Soil erosion modelling: A bibliometric analysis.

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.

Soil erosion modelling: A global review and statistical analysis.

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.

A synoptic land change assessment of Ethiopia's Rainfed Agricultural Area for evidence-based agricultural ecosystem management.

This paper demonstrates synoptic ways of presenting and characterizing land change processes across Ethiopia's large, complex Rainfed Agricultural Area (RAA). We translated pixel-level detected changes into neighbourhood-level changes that are useful to decision-makers. First, we identified pixel-level changes without and with type/direction of change, based on land cover maps from the years 1986 and 2010. For type-/direction-based characterization, we sorted observed transitions into four categories of prominent land change processes ("forest degradation", "deforestation", "afforestation", and "no change"). Adopting appropriate window sizes for identified ecoregions in the study area, we ran a focal statistics summation operator separately on the two change rasters (with/without consideration of direction of change). The results obtained by applying the approach can be described in relative terms as well as qualitative terms, using ranges of change values that can be further classified using qualitative terms, i.e. ranging from "no change" to "high/substantial change". Our non-directional change assessment result showed that approximately 6% of the RAA is characterized by substantial change, whereas 40% appears stable ("no change"). Based on the directional-change assessment results, 3% of deforestation, 4% of forest degradation, and 3% of revegetation processes were found to constitute "high/substantial change". The types and intensity of landscape transformations display distinct spatial patterns linked to agro-ecological belts and socio-economic dynamics. Minimal reverse changes were observed on some severely degraded lands in the highlands, but the overall per cent cover remains relatively small. Overall, vegetation degradation still exceeds regeneration by more than half a per cent. Relatively lower altitudes and middle altitudes exhibit higher transformation. The presented approach and resulting outputs can provide planners and decision-makers with a synoptic view of land change processes. It can support policy formulation of sustainable land management and rehabilitation activities of the agricultural ecosystem at national and regional scales.