Robert J. Abrahart
- Environmental Engineering top 0.2%
- Water Science and Technology top 0.5%
- Global and Planetary Change top 1%
- Electrical and Electronic Engineering top 10%
- Artificial Intelligence top 5%
- Co-authors
- Linda SeeChristian W. DawsonRobert L. WilbyAsaad Y. ShamseldinNick J. MountPauline E. KnealeDimitri SolomatineElena Toth
- Topics
- Hydrological Forecasting Using AI (52 papers)Hydrology and Watershed Management Studies (48 papers)Flood Risk Assessment and Management (18 papers)
- Partner nations
- United KingdomNew ZealandNetherlands
In The Last Decade
Robert J. Abrahart
60 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 96
- Environmental Engineering 1.8k
- Water Science and Technology 1.7k
- Global and Planetary Change 1.3k
- Electrical and Electronic Engineering 315
- Artificial Intelligence 224
Countries citing papers authored by Robert J. Abrahart
This map shows the geographic impact of Robert J. Abrahart'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 Robert J. Abrahart with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert J. Abrahart more than expected).
Fields of papers citing papers by Robert J. Abrahart
This network shows the impact of papers produced by Robert J. Abrahart. 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 Robert J. Abrahart. The network helps show where Robert J. Abrahart may publish in the future.
Co-authorship network of co-authors of Robert J. Abrahart
This figure shows the co-authorship network connecting the top 25 collaborators of Robert J. Abrahart. A scholar is included among the top collaborators of Robert J. Abrahart 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 Robert J. Abrahart. Robert J. Abrahart is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 49 | |
| 2 | 82 | |
| 3 | 14 | |
| 4 | How much complexity is warranted in a rainfall-runoff model? Findings obtained from symbolic regression, using Eureqa | 3 |
| 5 | 14 | |
| 6 | 6 | |
| 7 | 8 | |
| 8 | Neural network modelling trade-offs: small might be beautiful but perhaps bigger is better? | 1 |
| 9 | Multi-model forecasting: Using gene expression programming to develop explicit equations for rainfall-runoff modelling combinations | 1 |
| 10 | 21 | |
| 11 | 30 | |
| 12 | 2 | |
| 13 | 81 | |
| 14 | 40 | |
| 15 | Neural Network Hydrological Modelling: Linear Output Activation Functions? | 1 |
| 16 | Using JavaSANE to Evolve Neural Network Rainfall-Runoff Models. | 1 |
| 17 | 44 | |
| 18 | 169 | |
| 19 | 105 | |
| 20 | 70 |
About Robert J. Abrahart
Robert J. Abrahart is a scholar working on Environmental Engineering, Water Science and Technology and Global and Planetary Change, having authored 60 papers that have together received 2.5k indexed citations. Recurring topics across this work include Hydrological Forecasting Using AI (52 papers), Hydrology and Watershed Management Studies (48 papers) and Flood Risk Assessment and Management (18 papers). The work is most often cited by research in Environmental Engineering (1.8k citations), Water Science and Technology (1.7k citations) and Global and Planetary Change (1.3k citations). Robert J. Abrahart has collaborated with scholars based in United Kingdom, New Zealand and Netherlands. Frequent co-authors include Linda See, Christian W. Dawson, Robert L. Wilby, Asaad Y. Shamseldin, Nick J. Mount, Pauline E. Kneale, Dimitri Solomatine, Elena Toth, S. M. White and Alison Heppenstall. Their work appears in journals such as Journal of Hydrology, Geomorphology and Neural Networks.
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.