Lowland river basins are characterised by complex hydrologic and hydraulic interactions between the different subsystems (aerated zone, groundwater, surface water), which may require physically-based dynamically-coupled surface water and groundwater hydrological models to reliably describe these processes. Exemplarily, for a typical north-eastern Germany lowland catchment (Tollense river with about 400 km(2)), an integrated hydrological model, MIKE SHE, coupled with a hydrodynamic model, MIKE 11, was developed and assessed. Hydrological and hydraulic processes were simulated from 2010 to 2018, covering strongly varying meteorological conditions. To achieve a highly reliable model, the calibration was performed in parallel for groundwater levels and river flows at the available monitoring sites in the defined catchment. Based on sensitivity analysis, saturated hydraulic conductivity, leakage coefficients, Manning's roughness, and boundary conditions (BCs) were used as main calibration parameters. Despite the extreme soil heterogeneity of the glacial terrain, the model performance was quite reasonable in the different sub-catchments with an error of less than 2% for water balance estimation. The resulted water balance showed a strong dependency on land use intensity and meteorological conditions. During relatively dry hydrological years, actual evapotranspiration (ETa) becomes the main water loss component, with an average of 60%-65% of total precipitation and decreases to 55%-60% during comparatively wet hydrological years during the simulation period. Base flow via subsurface and drainage flow accounts for an approximate average of 30%-35% during wet years and rises up to 35%-45% of the total water budget during the dry hydrological years. This means, groundwater is in lowland river systems the decisive compensator of varying meteorological conditions. The coupled hydrologic and hydraulic model is valuable for detailed water balance estimation and seasonal dynamics of groundwater levels and surface water discharges, and, due to its physical foundation, can be extrapolated to analyse meteorological and land use scenarios. Future work will focus on coupling with nutrient transport and river water quality models.