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.
Automatic calibration of a conceptual rainfall–runoff model using multiple objectives
This map shows the geographic impact of Henrik Madsen'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 Henrik Madsen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Henrik Madsen more than expected).
This network shows the impact of papers produced by Henrik Madsen. 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 Henrik Madsen. The network helps show where Henrik Madsen may publish in the future.
Co-authorship network of co-authors of Henrik Madsen
This figure shows the co-authorship network connecting the top 25 collaborators of Henrik Madsen.
A scholar is included among the top collaborators of Henrik Madsen 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 Henrik Madsen. Henrik Madsen is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Schneider, Raphael, et al.. (2016). Assimilation of CryoSat-2 altimetry to a hydrodynamic model of the Brahmaputra river. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 18.1 indexed citations
Schneider, Raphael, et al.. (2015). Combining Envisat type and CryoSat-2 altimetry to inform hydrodynamic models. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 17. 9372.2 indexed citations
Velzen, Nils van, et al.. (2014). A flexible open data assimilation framework for hydrological modelling. EGU General Assembly Conference Abstracts. 16896.
Stoll, Sebastian, Harrie‐Jan Hendricks Franssen, Michael Butts, et al.. (2010). Prediction of long-term trends in groundwater levels of a perialpine groundwater system: comparing different climate models and different downscaling procedures. JuSER (Forschungszentrum Jülich). 10257.1 indexed citations
16.
Madsen, Henrik & Soon‐Thiam Khu. (2007). On the use of Pareto optimization for multi-criteria calibration of hydrological models. Tunnelling and Underground Space Technology. 16(3). 15–15.1 indexed citations
17.
Madsen, Henrik, et al.. (2006). Comparison of parameter estimation algorithms in hydrological modelling. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 67–72.2 indexed citations
18.
Madsen, Henrik, et al.. (2006). Simulation and optimisation modelling approach for operation of the Hoa Binh reservoir. European geosciences union general assembly. 8.8 indexed citations
19.
Madsen, Henrik, et al.. (2003). A new reduced rank square root Kalman filter technique for data assimilation in large scale modelling systems. EAEJA. 12800.1 indexed citations
20.
Madsen, Henrik, et al.. (2002). Uncertainty Estimation In Groundwater Modelling Using Kalman Filtering. EGS General Assembly Conference Abstracts. 1004.5 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.