Andrew Binns

958 total citations
55 papers, 683 citations indexed

About

Andrew Binns is a scholar working on Water Science and Technology, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Andrew Binns has authored 55 papers receiving a total of 683 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Water Science and Technology, 21 papers in Global and Planetary Change and 20 papers in Environmental Engineering. Recurrent topics in Andrew Binns's work include Hydrology and Watershed Management Studies (30 papers), Hydrology and Sediment Transport Processes (18 papers) and Flood Risk Assessment and Management (16 papers). Andrew Binns is often cited by papers focused on Hydrology and Watershed Management Studies (30 papers), Hydrology and Sediment Transport Processes (18 papers) and Flood Risk Assessment and Management (16 papers). Andrew Binns collaborates with scholars based in Canada, Iran and United Kingdom. Andrew Binns's co-authors include Bahram Gharabaghi, Hossein Bonakdari, Jana Levison, Isa Ebtehaj, Pradeep Goel, Ana Maria Ferreira da Silva, Edward A. McBean, Ashutosh Singh, Amir Hossein Zaji and Jan Adamowski and has published in prestigious journals such as The Science of The Total Environment, Journal of Hydrology and Journal of Environmental Management.

In The Last Decade

Andrew Binns

50 papers receiving 664 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew Binns Canada 16 316 264 222 168 129 55 683
Oliver Saavedra Japan 16 371 1.2× 286 1.1× 200 0.9× 115 0.7× 52 0.4× 71 749
Danrong Zhang China 17 392 1.2× 395 1.5× 245 1.1× 111 0.7× 104 0.8× 42 746
Ebru Eriş Türkiye 16 381 1.2× 387 1.5× 154 0.7× 142 0.8× 186 1.4× 33 755
Kim Vercruysse United Kingdom 12 309 1.0× 289 1.1× 180 0.8× 289 1.7× 246 1.9× 16 705
Conrad Jackisch Germany 15 390 1.2× 290 1.1× 282 1.3× 81 0.5× 90 0.7× 36 665
B. Venkatesh India 13 415 1.3× 420 1.6× 283 1.3× 82 0.5× 184 1.4× 29 773
Ali Ameli Canada 16 532 1.7× 314 1.2× 307 1.4× 209 1.2× 88 0.7× 35 857
Hui Peng China 18 523 1.7× 436 1.7× 321 1.4× 73 0.4× 76 0.6× 39 901

Countries citing papers authored by Andrew Binns

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Binns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Binns

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Binns. A scholar is included among the top collaborators of Andrew Binns 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 Andrew Binns. Andrew Binns 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.
Binns, Andrew, et al.. (2025). Decomposing streamflow for improved river flow prediction accuracy of machine learning models. International Journal of River Basin Management. 1–16.
2.
3.
Levison, Jana, et al.. (2024). Machine learning models for prediction of nutrient concentrations in surface water in an agricultural watershed. Journal of Environmental Management. 372. 123305–123305. 10 indexed citations
4.
Levison, Jana, et al.. (2024). Subsurface influences on watershed nutrient concentrations and loading in a clay dominated agricultural system. Journal of Hydrology. 645. 132140–132140. 10 indexed citations
5.
Binns, Andrew, et al.. (2024). Characterizing Flow Patterns and Velocities in a Backwater Valve Using Fluorescent Particle Tracers for Image Velocimetry. Journal of Hydraulic Engineering. 150(6). 1 indexed citations
6.
Binns, Andrew, et al.. (2024). Findings from a National Survey of Canadian perspectives on predicting river channel migration and river bank erosion. River Research and Applications. 40(10). 1787–1800. 2 indexed citations
7.
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Levison, Jana, et al.. (2023). Application of classification machine learning algorithms for characterizing nutrient transport in a clay plain agricultural watershed. Journal of Environmental Management. 345. 118924–118924. 17 indexed citations
9.
McBean, Edward A., et al.. (2023). Understanding changes in the timing of heavy storms: a regional case study of climate change impacts. Climatic Change. 176(12). 2 indexed citations
10.
Binns, Andrew. (2023). Preparing for severe flooding: Flood risk management research leading to better flood preparedness. Journal of Flood Risk Management. 16(3).
11.
Levison, Jana, et al.. (2023). Text mining-aided meta-research on nutrient dynamics in surface water and groundwater: Popular topics and perceived gaps. Journal of Hydrology. 626. 130338–130338. 9 indexed citations
12.
13.
Binns, Andrew, et al.. (2021). Early detection of riverine flooding events using the group method of data handling for the Bow River, Alberta, Canada. International Journal of River Basin Management. 20(4). 533–544. 20 indexed citations
14.
Douglas‐Mankin, Kyle R., Swapan Kumar Roy, Aleksey Y. Sheshukov, et al.. (2020). A comprehensive review of ephemeral gully erosion models. CATENA. 195. 104901–104901. 34 indexed citations
15.
Binns, Andrew, et al.. (2020). Improved Streamflow Forecasting Using Variational Mode Decomposition and Extreme Gradient Boosting. AGU Fall Meeting Abstracts. 2020. 1 indexed citations
16.
Binns, Andrew, et al.. (2020). Urban flood susceptibility mapping using supervised regression and machine learning models in Toronto, Canada. AGU Fall Meeting Abstracts. 2020. 1 indexed citations
17.
Levison, Jana, et al.. (2020). Spatiotemporal variations of nitrogen and phosphorus in a clay plain hydrological system in the Great Lakes Basin. The Science of The Total Environment. 714. 136328–136328. 37 indexed citations
18.
Binns, Andrew, et al.. (2019). Estimating 2-year flood flows using the generalized structure of the Group Method of Data Handling. Journal of Hydrology. 575. 671–689. 53 indexed citations
19.
McBean, Edward A., et al.. (2019). Quantifying Rainfall-Derived Inflow from Private Foundation Drains in Sanitary Sewers: Case Study in London, Ontario, Canada. Journal of Hydrologic Engineering. 24(9). 14 indexed citations
20.
Binns, Andrew, et al.. (2008). The properties of Lias Clay for landfill liners. Proceedings of the Institution of Civil Engineers - Geotechnical Engineering. 161(4). 197–207. 1 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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