly different complexity has the potential to substantially advance our ability to understand and robustly predict regional evapotranspiration and the surface energy balance.

Topography and the spatial variability in surface characteristics such as vegetation and soil properties create typical patterns and structures in the landscape. These patterns shape important environmental processes such as the movement of water within a catchment, solute transport or water and nutrient availability in forests and agricultural systems. Spatial variability in these processes results in spatially variable water quality, rates of plant photosynthesis etc. Understanding and characterizing these patterns and structures and their evolution over time as well as possible interactions and feedbacks is therefore of critical importance. In the framework of the CAOS project, we aimed at exploring the utility of large and small scale remote sensing techniques for an improved quantification of these patterns. One focus of the project was on the use of observations of the thermal infrared (TIR) emission from the land surface. We could show that the integration of TIR information leads to improvements in land cover classification and the representation of its temporal dynamics as compared to the use of information from the visible and near-infrared spectral range alone. A principle component analysis of a 10 years long time series of satellite TIR imagery over the Attert catchment (Luxembourg) allowed for the identification of elementary functional units, which define similarity of landscape units with respect to water and energy fluxes. The delineation of these functional units is an essential prerequisite for the development and parameterization of hydrological and land surface models. The time series of TIR observations could be further used for the derivation of high-resolution soil texture information, which is particularly important for modelling water and solute transport in the subsurface. A self-assembled unmanned aerial system (UAS), equipped with a dual camera setup consisting of a regular digital camera and a thermal imager, allowed for mapping vegetation conditions and land surface temperature (LST) with high spatial and temporal detail. Studies over temperate grasslands demonstrated the utility of the UAS-based imagery in combination with LST-based models of different complexity for the accurate and spatially distributed assessment of plant heat stress and evapotranspiration. The applied UAS setup in combination with easily applicable modelling schemes provide unprecedented opportunities for spatially explicit irrigation and nutrient management and for addressing research questions regarding water and energy transfer within the highly coupled soil-vegetation-atmosphere system.