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To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and 2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named ‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’, includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, and make future expansions.

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Understanding the linkages between structure and processes in soil landscapes involves analyses across several spatial and temporal scales. The transfer of information between scales requires the (1) identification of respective scale levels and (2) procedures for regionalization. Here, we present a multiparameter delineation of landform units and their attribution with typical Reference Soil Groups (RSG) of a landscape of NE Germany which is representative of young moraine regions. Data sources are a digital elevation model (DEM, 5 m × 5 m), a reference data set from sections of an intensively augered landscape, and expert knowledge. A conceptual digital soil map was constructed in the scale 1:5000 based on the Topographic Position Index (TPI). The methodology is applicable for multiscale analyses. Results are (1) the landform unit classified by digital terrain analysis of a DEM, (2) the attribution of RSG, and (3) the evaluation of the classification. Accuracy of the method was 57% overall, with 70% accuracy on typical erosional sites. The developed method allows identification of terrain‐related soil pattern with high spatial resolution in glacial‐drift areas. The high resolution of soil information can be used for delineation of management zones in precision farming, or as input for process studies and models requiring a translation of typological soil information into relevant soil properties (e.g., by pedotransfer functions).