Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper.

Reservoir and lake sedimentation is a vital problem in Ethiopia. Constructing small and medium size dams at the outlets of sub-catchments within larger catchment helps to reduce the transport of sediment downstream to reservoirs or lakes. This study assessed the sediment trapping efficacy (STE) of sediment storage dams (SSDs) built at the outlets of eight small sub-catchments in northwest Ethiopia, as an off-site sediment trapping measure. Satellite imagery and topographic maps were used to assess land use/land cover and delineate the boundaries of sub-catchments. In the field, trapped sediment by SSDs was measured directly, as well as in- and outflow of suspended sediment with which the STE of each SSD was estimated. Sediment yield of each sub-catchment was calculated from the measured trapped sediment and estimated suspended sediment loss. Results show that SSDs trapped an average of 1584 t yr-1 of the inflow sediment and catchment specific sediment yield ranged from 8.6-55 t ha-1 yr-1. Two representative SSDs constructed from gabion and stone were evaluated with regard to their STE. Results showed that their efficacy was 74% and 67% for the gabion and stone SSD, respectively. In general, although SSDs might be costly for small scale farmers and have a relatively short life span depending on their size, they are promising off-site structural measures to trap significant amounts of sediment at the outlets of sub-catchments and subsequently reducing sediment movement to downstream water bodies.