Natural flood management (NFM) is widely promoted for managing flood risks but the effectiveness of different types of NFM schemes at medium (100–1000 km²) and large scales (>1000 km²) remains widely unknown. This study demonstrates the importance of fully understanding the impact of model structure, calibration and uncertainty techniques on the results before the NFM assessment is undertaken. Land-based NFM assessment is undertaken in two medium-scale lowland catchments within the Thames River basin (UK) with a modelling approach that uses the Soil and Water Assessment Tool (SWAT) model within an uncertainty framework. The model performed poorly in groundwater-dominated areas (P-factor <0.5 and R-factor >0.6). The model performed better in areas dominated by surface and interflow processes (P-factor >0.5 and R-factor <0.6) and here hypothetical experiments converting land to broadleaf woodland and cropland showed that the model offers good potential for the assessment of NFM effectiveness. However, the reduction of large flood flows greater than 4% in medium-sized catchments would require afforestation of more than 75% of the area. Whilst hydrological models, and specifically SWAT, can be useful tools in assessing the effectiveness of NFM, these results demonstrate that they cannot be applied in all settings.