Rainfall erosivity is the main driver of water-induced soil erosion. A ground radar-based data was used to prepare a rainfall erosivity map of Europe. This study shows that the radar-based data products are a valuable solution for estimating large-scale rainfall erosivity, especially in regions with limited station-based precipitation data. A rainfall erosivity ensemble was derived to give first insights into a future avenue for updatable pan-European rainfall erosivity predictions.

We assess if a simplistic model can simulate the timing of soil erosion and sediment transport (delivery) in several small agricultural catchments in North-West Europe. The findings show that the loss of soil in fields and the delivery of sediment to streams are related in complex (non-linear) ways through time which impact our knowledge of soil redistribution. Furthermore, we show how adaptations of simplistic models can be used to reveal the missing processes which require future developments.

For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.

Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport, and deposition (ETD) of soil material. The present work developed ETD formulation, illustrated model calibration and validation for Europe, and presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models.

Erosion is a threat for soils with rainfall as the driving force. The annual rainfall erosivity factor quantifies rainfall impact by analysing high-resolution rainfall time series (~ 5 min). Due to a lack of measuring stations, alternatives for its estimation are analysed in this study. The best results are obtained for regionalisation of the erosivity factor itself. However, the identified minimum of 60-year time series length suggests using rainfall generators as in this study as well.