Jim Freer

25.1k total citations · 6 hit papers
187 papers, 16.0k citations indexed

About

Jim Freer is a scholar working on Water Science and Technology, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Jim Freer has authored 187 papers receiving a total of 16.0k indexed citations (citations by other indexed papers that have themselves been cited), including 143 papers in Water Science and Technology, 93 papers in Global and Planetary Change and 46 papers in Environmental Engineering. Recurrent topics in Jim Freer's work include Hydrology and Watershed Management Studies (139 papers), Flood Risk Assessment and Management (73 papers) and Hydrology and Drought Analysis (37 papers). Jim Freer is often cited by papers focused on Hydrology and Watershed Management Studies (139 papers), Flood Risk Assessment and Management (73 papers) and Hydrology and Drought Analysis (37 papers). Jim Freer collaborates with scholars based in United Kingdom, United States and Canada. Jim Freer's co-authors include Keith Beven, Ross Woods, Wouter Knoben, Thorsten Wagener, Bruno Ambroise, Paul Bates, Penny J Johnes, K. Beven, Charlotte Lloyd and Hilary McMillan and has published in prestigious journals such as Nature Communications, Journal of Geophysical Research Atmospheres and PLoS ONE.

In The Last Decade

Jim Freer

184 papers receiving 15.5k citations

Hit Papers

Equifinality, data assimilation, and uncertainty estimati... 1996 2026 2006 2016 2001 2016 2019 1996 2013 500 1000 1.5k
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. Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology
    2001 1.7k citations Keith Beven, Jim Freer profile →
  2. Sensitivity analysis of environmental models: A systematic review with practical workflow
    2016 1.1k citations Francesca Pianosi, Keith Beven et al. profile →
  3. Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores
    2019 864 citations Wouter Knoben, Jim Freer et al. Hydrology and earth system sciences profile →
  4. Bayesian Estimation of Uncertainty in Runoff Prediction and the Value of Data: An Application of the GLUE Approach
    1996 633 citations Jim Freer, K. Beven et al. Water Resources Research profile →
  5. Geophysical Research Abstracts
    2013 506 citations Charlotte Lloyd, Jim Freer et al. profile →
  6. A high-resolution global flood hazard model
    2015 408 citations Christopher Sampson, Paul Bates et al. Water Resources Research profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jim Freer United Kingdom 66 11.2k 8.6k 4.8k 2.8k 2.0k 187 16.0k
Daniel N. Moriasi United States 28 11.6k 1.0× 7.5k 0.9× 4.6k 0.9× 1.9k 0.7× 1.6k 0.8× 115 14.9k
Jan Seibert Sweden 74 13.2k 1.2× 10.1k 1.2× 4.3k 0.9× 5.0k 1.8× 3.0k 1.5× 298 18.6k
Thorsten Wagener United Kingdom 75 13.6k 1.2× 11.2k 1.3× 6.9k 1.4× 2.8k 1.0× 1.5k 0.7× 264 20.1k
Karim C. Abbaspour Switzerland 57 13.1k 1.2× 8.5k 1.0× 5.3k 1.1× 1.7k 0.6× 1.2k 0.6× 178 17.4k
R. Daren Harmel United States 39 12.4k 1.1× 7.4k 0.9× 4.9k 1.0× 1.8k 0.7× 1.9k 0.9× 139 16.8k
M. W. Van Liew United States 12 10.6k 0.9× 7.0k 0.8× 4.0k 0.8× 1.7k 0.6× 1.5k 0.7× 17 13.5k
Anthony J. Jakeman Australia 61 8.5k 0.8× 7.4k 0.9× 4.4k 0.9× 1.4k 0.5× 2.0k 1.0× 319 16.7k
H. H. G. Savenije Netherlands 79 10.2k 0.9× 9.2k 1.1× 4.5k 0.9× 3.6k 1.3× 2.5k 1.3× 344 18.2k
Jun Xia China 62 7.9k 0.7× 8.8k 1.0× 3.8k 0.8× 2.6k 1.0× 1.5k 0.7× 528 15.2k
J. V. Sutcliffe United Kingdom 20 13.9k 1.2× 10.6k 1.2× 6.1k 1.3× 3.5k 1.3× 2.7k 1.3× 42 20.0k

Countries citing papers authored by Jim Freer

Since Specialization
Citations

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

Fields of papers citing papers by Jim Freer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jim Freer

This figure shows the co-authorship network connecting the top 25 collaborators of Jim Freer. A scholar is included among the top collaborators of Jim Freer 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 Jim Freer. Jim Freer 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.
Coxon, Gemma, Francesca Pianosi, Rosanna Lane, et al.. (2024). Developing water supply reservoir operating rules for large-scale hydrological modelling. Hydrology and earth system sciences. 28(17). 4203–4218. 2 indexed citations
2.
Tang, Guoqiang, Martyn Clark, Wouter Knoben, et al.. (2024). Uncertainty Hotspots in Global Hydrologic Modeling: The Impact of Precipitation and Temperature Forcings. Bulletin of the American Meteorological Society. 106(1). E146–E166. 3 indexed citations
3.
Smith, Paul J., Keith Beven, Francesca Pianosi, et al.. (2023). Technical note: The CREDIBLE Uncertainty Estimation (CURE) toolbox: facilitating the communication of epistemic uncertainty. Hydrology and earth system sciences. 27(13). 2523–2534. 5 indexed citations
4.
Freer, Jim, et al.. (2023). Evidence-based requirements for perceptualising intercatchment groundwater flow in hydrological models. Hydrology and earth system sciences. 27(3). 761–781. 9 indexed citations
5.
Shannon, Sarah, A. J. Payne, Jim Freer, et al.. (2023). A snow and glacier hydrological model for large catchments – case study for the Naryn River, central Asia. Hydrology and earth system sciences. 27(2). 453–480. 9 indexed citations
6.
Lane, Rosanna, Gemma Coxon, Jim Freer, Jan Seibert, & Thorsten Wagener. (2022). A large-sample investigation into uncertain climate change impacts on high flows across Great Britain. Hydrology and earth system sciences. 26(21). 5535–5554. 14 indexed citations
7.
Lane, Rosanna, Jim Freer, Gemma Coxon, & Thorsten Wagener. (2021). Incorporating Uncertainty Into Multiscale Parameter Regionalization to Evaluate the Performance of Nationally Consistent Parameter Fields for a Hydrological Model. Water Resources Research. 57(10). 16 indexed citations
8.
Byers, Edward, Gemma Coxon, Jim Freer, & Jim W. Hall. (2020). Drought and climate change impacts on cooling water shortages and electricity prices in Great Britain. Nature Communications. 11(1). 2239–2239. 77 indexed citations
9.
Coxon, Gemma, Nans Addor, John P. Bloomfield, et al.. (2020). CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain. Earth system science data. 12(4). 2459–2483. 146 indexed citations
10.
Beven, Keith, Paul Bates, Eleanor Blyth, et al.. (2019). Developing observational methods to drive future hydrological science: Can we make a start as a community?. Hydrological Processes. 34(3). 868–873. 42 indexed citations
11.
Zischg, Andreas Paul, Rolf Weingartner, Niall Quinn, et al.. (2018). Effects of variability in probable maximum precipitation patterns on flood losses. Hydrology and earth system sciences. 22(5). 2759–2773. 35 indexed citations
12.
Zischg, Andreas Paul, Rolf Weingartner, Niall Quinn, et al.. (2018). Effects of variability in probable maximum precipitation patterns on flood losses. 2 indexed citations
13.
Kiang, Julie E., Hilary McMillan, Gemma Coxon, et al.. (2018). A Comparison of Methods for Streamflow Uncertainty Estimation. Water Resources Research. 54(10). 7149–7176. 130 indexed citations
14.
15.
Nijzink, Remko C., Christopher Hutton, Ilias Pechlivanidis, et al.. (2016). The evolution of root zone moisture capacities after land use change: a step towards predictions under change?.
16.
Nijzink, Remko C., Christopher Hutton, Ilias Pechlivanidis, et al.. (2016). The evolution of root-zone moisture capacities after deforestation: a step towards hydrological predictions under change?. Hydrology and earth system sciences. 20(12). 4775–4799. 70 indexed citations
17.
Coxon, Gemma, et al.. (2016). A percentile approach to evaluate simulated groundwater levels andfrequencies in a Chalk catchment in Southwest England. Bristol Research (University of Bristol). 1 indexed citations
18.
Sampson, Christopher, Timothy Fewtrell, Fiachra O’Loughlin, et al.. (2014). The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model. Hydrology and earth system sciences. 18(6). 2305–2324. 51 indexed citations
19.
Lloyd, Charlotte, Jim Freer, Penny J Johnes, & Alan R. Collins. (2013). Assessing the effects of sampling design on water quality status classification. Bristol Research (University of Bristol). 13032. 1 indexed citations
20.
Wagener, Thorsten, Jim Freer, Erwin Zehe, et al.. (2006). Predictions in Ungauged Basins: Promise and Progress. IAHS-AISH publication. 25 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Daniel N. Moriasi Breakdown of academic impact, for papers by Jan Seibert Breakdown of academic impact, for papers by Thorsten Wagener Breakdown of academic impact, for papers by Karim C. Abbaspour Breakdown of academic impact, for papers by R. Daren Harmel Breakdown of academic impact, for papers by M. W. Van Liew Breakdown of academic impact, for papers by Anthony J. Jakeman Breakdown of academic impact, for papers by H. H. G. Savenije Breakdown of academic impact, for papers by Jun Xia Breakdown of academic impact, for papers by J. V. Sutcliffe
Rankless by CCL
2026