Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Rates and spatial variations of soil erosion in Europe: A study based on erosion plot data
2010553 citationsAndreas Klik, Svetla Rousseva et al.profile →
Rainfall erosivity in Europe
2015500 citationsPanos Panagos, Cristiano Ballabio et al.The Science of The Total Environmentprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Svetla Rousseva
Since
Specialization
Citations
This map shows the geographic impact of Svetla Rousseva's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Svetla Rousseva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Svetla Rousseva more than expected).
This network shows the impact of papers produced by Svetla Rousseva. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Svetla Rousseva. The network helps show where Svetla Rousseva may publish in the future.
Co-authorship network of co-authors of Svetla Rousseva
This figure shows the co-authorship network connecting the top 25 collaborators of Svetla Rousseva.
A scholar is included among the top collaborators of Svetla Rousseva based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Svetla Rousseva. Svetla Rousseva is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Rousseva, Svetla, et al.. (2017). Sensitivity Analysis of Predicted Soil Loss from Erosion to Its Determining Factors.
4.
Rousseva, Svetla, et al.. (2017). Factors and Risk of Soil Erosion by Water and Wind in the Zone of Bulgarian Chernozems.
5.
Rousseva, Svetla, et al.. (2016). SOIL EROSION RISK ASSESSMENTS USING GIS TECHNOLOGIES BULGARIAN EXPERIENCE. Bulgarian Journal of Agricultural Science. 22(2). 205–208.4 indexed citations
6.
Panagos, Panos, Cristiano Ballabio, Pasquale Borrelli, et al.. (2015). Rainfall erosivity in Europe. The Science of The Total Environment. 511. 801–814.500 indexed citations breakdown →
7.
Rousseva, Svetla, et al.. (2014). Sensitivity Analysis of the USLE Soil Erodibility Factor to Its Determining Parameters. EGU General Assembly Conference Abstracts. 650.1 indexed citations
8.
Rousseva, Svetla, et al.. (2014). Soil Water Retention as Indicator for Soil Physical Quality - Examples from Two SoilTrEC European Critical Zone Observatories. EGUGA. 5970.2 indexed citations
Rousseva, Svetla, et al.. (2009). Soil erosion rates at field plot studies in Bulgaria. GeCAS. 73.1 indexed citations
14.
Rousseva, Svetla, et al.. (2009). Mapping the factors and soil erosion risk in Bulgaria.. 43(2). 30–41.1 indexed citations
15.
Lipiec, Jerzy, et al.. (2003). Effect of soil compaction on root growth and crop yield in Central and Eastern Europe. International Agrophysics. 17(2). 61–69.77 indexed citations
16.
Rousseva, Svetla, et al.. (2002). Databank on the field plots for soil erosion studies in Bulgaria.. 1635–1645.2 indexed citations
17.
Rousseva, Svetla, et al.. (2000). Studies on subsoil compaction by tillage and traffic in Bulgaria: a review.. 388–396.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.