## 4 Discussion  
The sites of ICP Forest Level II enabled hydrological modeling with realistic site-based input data and model validation. In the model validation section, we show that our model setup reproduces measurements, expressed by interception and soil water content. Modeled interception was higher than measured, probably due to the lacking measurements of interception by the ground vegetation. Unfortunately, most research studies focus on forest canopy interception and why direct measurements of ground vegetation interception are rare [65]. Based on the modeled daily net rainfall and the measured throughfall in the rain gauge, the amount of the ground vegetation interception of the four pine stands examined ranged between 0% and 9% of annual gross rainfall. However, partitioning of gross rainfall into interception, throughfall, and stemflow is strongly influenced by stand characteristics and might vary between seasons and years due to different rainfall conditions [66]. Thus, the role of ground vegetation interception cannot be described precisely. Nevertheless, we consider a reliable estimate of daily throughfall rates as soil water predictions have been in good agreement with measurements. The simulation results indicate that tuning the infiltration parameter _infexp_ could improve on some sites the soil water predictions, while at others, it had less influence. In BROOK90, macropore-assisted infiltration is not explicitly modeled. Nevertheless, incoming water can be partitioned across the soil column by the infiltration parameters, and thus, preferential flows are represented. Preferential flows exhibit a high small-scale spatial variability and are influenced by stemflow and rooting, e.g., [67; 68]. Water is collected by tree crowns and conducted via stem and roots to the soil causing a greater infiltration depth nearby the trunks [69]. This effect is influenced by species [70]. Beech trees have a larger partitioning of gross precipitation to stemflow compared to pine trees and might have a substantial effect on the groundwater recharge in the direct surrounding of beech trees [71]. Because the soil moisture measurements on the ICP Forests Level II sites are undertaken with three replications, these measurements do not account for small-scale variance. Furthermore, because the sondes are placed at a distance to the stems, the probability is higher that infiltrated water originates from throughfall than from stemflow. Therefore, model optimization also reflects the throughfall-descended rather than stemflow-descended infiltration. However, by varying _infexp_, we were able to fit the simulated infiltration distribution to the measured soil water contents in different depths at each site. The average r\({}^{2}\) ranged from 0.60 to 0.82 and confirmed reliable predictions of soil moisture at all sites. The modeled actual transpiration is limited by the water supply rate controlled by the water potential gradient and plant resistance and is, thus, depending on reliable soil moisture predictions and maximum root water uptake, respectively. We obtained reliable stand transpiration rates compared to other studies. Based on sap flow measurements,  
Figure 4: Temperature (T), precipitation (P), climate water balance (CWB), actual evapotranspiration (ET), plant-available soil water down to a depth of 2 m (SW), seepage (S), and dry days (TI) in 1961–2019 and under scenarios in 2010–2010, for individual plots and whole dataset (black). The significant slope of the whole dataset is denoted by \(p<0.05\), non-significance by n.s. pine canopy transpiration within the growing season ranged between 112 mm and 239 mm, depending on stand age, site condition, and year [72; 73; 74]. Because we cannot separate canopy and ground vegetation transpiration, a direct comparison to [72; 73; 74] is not possible. Nevertheless, based on results from [PERSON] [74] and [PERSON] [75], we conclude that the transpiration of ground vegetation is higher than 50% of pine canopy transpiration.