Importance of different imperviousness measures for predicting runoff and nutrient emissions from non-urban and urban land-uses at large spatial coverage.

Growing population and urbanization challenge water resources sustainability and require stringent solutions in terms of emission measurements and pollution controls. Advancements in observation techniques have improved the availability of impervious surface data that cover both urban and non-urban areas to assess the impacts of urbanization. However, most models used in macroscale studies continue to derive surface imperviousness based on land-use classes and population data, and the contributions of non-urban impervious surfaces to runoff and nutrient emissions remain largely ignored. Effects of different impervious surface data on the predicted runoff and nutrient emissions is investigated in this study for macroscale urban and non-urban areas in tandem by means of an extended urban module MONERIS - PCRaster to enable scenarios with high-resolution imperviousness data. The results showed that approximately 70% of the total runoff and nutrient emissions nationwide originated from low-to-medium populated impervious surfaces rather than from major urban catchments. Using high-resolution imperviousness data at various aggregation levels resulted in lower biased outputs of predicted runoff and nutrient emissions when compared to results using the estimated impervious data from land-use and population information. The impervious surface shares between urban and non-urban lands revealed the opposite trends of urbanization developments in the less populated areas versus an increasing contribution of emissions from non-urban areas rather than urban centers in densely populated municipalities. Overall, the non-urban impervious surface areas contributed 5-20% of the "hidden" runoff volumes and nutrient emissions from all impervious areas. The results of this study highlight the need of model adaptations regarding the increased availability of high-resolution imperviousness data and the trend of urbanization development beyond urban areas for more accurate quantification of potential flood risks and emission hotspots of macroscale urbanized areas for sustainable water resources management.

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.

The potential of large floodplains to remove nitrate in river basins - The Danube case.

Floodplains remove nitrate from rivers through denitrification and thus improve water quality. The Danube River Basin (DRB) has been affected by elevated nitrate concentrations and a massive loss of intact floodplains and the ecosystem services they provide. Restoration measures intend to secure and improve these valuable ecosystem services, including nitrate removal. Our study provides the first large-scale estimate of the function of large active floodplains in the DRB to remove riverine nitrate and assesses the contribution of reconnection measures. We applied a nutrient emission model in 6 river systems and coupled it with denitrification and flooding models which we adapted to floodplains. The floodplains have the capacity to eliminate about 33,200 t nitrate-N annually, which corresponds to 6.5 % of the total nitrogen emissions in the DRB. More nitrate is removed in-stream at regular flow conditions than in floodplain soils during floods. However, increasing frequently inundated floodplain areas reveals greater potential for improvement than increasing the channel network. In total, we estimate that 14.5 % more nitrate can be removed in reconnected floodplains. The largest share of nitrogen emissions is retained in the Yantra and Tisza floodplains, where reconnections are expected to have the greatest impact on water quality. In absolute numbers, the floodplains of the lower Danube convert the greatest quantities of nitrate, driven by the high input loads. These estimates are subject to uncertainties due to the heterogeneity of the available input data. Still, our results are within the range of similar studies. Reconnections of large floodplains in the DRB can, thus, make a distinct contribution to improving water quality. A better representation of the spatial configuration of water quality functions and the effect of floodplain reconnections may support the strategic planning of such to achieve multiple benefits and environmental targets.

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.