Bo Vangsø Iversen

2.9k total citations
98 papers, 2.3k citations indexed

About

Bo Vangsø Iversen is a scholar working on Environmental Engineering, Civil and Structural Engineering and Water Science and Technology. According to data from OpenAlex, Bo Vangsø Iversen has authored 98 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Environmental Engineering, 50 papers in Civil and Structural Engineering and 28 papers in Water Science and Technology. Recurrent topics in Bo Vangsø Iversen's work include Soil and Unsaturated Flow (48 papers), Groundwater flow and contamination studies (29 papers) and Hydrology and Watershed Management Studies (28 papers). Bo Vangsø Iversen is often cited by papers focused on Soil and Unsaturated Flow (48 papers), Groundwater flow and contamination studies (29 papers) and Hydrology and Watershed Management Studies (28 papers). Bo Vangsø Iversen collaborates with scholars based in Denmark, United States and Brazil. Bo Vangsø Iversen's co-authors include Per Schjønning, Per Møldrup, Mogens Humlekrog Greve, Lis Wollesen de Jonge, Tjalfe G. Poulsen, O. H. Jacobsen, Charlotte Kjærgaard, Mathieu Lamandé, P. Møldrup and Amélie Beucher and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Water Resources Research.

In The Last Decade

Bo Vangsø Iversen

97 papers receiving 2.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bo Vangsø Iversen Denmark 27 1.0k 900 885 391 306 98 2.3k
Mats Larsbo Sweden 29 1.3k 1.3× 938 1.0× 851 1.0× 363 0.9× 206 0.7× 75 2.6k
Lis W. de Jonge Denmark 27 819 0.8× 631 0.7× 938 1.1× 449 1.1× 134 0.4× 58 2.3k
John Koestel Sweden 31 1.7k 1.7× 1.2k 1.3× 1.3k 1.5× 324 0.8× 340 1.1× 66 3.2k
Annemieke I. Gärdenäs Sweden 23 917 0.9× 835 0.9× 835 0.9× 410 1.0× 345 1.1× 43 2.2k
Qing Zhu China 27 608 0.6× 789 0.9× 999 1.1× 672 1.7× 452 1.5× 119 2.6k
Toshiko Komatsu Japan 31 1.7k 1.7× 640 0.7× 1.4k 1.5× 188 0.5× 258 0.8× 113 3.0k
Bernd Huwe Germany 28 561 0.5× 1.0k 1.1× 722 0.8× 442 1.1× 388 1.3× 103 2.7k
Lichun Wang China 29 572 0.5× 684 0.8× 1.1k 1.2× 287 0.7× 243 0.8× 113 2.8k
Dongli She China 28 611 0.6× 1.1k 1.2× 528 0.6× 534 1.4× 380 1.2× 131 2.5k
Ryan D. Stewart United States 23 650 0.6× 841 0.9× 589 0.7× 241 0.6× 311 1.0× 115 2.1k

Countries citing papers authored by Bo Vangsø Iversen

Since Specialization
Citations

This map shows the geographic impact of Bo Vangsø Iversen'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 Bo Vangsø Iversen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bo Vangsø Iversen more than expected).

Fields of papers citing papers by Bo Vangsø Iversen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bo Vangsø Iversen. 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 Bo Vangsø Iversen. The network helps show where Bo Vangsø Iversen may publish in the future.

Co-authorship network of co-authors of Bo Vangsø Iversen

This figure shows the co-authorship network connecting the top 25 collaborators of Bo Vangsø Iversen. A scholar is included among the top collaborators of Bo Vangsø Iversen 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 Bo Vangsø Iversen. Bo Vangsø Iversen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gelbrecht, Jörg, Rasmus Jes Petersen, David Rayner, et al.. (2025). A comprehensive porewater survey of European peatlands reveals sustained elevated phosphorus levels after 10–20 years of rewetting. Geoderma. 463. 117554–117554.
2.
Gomes, Lucas Carvalho, Amélie Beucher, Anders Bjørn Møller, et al.. (2023). Soil assessment in Denmark: Towards soil functional mapping and beyond. SHILAP Revista de lepidopterología. 3. 17 indexed citations
3.
Therrien, René, et al.. (2023). 3D surface–subsurface modeling of a bromide tracer test in a macroporous tile‐drained field: Improvements and limitations. Soil Science Society of America Journal. 87(3). 462–484. 1 indexed citations
4.
Iversen, Bo Vangsø, et al.. (2023). Effect of different underlying surfaces on hydraulic parameters of overland flow. Soil and Tillage Research. 232. 105776–105776. 12 indexed citations
5.
Ferré, Ty P. A., et al.. (2022). Using machine learning to predict optimal electromagnetic induction instrument configurations for characterizing the shallow subsurface. Hydrology and earth system sciences. 26(1). 55–70. 5 indexed citations
6.
7.
Petersen, Rasmus Jes, et al.. (2020). Riparian Lowlands in Clay Till Landscapes Part II: Nitrogen Reduction and Release Along Variable Flow Paths. Water Resources Research. 56(4). 13 indexed citations
8.
Nagy, Dávid, Annette E. Rosenbom, Bo Vangsø Iversen, Mohamed Jabloun, & Finn Plauborg. (2020). Estimating the degree of preferential flow to drainage in an agricultural clay till field for a 10-year period. 5 indexed citations
9.
Nagy, Dávid, Annette E. Rosenbom, Bo Vangsø Iversen, & Finn Plauborg. (2020). Effect of preferential transport and coherent denitrification on leaching of nitrate to drainage. 6 indexed citations
10.
Møller, Anders Bjørn, et al.. (2020). Predicting tile drainage discharge using machine learningalgorithms. 2 indexed citations
11.
12.
Petersen, Rasmus Jes, et al.. (2020). Riparian Lowlands in Clay Till Landscapes: Part I—Heterogeneity of Flow Paths and Water Balances. Water Resources Research. 56(4). 18 indexed citations
13.
Koganti, Triven, et al.. (2019). Evaluating the Performance of a Frequency-Domain Ground Penetrating Radar and Multi-Receiver Electromagnetic Induction Sensor to Map Subsurface Drainage in Agricultural Areas. Ghent University Academic Bibliography (Ghent University). 3 indexed citations
14.
Petersen, Rasmus Jes, et al.. (2019). Locating tile drainage outlets and surface flow in riparian lowlands using thermal infrared and RGB-NIR remote sensing. Geografisk Tidsskrift-Danish Journal of Geography. 119(1). 94–105. 7 indexed citations
15.
Hansen, Anne Lausten, Rasmus Jakobsen, Jens Christian Refsgaard, et al.. (2018). Groundwater dynamics and effect of tile drainage on water flow across the redox interface in a Danish Weichsel till area. Advances in Water Resources. 123. 23–39. 22 indexed citations
16.
Højberg, Anker Lajer, et al.. (2018). Testing the use of Drain Flow Measurements to guide Calibration and Improving Local Scale Model Performance in a Distributed Hydrological Catchment Model for a Danish Glacial Till Area. AGUFM. 2018. 1 indexed citations
17.
Therrien, René, et al.. (2017). Simulating seasonal variations of tile drainage discharge in an agricultural catchment. Water Resources Research. 53(5). 3896–3920. 45 indexed citations
18.
Kjærgaard, Charlotte, et al.. (2015). Drainage filter technologies to mitigate site-specific phosphorus losses in agricultural drainage discharge. 1 indexed citations
19.
Salm, C. van der, Rémi Dupas, Ruth Grant, et al.. (2011). Predicting Phosphorus Losses with the PLEASE Model on a Local Scale in Denmark and the Netherlands. Journal of Environmental Quality. 40(5). 1617–1626. 14 indexed citations
20.
Keur, Peter van der & Bo Vangsø Iversen. (2006). Uncertainty in soil physical data at river basin scale – a review. Hydrology and earth system sciences. 10(6). 889–902. 14 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.

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