Process-Based Modeling of Lysimeter Boundary Conditions for Climate Change Experiments in Ecotron Facilities

Ecotron facilities are key tools to emulate and monitor environmental conditions for improving the understanding of terrestrial ecosystems. Although their conditions can be precisely modified by cutting-edge controlling systems, the external factors influencing the boundary conditions of such ecotron units remain uncertain under reconstructed scenarios (e.g., climate change). We assessed how an agroecosystem model can be used to simulate the bottom boundary conditions of the newly developed ecotron facility AgraSim. The facility comprises six identical ecotron units composed of a climate-controlled plant chamber on top of a cylindrical lysimeter (1 m² by 150 cm depth). An automatic suction cup–pumping system installed below each lysimeter is used to control the bottom boundary condition of the system depending on the measured pressure head near its bottom. The first experimental trial of AgraSim is aimed to quantify the key climate responses of a typical agricultural field located in North-Rhine Westphalia (Germany) to transient climate change. A set of four climate scenarios were derived from storyline simulations with the regional atmospheric circulation model ICON, imposing a transient temperature gradient of +1^oC to +4^oC within the climate chambers. While the atmospheric forcings and the soil texture and hydraulic properties are well-characterized, the bottom boundary condition at 150 cm depth is unknown for the different climate change scenarios. We thus used an agroecosystem model (AgroC) to numerically solve water movement within the soil column (0-150 cm) and investigated the impact of choosing one of the following bottom boundary conditions: fixed pressure heads (FP); free-drainage (FD); and a modified seepage face at h=-100hPa (SP). A simulation that assumes a 500 cm deep soil column and free drainage was taken as a reference for assessing the performance of each of the different bottom boundary conditions. This setup was replicated for two rainfed cropping systems (winter wheat and maize), each parameterized with three types of rooting profile representing shallow, deeper and homogeneous root profiles, respectively. A 1-year spin-up run was performed to minimize the effect of the initial conditions. Our model simulations showed that the different boundary conditions only affected soil moisture below 30 cm, while topsoil moisture was mainly controlled by atmospheric forcings. The FP and FD scenarios tended to underestimate soil water availability in the 150 cm column, especially during critical summer drought periods. The modified SP showed the best agreement with the reference simulations, keeping the soil unsaturated during winter and maintaining moisture and fluxes closer to the reference levels in summer. This result was consistent across both crops and rooting profiles. At the crop level, the different boundary conditions had no significant effect on key crop variables (e.g., biomass and leaf area) and their respective response to the climate scenarios. Although our results are limited by observation availability and model parameterization uncertainty, they demonstrate the potential application of process-based models for decision-making in controlled-system facilities.