| Summary: | Water erosion is the main cause of soil degradation in agricultural areas. Rill erosion can contribute vastly to the overall erosion rate. It is therefore crucial to identify areas prone to rill erosion in order to protect soil quality. Research on rainfall-runoff and subsequent sediment transport processes is often based on observing these processes at several scales, followed by a mathematical description of the observations. This paper presents the use of a combination of data obtained by different approaches at multiple scales to validate the SMODERP2D episodic hydrological-erosion model. This model describes infiltration, surface retention, surface runoff, and rill flow processes. In the model, the surface runoff generation is based on a water balance equation and is described by two separate processes: (a) for sheet flow, the model uses the kinematic wave approximation, which has been parameterized for individual soil textural classes using laboratory rainfall simulations, and (b) for rill flow, the Manning formula is used. Rill flow occurs if the critical water level of sheet flow is exceeded. The concept of model validation presented here uses datasets at different scales to study the surface runoff and erosion processes on the Býkovice agricultural catchment. The first dataset consisted of runoff generated by simulated rainfall on plots with dimensions of 2 × 8 m. The second dataset consisted of the runoff response to natural rainfall events obtained from long-term monitoring of 50 m<sup>2</sup> plots. These two datasets were used to validate and calibrate the sheet flow and infiltration parameters. The third dataset consisted of occurrence maps of rills formed during heavy rainfalls obtained using remote sensing methods on a field plot with an area of 36.6 ha. This last dataset was used to validate the threshold critical water level that is responsible in the model for rill flow initiation in the SMODERP2D model. The validation and the calibration of the surface runoff are performed well according to the Nash–Sutcliffe efficiency coefficient. The scale effect was evident in the 50 m<sup>2</sup> plots where parameters lower than the mean best fit the measured data. At the field plot scale, pixels with measured rills covered 5% of the total area. The best model solution achieved a similar rill cover for a vegetated soil surface. The model tended to overestimate the occurrence of rills in the case of simulations with bare soil. Although rills occurred both in the model and in the monitored data in many model runs, a spatial mismatch was often observed. This mismatch was caused by flow routing algorithm displacement of the runoff path. The suitability of the validation and calibration process at various spatial scales has been demonstrated. In a future study, data will be obtained from various localities with various land uses and meteorological conditions to confirm the transferability of the procedure.
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