An important component of the National Forest Soils Inventory (NFSI) is the investigation of inorganic and organic pollutants. Forests are able to filter out large quantities of these substances from the atmosphere and incorporate them into the soil for a long time. The aim of this study was the integrative evaluation of organic and inorganic pollutant concentrations in forest soils in the state of Brandenburg, Germany. With the help of principle component analysis, the pollutant concentrations can essentially be explained by three significant environmental components, which explain 76% of the total variance of all pollutants examined within the scope of the NFSI. The first component characterizes the extent of the atmospheric pollution caused by flue gases and fly ash from lignite combustion in the 1970s and 1980s and is mainly charged by the organic pollutants HCB and PAH, and the elements arsenic and chromium. This component shows positive relation to both spatially interpolated calcium-deposition data from the 1980s (as an indicator for the dust emission from coal combustion) and crown defoliation data of pine stands from the forest condition survey in the early 1990s. The depositions of zinc and cadmium from industrial sources, vehicle traffic and the use of fertilizers in agriculture mainly characterize the second principle component. The use of the pesticides DDT and lindane in the early 1980s and the associated pollutants input into the forest soils are expressed by the third component. In expanding the term archiving function of soils, the results illustrate their particular importance for the long-term archiving of anthropogenic inputs and the associated potential stress factors for forests.

To cope with the challenges in forest management that are contemporarily caused by climate change, data on current chemical and physical soil properties are more and more necessary. For this purpose, we present a further amalgam of depth functions and SCORPAN modelling to provide data at arbitrary depth layers. In this concept, regionalisation is split up into the modelling of plot totals and the estimation of vertical distributions. The intended benefits by splitting up are: consistency between estimates on plot level and depth layer level, avoidance of artificial depth gradients, straightforward interpretation of covariates in the sense of pedogenetic processes, and circumnavigation of the propagation of uncertainties associated with separation between horizons during field sampling. The methodology was tailored to the circumstances within the north-eastern lowlands and the utilisation of current inventory data of the National Forest Soil Inventory (NFSI) in Brandenburg (Germany). Using the regionalisation of soil organic carbon (SOC) as an example, the application is demonstrated and discussed in detail. The depth to groundwater table and terrain parameters related to the catchment area were the main factors in SOC storage. The use of kriging did not improve the model performance. The relative depth gradients of SOC were especially distinguished by tree species composition and stand age. We suppose that interesting fields of application may be found in scenario-based modelling of SOC and when SOC serves as a basis for hydrological modelling.

To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961–2019, and for climate change projections for the time period 2010–2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071–2100 compared to 1990–2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6.

Environmental services of mires and peatlands and negative impacts of their alteration are comprehensively documented. A spatial detection of these organic soils is therefore essential. This paper examines the detectability of organic soils in forests using open ge-ospatial and remote sensing data combined with mapped soil and water level infor-mation in two Random Forest (RF) approaches. Either surrounded in or covered by for-est, organic soils of the study region exhibit elevated soil water content reaching satura-tion during the hydrological winter. Consequently, terrain indices from Digital Elevation Models (DEM) and soil moisture from L-band ALOS PALSAR signals are used as pre-dictors in RF algorithms. CORINE Land Cover data help assess how different forest cov-er types (FCT) influence RF models. Substantial agreement is reached in the target classi-fication when FCT is included and when using the higher spatial resolution DEM. The Boolean approach is less affected by different compositions of predictor variables, but is more sensitive to the level of imbalance in the reference data. This becomes evident when comparing the “event error” and “no event error”. In all RF models, the variable importance of soil moisture pixel values retrieved from L-band ALOS PALSAR is the highest when FCT is not in-cluded.

Climate change is expected to alter hydro-climatic conditions and water availability across Central Europe, with important implications for vegetation and land-use systems. This study assesses projected changes in climatic water balance (CWB), hydro-climatic stress indicators, and their relationship with root-zone soil moisture in Brandenburg, Germany. Four regional climate model realizations under RCP4.5 and RCP8.5 were analyzed for 2006–2100. Air temperature (tas), precipitation (pr), reference evapotranspiration (ET₀), and CWB were evaluated together with indicators describing drought frequency, water-deficit magnitude, aridity, and standardized CWB anomalies. All model realizations project substantial warming, exceeding +2 °C under RCP8.5 by the late century. While annual precipitation remains relatively stable, vegetation-period precipitation decreases and evaporative demand increases, resulting in increasingly negative growing-season CWB. Projected vegetation-period CWB changes range from −22 to −139 mm between near-future and far-future periods. Hydro-climatic stress indicators consistently show increasing seasonal water limitation. Comparisons between CWB and root-zone soil moisture reveal significant positive relationships (p < 0.001), although explanatory power remains low (R² < 0.14). Despite differences in the magnitude of projected changes, all model realizations agree on the direction of change, indicating a robust signal of increasing growing-season drying. These findings highlight the importance of seasonal hydro-climatic indicators for assessing future drought risk and ecosystem water availability.