Stephen Nash

3.8k total citations · 5 hit papers
71 papers, 2.7k citations indexed

About

Stephen Nash is a scholar working on Oceanography, Water Science and Technology and Atmospheric Science. According to data from OpenAlex, Stephen Nash has authored 71 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Oceanography, 21 papers in Water Science and Technology and 19 papers in Atmospheric Science. Recurrent topics in Stephen Nash's work include Tropical and Extratropical Cyclones Research (16 papers), Water Quality and Pollution Assessment (14 papers) and Wind Energy Research and Development (13 papers). Stephen Nash is often cited by papers focused on Tropical and Extratropical Cyclones Research (16 papers), Water Quality and Pollution Assessment (14 papers) and Wind Energy Research and Development (13 papers). Stephen Nash collaborates with scholars based in Ireland, Australia and United Kingdom. Stephen Nash's co-authors include Agnieszka I. Olbert, Md Galal Uddin, Azizur Rahman, Michael Hartnett, Mir Talas Mahammad Diganta, Jamie Goggins, Tomasz Dabrowski, Fearghal O’Donncha, Lei Ren and S.B. Leen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and The Science of The Total Environment.

In The Last Decade

Stephen Nash

67 papers receiving 2.7k citations

Hit Papers

A review of water quality index models and their use for ... 2020 2026 2022 2024 2020 2022 2022 2022 2022 200 400 600
What are hit papers?

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.

  1. A review of water quality index models and their use for assessing surface water quality
    2020 736 citations Md Galal Uddin, Stephen Nash et al. profile →
  2. A comprehensive method for improvement of water quality index (WQI) models for coastal water quality assessment
    2022 246 citations Md Galal Uddin, Stephen Nash et al. Water Research profile →
  3. Performance analysis of the water quality index model for predicting water state using machine learning techniques
    2022 175 citations Md Galal Uddin, Stephen Nash et al. profile →
  4. A novel approach for estimating and predicting uncertainty in water quality index model using machine learning approaches
    2022 152 citations Md Galal Uddin, Stephen Nash et al. Water Research profile →
  5. Robust machine learning algorithms for predicting coastal water quality index
    2022 150 citations Md Galal Uddin, Stephen Nash et al. Journal of Environmental Management profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen Nash Ireland 25 1.6k 1.1k 393 380 374 71 2.7k
Agnieszka I. Olbert Ireland 26 1.8k 1.1× 1.2k 1.1× 443 1.1× 430 1.1× 245 0.7× 65 2.8k
Wen‐Cheng Liu Taiwan 33 1.1k 0.7× 789 0.7× 860 2.2× 128 0.3× 1.1k 2.9× 150 3.1k
Roberto Revelli Italy 30 1.4k 0.9× 1.3k 1.2× 266 0.7× 109 0.3× 72 0.2× 90 3.1k
Ahmed Sefelnasr United Arab Emirates 29 653 0.4× 1.1k 1.0× 421 1.1× 80 0.2× 127 0.3× 79 2.0k
Rahim Barzegar Iran 32 1.5k 1.0× 1.9k 1.7× 570 1.5× 209 0.6× 73 0.2× 75 3.1k
Hongwu Tang China 28 925 0.6× 410 0.4× 364 0.9× 62 0.2× 158 0.4× 180 2.7k
Jian Peng China 33 954 0.6× 1.4k 1.4× 1.6k 4.0× 168 0.4× 200 0.5× 157 3.9k
Subbarayan Saravanan India 24 925 0.6× 900 0.8× 950 2.4× 79 0.2× 45 0.1× 91 2.1k
Xing Fang United States 34 1.4k 0.9× 1.1k 1.0× 977 2.5× 108 0.3× 643 1.7× 209 3.9k
Asghar Asghari Moghaddam Iran 34 1.4k 0.9× 1.9k 1.8× 377 1.0× 194 0.5× 47 0.1× 75 3.1k

Countries citing papers authored by Stephen Nash

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Nash

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen Nash

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Nash. A scholar is included among the top collaborators of Stephen Nash 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 Stephen Nash. Stephen Nash 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.
Farrell, Eugene J., et al.. (2025). Measurement and Modelling of Beach Response to Storm Waves: A Case Study of Brandon Bay, Ireland. SHILAP Revista de lepidopterología. 5(3). 32–32.
2.
Nash, Stephen, et al.. (2024). Weather window analysis for the deployment, operation, and maintenance of marine renewable energy devices in Irish coastal waters. Journal of Ocean Engineering and Marine Energy. 10(4). 711–729. 1 indexed citations
3.
Uddin, Md Galal, Stephen Nash, Azizur Rahman, Tomasz Dabrowski, & Agnieszka I. Olbert. (2023). Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches. Environmental Research. 242. 117755–117755. 41 indexed citations
4.
Uddin, Md Galal, Stephen Nash, Azizur Rahman, & Agnieszka I. Olbert. (2023). A sophisticated model for rating water quality. The Science of The Total Environment. 868. 161614–161614. 77 indexed citations
5.
Uddin, Md Galal, Mir Talas Mahammad Diganta, Abdul Majed Sajib, et al.. (2023). Assessing the impact of COVID-19 lockdown on surface water quality in Ireland using advanced Irish water quality index (IEWQI) model. Environmental Pollution. 336. 122456–122456. 43 indexed citations
6.
Uddin, Md Galal, et al.. (2023). Comparison between the WFD approaches and newly developed water quality model for monitoring transitional and coastal water quality in Northern Ireland. The Science of The Total Environment. 901. 165960–165960. 43 indexed citations
7.
Uddin, Md Galal, Azizur Rahman, Stephen Nash, et al.. (2023). Marine waters assessment using improved water quality model incorporating machine learning approaches. Journal of Environmental Management. 344. 118368–118368. 57 indexed citations
8.
Uddin, Md Galal, Stephen Nash, Azizur Rahman, & Agnieszka I. Olbert. (2022). Assessing optimization techniques for improving water quality model. Journal of Cleaner Production. 385. 135671–135671. 106 indexed citations
9.
Uddin, Md Galal, Stephen Nash, Azizur Rahman, & Agnieszka I. Olbert. (2022). A novel approach for estimating and predicting uncertainty in water quality index model using machine learning approaches. Water Research. 229. 119422–119422. 152 indexed citations breakdown →
10.
Uddin, Md Galal, Stephen Nash, Mir Talas Mahammad Diganta, Azizur Rahman, & Agnieszka I. Olbert. (2022). Robust machine learning algorithms for predicting coastal water quality index. Journal of Environmental Management. 321. 115923–115923. 150 indexed citations breakdown →
11.
Uddin, Md Galal, Stephen Nash, Azizur Rahman, & Agnieszka I. Olbert. (2022). A comprehensive method for improvement of water quality index (WQI) models for coastal water quality assessment. Water Research. 219. 118532–118532. 246 indexed citations breakdown →
12.
Nash, Stephen, et al.. (2020). Application of the IEC Technical Specification for Assessment of Wave Energy Resource: A Case Study from the West Coast of Ireland. 2 indexed citations
13.
Nash, Stephen, et al.. (2019). Hydrodynamic modelling approaches to assess mechanisms affecting the structural performance and maintenance of vortex drops shaft structures. Journal of Structural Integrity and Maintenance. 4(3). 162–178. 6 indexed citations
14.
Nash, Stephen, et al.. (2018). High Resolution Urban Flood Modelling: A Case Study of Cork City, Ireland. EPiC series in engineering. 3. 1495–1484. 1 indexed citations
15.
Olbert, Agnieszka I., et al.. (2017). Development of high-resolution multi-scale modelling system for simulation of coastal-fluvial urban flooding. Natural hazards and earth system sciences. 17(2). 205–224. 15 indexed citations
16.
Hartnett, Michael & Stephen Nash. (2017). High-resolution flood modeling of urban areas using MSN_Flood. Water Science and Engineering. 10(3). 175–183. 28 indexed citations
17.
Ren, Lei, et al.. (2015). Estimation of the High Resolution Wind Field at Galway Bay. Journal of Clean Energy Technologies. 4(5). 353–356.
18.
Nash, Stephen & Michael Hartnett. (2005). Nutrient dynamics in Cork Harbour. WIT Transactions on Ecology and the Environment. 83. 1 indexed citations
19.
Brown, Cameron L., Amanda Berry, J. B. Curtis, et al.. (2004). Feasibility Study on the Establishment of a Large Scale Inshore Resource Mapping Project. Marine Institute Open Access Repository (Marine Institute). 1 indexed citations
20.
Hartnett, Michael, et al.. (1970). The Prediction Of Far-field PollutantConcentrations Using Residual Currents. WIT Transactions on Ecology and the Environment. 29. 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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