## 5 Conclusions  
To study the impact of drought on forests in northeast Germany by means of water budget modeling, a valid model setup is needed. This is crucial for extending site-specific water balance modeling to sites where no measurements are available and to different scenarios of stand development and stand composition. Therefore, our aim was to evaluate and optimize the performance of the hydrological model with measured soil moisture data.  
Our evaluation of the modeling approach yields a good correlation of modeled output with measurements. We conclude that our model setup provides the basis for studying forest water budgets under changing climate and management.  
One of the aims of our study was to evaluate the changes in water budgets within the time period 1961-2019. We could show that within the historical time period, evapotranspiration increased in parallel to temperature, which leads due to unchanged precipitation to an increase of dry days. Especially, the last two years of the time series were extreme. We conclude, based on the observed trend in our study and on observations on forest damages made in this region, that forests in northeast Germany are exposed to increasing drought risk. Our assessment of the future changes in water budgets under RCP2.6 and RCP8.5 with two regionalized CMIP5 models concludes that under RCP8.5, drought conditions will increase, in contrast to RCP2.6. The increase of temperature, evapotranspiration, and dry days within the historical time series is more in line with RCP8.5 than RCP2.6, suggesting that this scenario is more likely than RCP2.6. Changes in amounts of precipitation differ between both models within RCP8.5, indicating a high uncertainty in simulations of precipitation. In consequence, forest planners are faced with an uncertain future with respect to the water supply of forests. To minimize the risk, forest planning should focus on these uncertainties, e.g., by relying on diverse, species-rich forests.  
The following are available online at [[https://www.mdpi.com/2076-341/7/11/5/2403/s1](https://www.mdpi.com/2076-341/7/11/5/2403/s1)]([https://www.mdpi.com/2076-341/7/11/5/2403/s1](https://www.mdpi.com/2076-341/7/11/5/2403/s1)), Table S1: Ranges of parameter values, Table S2: Two-sided hypothesis-test statistics for pairwise comparison of periods 1961-1990, 1991-2019, and 2071-2100, Table S3: Two-sided hypothesis-test statistics for the significance of slope within the scenarios, Table S4: Two-sided test statistics for pairwise comparison for the difference of slopes, Table S5: Two-sided hypothesis-test statistics for the significance of intercept of random effect (site) within the historical time series.  
Conceptualization, D.Z. and W.R.; methodology, D.Z., A.R., and R.H.; software, D.Z.; validation, D.Z.; formal analysis, D.Z.; investigation, D.Z.; resources, W.R.; data curation, A.R., R.H., and J.M.; writing--original draft preparation, D.Z.; writing--review and editing, D.Z., W.R., H., A.R., and J.M.; visualization, D.Z.; supervision, W.R.; project administration, W.R.; funding acquisition, W.R. and J.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
We thank all colleagues who were involved in field sampling and laboratory measurements. We thank the Bayrische Landesanstalt fur Wald und Forstwirtschaft (LWF Freising) for providing the hydrological model LWF-BROOK90.  
The authors declare no conflict of interest.