David Swayne

653 total citations
40 papers, 442 citations indexed

About

David Swayne is a scholar working on Water Science and Technology, Environmental Engineering and Ocean Engineering. According to data from OpenAlex, David Swayne has authored 40 papers receiving a total of 442 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Water Science and Technology, 13 papers in Environmental Engineering and 5 papers in Ocean Engineering. Recurrent topics in David Swayne's work include Hydrology and Watershed Management Studies (14 papers), Hydrological Forecasting Using AI (9 papers) and Groundwater flow and contamination studies (5 papers). David Swayne is often cited by papers focused on Hydrology and Watershed Management Studies (14 papers), Hydrological Forecasting Using AI (9 papers) and Groundwater flow and contamination studies (5 papers). David Swayne collaborates with scholars based in Canada, United States and Malaysia. David Swayne's co-authors include David Lam, Charlie Obimbo, Sarah Dorner, Qusay H. Mahmoud, William M. Schertzer, Luis F. De León, John D. Storey, D.C.C. Lam, C. I. Mayfield and Karen Hopkins and has published in prestigious journals such as Computer, Ecological Modelling and Journal of the Association for Information Systems.

In The Last Decade

David Swayne

39 papers receiving 399 citations

Peers

David Swayne
Comparison fields: 5 of 94
  • Water Science and Technology 125
  • Global and Planetary Change 106
  • Environmental Engineering 86
  • Ocean Engineering 58
  • Artificial Intelligence 54
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Citations per field, relative to David Swayne
David Swayne · 1×
Citations per year, relative to David Swayne
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Countries citing papers authored by David Swayne

Since Specialization
Citations

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

Fields of papers citing papers by David Swayne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Swayne

This figure shows the co-authorship network connecting the top 25 collaborators of David Swayne. A scholar is included among the top collaborators of David Swayne 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 David Swayne. David Swayne 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
# Work Indexed citations
1 80
2
A Novel Model Calibration Technique Through Application of Machine Learning Association Rules
1
3
Innovative Autocalibration Techniques Using High Performance Computing
1
4
The Land and Water Integration Decision Support System
3
5 15
6
A 3D Hydrodynamic Lake Model: Simulation on Great Slave Lake
2
7
Auto-Calibration of Hydrological Models Using High Performance Computing
6
8 16
9 18
10
Possible Courses: Multi-Objective Modelling and Decision Support Using a Bayesian Network Approximation to a Nonpoint Source Pollution Model
1
11 3
12 36
13 13
14 2
15 3
16 7
17 1
18 5
19 9
20 5

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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