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.
PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model
2018384 citationsEdwin H. Sutanudjaja, Rens van Beek et al.Geoscientific model developmentprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Kor de Jong'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 Kor de Jong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kor de Jong more than expected).
This network shows the impact of papers produced by Kor de Jong. 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 Kor de Jong. The network helps show where Kor de Jong may publish in the future.
Co-authorship network of co-authors of Kor de Jong
This figure shows the co-authorship network connecting the top 25 collaborators of Kor de Jong.
A scholar is included among the top collaborators of Kor de Jong 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 Kor de Jong. Kor de Jong is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Sutanudjaja, Edwin H., Rens van Beek, Niko Wanders, et al.. (2018). PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model. Geoscientific model development. 11(6). 2429–2453.384 indexed citations breakdown →
Sutanudjaja, Edwin H., Niels Drost, Rolf Hut, et al.. (2014). Assimilating data from remote sensing into a high-resolution global hydrological model. Research Repository (Delft University of Technology). 10714.1 indexed citations
Karssenberg, Derek, Oliver Schmitz, & Kor de Jong. (2012). Stochastic spatio-temporal modelling with PCRaster Python. Data Archiving and Networked Services (DANS).
10.
Lawrence, Deborah, L. Phil Graham, Johan Andréasson, et al.. (2012). Climate change impacts and uncertainties in flood risk management: Examples from the North Sea Region.6 indexed citations
11.
Jong, Kor de, et al.. (2009). G2 - The First Real-Time GPS and GLONASS Precise Orbit and Clock Service. 1885–1891.27 indexed citations
Karssenberg, Derek, et al.. (2008). A tool for construction of stochastic spatio-temporal models assimilated with observational data. Utrecht University Repository (Utrecht University).2 indexed citations
Karssenberg, Derek, Kor de Jong, & Johannes van der Kwast. (2007). Modelling landscape dynamics with Python. International Journal of Geographical Information Systems. 21(5). 483–495.46 indexed citations
16.
Karssenberg, Derek, et al.. (2006). Dynamic visualisation of spatial and spatio-temporal probability density functions. Utrecht University Repository (Utrecht University).1 indexed citations
17.
Karssenberg, Derek & Kor de Jong. (2006). Towards improved solution schemes for Monte Carlo simulation in environmental modeling languages. Utrecht University Repository (Utrecht University).4 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.