Impact of Terrestrial Hydrology on L-A feedback and Isotope Signatures

As climate change progresses, the role of interactions between land and atmosphere (L-A) is becoming increasingly important for weather and climate development. Since the resulting feedback mechanisms depend on the water pathways between land and atmosphere, a sound understanding of the associated processes is necessary in order to represent them realistically in models. Stable water isotopes can be used for this purpose. Since the isotope signature changes constantly due to various influences along the water pathways, they act as natural tracers in the water cycle. By comparing observed isotope data with modeled data within the DFG-project “LAFI” (Land-Atmosphere-Feedback-Initiative) the origin of the modeled behavior can be traced back and the models can be further improved.

To this purpose, we utilize the appropriate, fully coupled atmospheric-hydrological modeling system WRF-Hydro-Iso with its innovative “-Iso” implementation. By tracing water pathways with WRF-Hydro-Iso, we aim to improve our understanding of weather- and season-dependent interactions between groundwater, soil moisture, plant transpiration, soil evaporation, isotope signature, and L-A feedback in agricultural areas at the convection permitting scale.

Comparing a fully coupled model with all these compartments of the water cycle requires an observatory with multiple instruments—such as the Land-Atmosphere Feedback Observatory (LAFO) near Hohenheim, Stuttgart. During the 2025 growing season, various variables were measured within defined observation periods, which are used to evaluate WRF-Hydro-Iso. Therefore, an innovative multi-month setup with a resolution of 1.25 km was chosen, based on ERA5 reanalysis forcing data and iCESM isotope climatology. In the upcoming work within this project it is planned to reduce the resolution down to 250 m and 50 m.

In this session, we evaluate the model results using lysimeter, sap flow, isotope chamber, CRNS (Cosmic Ray Neutron Sensing) soil moisture, and precipitation measurements by displaying the correlation coefficient and RMSE (Root Mean Square Error) to provide an educated overview of model performance. With its rather high spatial and temporal resolution, this study provides detailed insights into L-A interactions, with a particular focus on evapotranspiration (ET) partitioning and isotopic signature herein. First results of a comparison of observation period in June 20.- 27. show that the observed transpiration ratio (T / ET) is 74 %, while the modeled transpiration ratio 86 % overestimates T a bit. However, comparing the diurnal course and peak values it gets clear, that the model is able to capture the overall dynamics of evaporation (E), T and ET already with a resolution of 1,25 km.