Terrestrial biogeochemical models are essential tools to quantify climate–carbon cycle feedback and plant–soil relations from local to global scale. In this study, a theoretical basis is provided for the latest version of the Biome-BGCMuSo biogeochemical model (version 6.2). Biome-BGCMuSo is a branch of the original Biome-BGC model with a large number of developments and structural changes. Earlier model versions performed poorly in terms of soil water content (SWC) dynamics in different environments. Moreover, lack of detailed nitrogen cycle representation was a major limitation of the model. Since problems associated with these internal drivers might influence the final results and parameter estimation, additional structural improvements were necessary. In this paper the improved soil hydrology as well as the soil carbon and nitrogen cycle calculation methods are described in detail. Capabilities of the Biome-BGCMuSo v6.2 model are demonstrated via case studies focusing on soil hydrology, soil nitrogen cycle, and soil organic carbon content estimation. Soil-hydrology-related results are compared to observation data from an experimental lysimeter station. The results indicate improved performance for Biome-BGCMuSo v6.2 compared to v4.0 (explained variance increased from 0.121 to 0.8 for SWC and from 0.084 to 0.46 for soil evaporation; bias changed from −0.047 to −0.007 m³ m⁻³ for SWC and from −0.68 to −0.2 mm d⁻¹ for soil evaporation). Simulations related to nitrogen balance and soil CO₂ efflux were evaluated based on observations made in a long-term field experiment under crop rotation. The results indicated that the model is able to provide realistic nitrate content estimation for the topsoil. Soil nitrous oxide (N₂O) efflux and soil respiration simulations were also realistic, with overall correspondence with the observations (for the N₂O efflux simulation bias was between −0.13 and −0.1 $\mathrm{mg}\mathrm{N}{\mathrm{m}}^{-\mathrm{2}}{\mathrm{d}}^{-\mathrm{1}}$ , and normalized root mean squared error (NRMSE) was 32.4 %–37.6 %; for CO₂ efflux simulations bias was 0.04–0.17 $\mathrm{g}\mathrm{C}{\mathrm{m}}^{-\mathrm{2}}{\mathrm{d}}^{-\mathrm{1}}$ , while NRMSE was 34.1 %–40.1 %). Sensitivity analysis and optimization of the decomposition scheme are presented to support practical application of the model. The improved version of Biome-BGCMuSo has the ability to provide more realistic soil hydrology representation as well as nitrification and denitrification process estimation, which represents a major milestone.

Climate change and water scarcity increase the vulnerability of crop production and other ecosystem services (ES) in flood-protected lowlands under a continental climate. Restoration of wetlands leads to a higher water-buffering capacity of the landscape, strengthening various ecosystem services, and fostering adaptation to climatic, ecological, and agricultural challenges. Such restoration efforts require extensive land-use change, leading to trade-offs in provisioning and regulating ES. However, knowledge is limited about these situations, especially in the case of lowland areas. Here, we introduce a hydrological analysis in a 243 km² flood-protected catchment in the Great Hungarian Plain, mapping the potential hydrological effects of water-retention scenarios on groundwater levels. We point out how the simulated groundwater levels will be used for estimating the changes in crop yields and tree growth (provisioning services). The introduced hydrological analysis and preliminary results for crop-yield estimates suggest a significant and scalable capacity for a nature-based hydrological adaptation: the extent of inundated areas could be increased stepwise and water retention could locally compensate dry periods due to the buffering effect of inundated meanders.

Central and Eastern Europe (CEE) is a pillar of global wheat and maize production. However, certain areas within the CEE region have become climate change hotspots, experiencing intensifying water deficits and drought pressure, rising mean and maximum temperatures. This study focuses on the long-term statistical relationships between climatic factors and rain-fed wheat and maize yields for different landscape types in Hungary over 30-year time windows between 1921 and 2010. The relationship between the variances of the detrended climatic parameters and crop yields was tested employing both simple and multifactorial linear models according to landscape types and periods. The sensitivity of wheat yields to spring–summer mean temperature shifted dynamically from the western part of the country to east (from cooler and wetter hilly landscapes to plains) between the periods 1921–1950 and 1981–2010. The cooling observed in summer temperature between the periods 1921–1950 and 1951–1980 supported an increase in wheat yields by an estimated 0.11–0.43 t ha⁻¹ year⁻¹, while the 0.9–1.2 °C warming of May–July temperature may have cut wheat yields by an estimated 0.44–0.56 t ha⁻¹ year⁻¹ in various regions over 1981–2010. That being said, the regional sensitivity of wheat yields to May–July mean temperature did not display substantial differences between the periods 1921–1950 and 1981–2010. Besides negative effects, climate change had a positive impact on wheat yields, since increasing January–March mean temperatures mitigated the negative impact of warming summer temperatures on wheat yields by an estimated 16–34% over 1981–2010. In this 30-year period, increasing mean temperature together with decreasing precipitation explained 46–75% of the variances in maize yields reducing annual maize harvests by an estimated 11.1–12.4% year⁻¹.

Historical trends in water management and recent climatic variations put wetlands in the Carpathian basin under strong pressure and led to their degradation. The lack of extended site specific environmental data series inhibits the understanding of long-term eco-hydrological processes. This undermines the success of restoration and/or management efforts. As a precedent we analyzed a recently degraded Hungarian lowland wetland, the Nyárjas fen in order to identify the main cause of its drying. Our method is based on one-dimensional simulations of a variably saturated soil column representing the dominant hydrological conditions of the wetland. To properly define the necessary soil hydraulic parameters, soil sampling, laboratory measurements and inverse modelling were carried out. The hydrological simulations for the 1961-2010 period clearly suggest that (i) the wetland degraded due to a temporal unfavorable combination of regional groundwater depletion and decreased precipitation, (ii) and could not recover afterwards despite the improvement of hydrological conditions. The ecological water demand of the Nyárjas fen can be explicitly expressed in terms of groundwater level. However, water availability is a necessary, but not sufficient criteria of good habitat status. The elaborated methodology provides the basis of bottom-up type environmental water demand estimation on a regional/national scale.

Accurate knowledge of groundwater levels and flow conditions in the vicinity of groundwater-dependent terrestrial ecosystems (GWDTE-s) is required for identifying groundwater dependency and comparing the present situation with the optimal one, as part of the status assessment of groundwaters according to the EU Water Framework Directive. Geostatistical methods (like kriging or cokriging) may result in an unrealistic groundwater level map if only a few measured data are available. In this paper a new, grid-based, deterministic method (GSGW-model) is introduced. The aim of the model is to calculate groundwater depth within the required accuracy from sparse data of monitoring wells. The basic principle of the GSGW-model is that the groundwater table is a smoothed replica of the ground surface. Hence, changes in the groundwater level between two grid points are calculated as a function of the digital elevation model (DEM) and soil properties. The GSGW-model was tested in the Nyírség region (Hungary). Results were compared with those gained by ordinary kriging and cokriging. It has been concluded that kriging overestimates the groundwater level in the low part of the test area, where wetlands are located, while the maps produced by the GSGW-model are a better fit of the real variability, providing more reliable estimates of groundwater depth in GWDTE-s as well.

Lowland forests benefiting from groundwater availability are important ecosystems in Central Europe, both from ecological and economic perspectives. Besides a great reduction in their extent in the historical times and further shifts in the land use and water management regimes intensified during the industrial era, continuing changes in the groundwater and overall hydro-climatic conditions can pose significant challenges to them. Although tree-ring analyses serve as widely used tools to assess the climatic impact on tree growth and vitality, few studies have attempted to investigate the effects of subsurface hydrology on interannual fluctuations in xylem production. In this study, we compared the tree-ring width series of pedunculate oak (Quercus robur L.) from a forested area in southwestern Hungary with the time series of monthly groundwater depth and climatic variables over the period of 1920–2017 with a specific focus on 1961–2017. The radial growth of the studied trees showed the strongest relationship with late winter and early spring groundwater and drought conditions preceding the growing season, differing from the commonly reported climatic signals marked by early summer meteorological conditions of the vegetation season. The results suggest that the groundwater recharge during the dormant period preceding the vegetation season and the groundwater levels in early spring were among the key limiting factors on tree growth in the study area. In the growing years starting with a sufficiently high groundwater table, even scarce summer precipitation did not seem to limit radial growth drastically. However, unfavorable shifts in climatic conditions during the past few decades and the associated uncertainties in the future groundwater regime imply that additional active measures aimed at maintaining and restoring groundwater conditions may well be highly beneficial for sustaining groundwater-dependent forest ecosystems and their productivity.