A. Kauffeldt

532 total citations
9 papers, 380 citations indexed

About

A. Kauffeldt is a scholar working on Water Science and Technology, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, A. Kauffeldt has authored 9 papers receiving a total of 380 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Water Science and Technology, 8 papers in Global and Planetary Change and 4 papers in Environmental Engineering. Recurrent topics in A. Kauffeldt's work include Hydrology and Watershed Management Studies (9 papers), Flood Risk Assessment and Management (6 papers) and Hydrological Forecasting Using AI (4 papers). A. Kauffeldt is often cited by papers focused on Hydrology and Watershed Management Studies (9 papers), Flood Risk Assessment and Management (6 papers) and Hydrological Forecasting Using AI (4 papers). A. Kauffeldt collaborates with scholars based in Sweden, United Kingdom and Norway. A. Kauffeldt's co-authors include Fredrik Wetterhall, Florian Pappenberger, J. Thielen, Peter Salamon, Chong‐Yu Xu, Sven Halldin, Ida Westerberg, Allan Rodhe, Jan Seibert and Keith Beven and has published in prestigious journals such as Geophysical Research Letters, Journal of Hydrology and Hydrological Processes.

In The Last Decade

A. Kauffeldt

9 papers receiving 376 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
A. Kauffeldt Sweden	6	325	309	122	89	28	9	380
Hongren Shen Canada	8	302 0.9×	280 0.9×	131 1.1×	67 0.8×	13 0.5×	17	378
Tara Razavi Canada	7	432 1.3×	409 1.3×	212 1.7×	104 1.2×	55 2.0×	7	524
Elin Widén-Nilsson Sweden	6	342 1.1×	319 1.0×	78 0.6×	119 1.3×	13 0.5×	14	402
Marcus Buechel United Kingdom	7	251 0.8×	302 1.0×	144 1.2×	78 0.9×	37 1.3×	12	396
Bailey Anderson United Kingdom	6	253 0.8×	296 1.0×	144 1.2×	83 0.9×	21 0.8×	13	376
J. Götzinger Germany	9	307 0.9×	228 0.7×	142 1.2×	63 0.7×	20 0.7×	11	362
Tanja Euser Netherlands	4	409 1.3×	328 1.1×	196 1.6×	76 0.9×	40 1.4×	7	465
Fernando Pereira Belgium	6	267 0.8×	208 0.7×	105 0.9×	44 0.5×	21 0.8×	12	286
Jef Dams Belgium	6	256 0.8×	257 0.8×	197 1.6×	39 0.4×	40 1.4×	12	394
Eric Sprokkereef Netherlands	7	239 0.7×	246 0.8×	95 0.8×	94 1.1×	16 0.6×	14	310

Countries citing papers authored by A. Kauffeldt

Since Specialization

Citations

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

Fields of papers citing papers by A. Kauffeldt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. Kauffeldt. 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 A. Kauffeldt. The network helps show where A. Kauffeldt may publish in the future.

Co-authorship network of co-authors of A. Kauffeldt

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Reynolds, J. E., Sven Halldin, Chong‐Yu Xu, Jan Seibert, & A. Kauffeldt. (2017). Sub-daily runoff predictions using parameters calibrated on the basis of data with a daily temporal resolution. Journal of Hydrology. 550. 399–411. 28 indexed citations

2.

Beven, Keith, et al.. (2016). Event and model dependent rainfall adjustments to improve discharge predictions. Hydrological Sciences Journal. 62(2). 232–245. 10 indexed citations

3.

Reynolds, J. E., Sven Halldin, Chong‐Yu Xu, Jan Seibert, & A. Kauffeldt. (2015). Sub-daily runoff simulations with parameters inferred at the daily time scale. 3 indexed citations

4.

Kauffeldt, A., Fredrik Wetterhall, Florian Pappenberger, Peter Salamon, & J. Thielen. (2015). Technical review of large-scale hydrological models for implementation in operational flood forecasting schemes on continental level. Environmental Modelling & Software. 75. 68–76. 190 indexed citations

5.

Kauffeldt, A., Sven Halldin, Florian Pappenberger, et al.. (2015). Imbalanced land surface water budgets in a numerical weather prediction system. Geophysical Research Letters. 42(11). 4411–4417. 10 indexed citations

6.

Kauffeldt, A.. (2014). Disinformative and Uncertain Data in Global Hydrology : Challenges for Modelling and Regionalisation. KTH Publication Database DiVA (KTH Royal Institute of Technology). 2 indexed citations

7.

Kauffeldt, A., Sven Halldin, Allan Rodhe, Chong‐Yu Xu, & Ida Westerberg. (2013). Disinformative data in large-scale hydrological modelling. Hydrology and earth system sciences. 17(7). 2845–2857. 87 indexed citations

8.

Kauffeldt, A., Sven Halldin, Allan Rodhe, Chong‐Yu Xu, & Ida Westerberg. (2013). Disinformative data in large-scale hydrological modelling. 1 indexed citations

9.

Juston, John, et al.. (2012). Smiling in the rain: Seven reasons to be positive about uncertainty in hydrological modelling. Hydrological Processes. 27(7). 1117–1122. 49 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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