Future projections indicate an intensification of droughts under global warming, which focuses the attention on the vegetation response under extreme climate conditions. Land surface models (LSMs) are primary tools designed to assess the impact of climate-induced stresses on ecosystem functioning and understand their propagation through soil-vegetation-atmosphere feedback mechanisms. Yet, several studies show a systematic overestimation of drought effects simulated with a wide range of LSMs. These deficiencies have stimulated the integration of an advanced representation of vegetation characteristics based on an explicit link between stomatal regulation and root water uptake through the plant hydraulic transport network. The theoretical foundation of this hydraulic approach opens new avenues to improve drought prediction capabilities, and prospects efficient ways of conditioning LSMs response by assimilating measurements of the actual plant water status. However, the characterization of the plant hydraulic traits for regional- and continental-scale studies is challenged by sparse observations that do not represent the richness in plant species diversity. This research proposal, CAPACITY, aims at investigating the sensitivity of stomata regulation and root water uptake as reflected in the simulated evapotranspiration response due to uncertainty inherited in the hydraulic traits. To this aim, the project will develop a seasonal-to-decadal numerical simulation framework based on point-, regional-, and continental-scale setups over Europe. We will make joint use of the state-of-the-art LSM CLM5.0 and multi-source observations, exploit globally assembled and continuously updated databases of plant traits, and extract past and future climate signal from multi-model ensemble atmospheric simulations. Finally, the project will investigate synergies between terrestrial systems modeling and thermal remote sensing-based evapotranspiration to improve drought monitoring and predictions at the regional scale.