57 research outputs found
A global bibliometric perspective on soil erosion modelling
Systematic bibliometric investigations are useful to evaluate and compare the scientific impact of
journal papers, book chapters and conference proceedings. Such studies allow the detection of
emerging research topics, the analyses of cooperation networks, and the collection of in-depth
insights into a specific research topic. In the presented work, we carried out a bibliometric study in
order to obtain an in-depth knowledge on soil erosion modelling applications worldwide.
As a starting point, we used the soil erosion modelling meta-analysis data collection generated by
the authors of this abstract in a joint community effort. This database contains meta-information
of more than 3,000 documents published between 1994 and 2018 that are indexed in the SCOPUS
database. The documents were reviewed and database entries verified. The database contains
various types of meta-information about the modelling studies (e.g., model used, study area, input
data, calibration, etc.). The bibliometric information was also included in the database (e.g.,
number of citations, type of publication, Scopus category, etc.). We investigated differences among
publication types and differences between papers published in journals that are part of various
Scopus categories. Moreover, relationships between publication CiteScore, number of authors,
and number of citations were analyzed. A boosted regression tree model was used to detect the
relative impact of the selected meta-information such as erosion model used, spatial modelling
scale, study period, field activity on the total number of citations. Detailed investigation of the
most cited papers was also conducted. The VOSviewer software was used to analyze citations, cocitations,
bibliographic coupling, and co-authorship networks of the database entries.
Our bibliometric investigations demonstrated that journal publications, on average, receive more
citations than book series or conference proceedings. There were differences among the erosion
models used, and some specific models such as the WaTEM/SEDEM model, on average, receive
more citations than other models (e.g., USLE). It should also be noted that self-citation rates in
case of most frequently used models were similar. Global studies, on average, receive more
citations than studies dealing with plot, regional, or national scales. According to the boosted
regression tree model, model calibration, validation, or field activity do not have significant impact
on the obtained publication citations. Co-citation investigation revealed some interesting patterns.
Our results also indicate that papers about soil erosion modeling also attract citations from
different fields and better international cooperation is needed to advance this field of research
with regard to its visibility and impact on human societies
A large sample analysis of European rivers on seasonal river flow correlation and its physical drivers
The geophysical and hydrological processes governing river flow formation exhibit persistence at several timescales, which may manifest itself with the presence of positive seasonal correlation of streamflow at several different time lags. We investigate here how persistence propagates along subsequent seasons and affects low and high flows. We define the high-flow season (HFS) and the low-flow season (LFS) as the 3-month and the 1-month periods which usually exhibit the higher and lower river flows, respectively. A dataset of 224 rivers from six European countries spanning more than 50 years of daily flow data is exploited. We compute the lagged seasonal correlation between selected river flow signatures, in HFS and LFS, and the average river flow in the antecedent months. Signatures are peak and average river flow for HFS and LFS, respectively. We investigate the links between seasonal streamflow correlation and various physiographic catchment characteristics and hydro-climatic properties. We find persistence to be more intense for LFS signatures than HFS. To exploit the seasonal correlation in the frequency estimation of high and low flows, we fit a bi-variate meta-Gaussian probability distribution to the selected flow signatures and average flow in the antecedent months in order to condition the distribution of high and low flows in the HFS and LFS, respectively, upon river flow observations in the previous months. The benefit of the suggested methodology is demonstrated by updating the frequency distribution of high and low flows one season in advance in a real-world case. Our findings suggest that there is a traceable physical basis for river memory which, in turn, can be statistically assimilated into high- and low-flow frequency estimation to reduce uncertainty and improve predictions for technical purposes
Brief communication: A first hydrological investigation of extreme August 2023 floods in Slovenia, Europe
Extreme floods occurred from 4 to 6 August 2023 in Slovenia causing three casualties and causing total direct and indirect damage, including post-disaster needs according to the Post-Disaster Needs Assessment (PDNA), close to EUR 10 billion. The atypical summer weather conditions combined with the high air and sea temperatures in the Mediterranean and the high soil moisture led to the most extreme flood event in Slovenia in recent decades. The return periods of both daily and sub-daily precipitation extremes and peak discharges reached 250–500 years, and the runoff coefficient of a typical torrential and mostly forested mesoscale catchment was around 0.5. In addition, flooding, soil erosion, mass movements and river sediment transport processes caused major damage to buildings (more than 12 000 houses) and diverse infrastructure.</p
Quality assessment of cadmium telluride as a detector material for multispectral medical imaging
Cadmiumtelluride (CdTe) is a high-Z material with excellent photon radiation absorption properties, making it a promising material to include in radiation detection technologies. However, the brittleness of CdTe crystals as well as their varying concentration of defects necessitate a thorough quality assessment before the complex detector processing procedure. We present our quality assessment of CdTe as a detector material for multispectralmedical imaging, a research which is conducted as part of the Consortium Project Multispectral Photon-counting for Medical Imaging and Beam characterization (MPMIB). The aim of the project is to develop novel CdTe detectors and obtain spectrum-per-pixel information that make the distinction between different radiation types and tissues possible. To evaluate the defect density inside the crystals - which can deteriorate the detector performance - we employ infrared microscopy (IRM). Posterior data analysis allows us to visualise the defect distributions as 3D defect maps. Additionally, we investigate front and backside differences of the material with current-voltage (IV) measurements to determine the preferred surface for the pixelisation of the crystal, and perform test measurements with the prototypes to provide feedback for further processing. We present the different parts of our quality assessment chain and will close with first experimental results obtained with one of our prototype photon-counting detectors in a small tomographic setup.Peer reviewe
EUSEDcollab: a network of data from European catchments to monitor net soil erosion by water
As a network of researchers we release an open-access database (EUSEDcollab) of water discharge and suspended sediment yield time series records collected in small to medium sized catchments in Europe. EUSEDcollab is compiled to overcome the scarcity of open-access data at relevant spatial scales for studies on runoff, soil loss by water erosion and sediment delivery. Multi-source measurement data from numerous researchers and institutions were harmonised into a common time series and metadata structure. Data reuse is facilitated through accompanying metadata descriptors providing background technical information for each monitoring station setup. Across ten European countries, EUSEDcollab covers over 1600 catchment years of data from 245 catchments at event (11 catchments), daily (22 catchments) and monthly (212 catchments) temporal resolution, and is unique in its focus on small to medium catchment drainage areas (median = 43 km(2), min = 0.04 km(2), max = 817 km(2)) with applicability for soil erosion research. We release this database with the aim of uniting people, knowledge and data through the European Union Soil Observatory (EUSO)
An integrated 1D–2D hydraulic modelling approach to assess the sensitivity of a coastal region to compound flooding hazard under climate change
Coastal regions are dynamic areas that often lie at the junction of different natural hazards. Extreme events such as storm surges and high precipitation are significant sources of concern for flood management. As climatic changes and sea-level rise put further pressure on these vulnerable systems, there is a need for a better understanding of the implications of compounding hazards. Recent computational advances in hydraulic modelling offer new opportunities to support decision-making and adaptation. Our research makes use of recently released features in the HEC-RAS version 5.0 software to develop an integrated 1D–2D hydrodynamic model. Using extreme value analysis with the Peaks-Over-Threshold method to define extreme scenarios, the model was applied to the eastern coast of the UK. The sensitivity of the protected wetland known as the Broads to a combination of fluvial, tidal and coastal sources of flooding was assessed, accounting for different rates of twenty-first century sea-level rise up to the year 2100. The 1D–2D approach led to a more detailed representation of inundation in coastal urban areas, while allowing for interactions with more fluvially dominated inland areas to be captured. While flooding was primarily driven by increased sea levels, combined events exacerbated flooded area by 5–40% and average depth by 10–32%, affecting different locations depending on the scenario. The results emphasise the importance of catchment-scale strategies that account for potentially interacting sources of flooding
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\u27s 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 comprehensivelyreviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the re-gions 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 per-form this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. Theresulting database, named‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’, includes 3030 indi-vidual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluatedand transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insightsinto the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to sup-port the upcoming country-based United Nations global soil-erosion assessment in addition to helping to informsoil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is anopen-source database available to the entire user-community to develop research, rectify errors, andmakefutureexpansion
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 ErosionModelling 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- erosionmodels and model applicationsworldwide. 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, andmake future
expansions
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
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