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.

Rainfall erosivity in Slovenia: Sensitivity estimation and trend detection.

Slovenia is one of the EU countries with the largest values and largest amounts of variability in rainfall erosivity, with maximum annual values exceeding 10,000 MJ mm ha-1 h-1 yr-1. Five-minute rainfall data was analysed from 10 Slovenian rainfall stations with data-length availability longer than 25 years with a maximum data length of 69 years and a total data-station length equal to 443 years. Trends in the rainfall erosivity R-factor were detected for four different sub-samples using monthly, half-year, and annual rainfall erosivity values. The results indicate that rainfall erosivity trends for the selected Slovenian stations are mostly statistically insignificant, with the selected significance level of 0.05. However, a larger share of identified trends are positive than negative. The maximum annual rainfall erosivity values were obtained for one specific mountain station. Furthermore, a sensitivity analysis regarding the rainfall erosivity factor R calculation showed that the rainfall threshold parameter (12.7 mm) that is used to remove the small-magnitude rainfall events in order to reduce the computational burden can attribute up to 10% of the average annual R-values in cases where this threshold is not used. Other parameters have, on average, a smaller impact on the calculated rainfall erosivity. Furthermore, the application of local kinetic energy equations resulted in, on average, about 20% higher annual rainfall erosivity values compared to the equation that is proposed by the Revised Universal Soil Loss Equation (RUSLE) manual and was not developed specifically for this region.

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.

Public perception and stakeholder involvement in the crisis management of sediment-related disasters and their mitigation: the case of the Stoze debris flow in NW Slovenia.

Sediments can pose a threat to humans not only when these deposits are polluted but also due to their large quantities. This physical aspect of sediments as a risk will be shown on a case study of a sediment-related disaster that occurred in the mountainous part of Slovenia, Central Europe in 2000. In November 2000, after a long wet period a large debris landslide had been triggered on the Stoze slope and stopped in the channel of the Mangart creek. Such an event took the majority of local inhabitants and emergency staff by surprise. Nevertheless, they had just organized the first mitigation measures when, after 35 hours, they were surprised by an even larger debrisflowinitiated as the second phase of the same mass movement event. Within a few minutes, the wet debris flow had devastated the alpine valley of the Koritnica River and killed 7 people in the village of Log pod Mangartom. This paper deals with crisis management and first mitigation measures under this very tense situation of searching for dead bodies. The uncertainty about possible new debris flows drove all inhabitants out of the village by a decision of the civil protection unit, and also other activities of the emergency relief units were overshadowed by the 7 victims. One of the main problems and challenges at the same time was the over 700,000 m³ of wet debris flow deposits in the area of the village of Log pod Mangartom within the Triglav National park, which posed a direct threat of flooding during the first heavy rainfalls in spring 2001, and which were about to be removed to make place for future debris flows. The understanding about what really happened or about the immediate triggering factors was different among the professionals in charge for relief action and for preparing a final remediation plan. The first phase during and immediately after the disaster (relief intervention of emergency units especially those for civil protection) can be described as Concern-Driven Crisis Management or as Judgment-Based Crisis Management, respectively. The Quantitative Risk Assessment came into play in the second remediation phase through special law enforcement. Even after 10 years since the disaster, general public perception speaks in favor of judgment-based risk management rather than quantitative risk assessment, a situation that can be explained by the poor understanding of the system by local inhabitants, by low public involvement in the preparation of the final remediation plan undertaken by the state agencies, and by the fact that the final remediation is still not finished.