Jonathan Frame

1.9k total citations · 2 hit papers
22 papers, 790 citations indexed

About

Jonathan Frame is a scholar working on Environmental Engineering, Water Science and Technology and Global and Planetary Change. According to data from OpenAlex, Jonathan Frame has authored 22 papers receiving a total of 790 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Environmental Engineering, 17 papers in Water Science and Technology and 13 papers in Global and Planetary Change. Recurrent topics in Jonathan Frame's work include Hydrology and Watershed Management Studies (17 papers), Hydrological Forecasting Using AI (15 papers) and Flood Risk Assessment and Management (12 papers). Jonathan Frame is often cited by papers focused on Hydrology and Watershed Management Studies (17 papers), Hydrological Forecasting Using AI (15 papers) and Flood Risk Assessment and Management (12 papers). Jonathan Frame collaborates with scholars based in United States, Austria and China. Jonathan Frame's co-authors include Grey Nearing, Frederik Kratzert, Hoshin V. Gupta, Daniel Klotz, Alden Keefe Sampson, Craig Pelissier, Cristina Prieto, Martin Gauch, Oren Gilon and Guy Shalev and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Water Resources Research.

In The Last Decade

Jonathan Frame

19 papers receiving 773 citations

Hit Papers

What Role Does Hydrological Science Play in the Age of Ma... 2020 2026 2022 2024 2020 2022 100 200 300
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. What Role Does Hydrological Science Play in the Age of Machine Learning?
    2020 391 citations Grey Nearing, Frederik Kratzert et al. Water Resources Research profile →
  2. Deep learning rainfall–runoff predictions of extreme events
    2022 156 citations Jonathan Frame, Frederik Kratzert et al. Hydrology and earth system sciences profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan Frame United States 8 591 577 469 120 46 22 790
Alden Keefe Sampson United States 7 814 1.4× 766 1.3× 658 1.4× 152 1.3× 59 1.3× 10 1.0k
Cristina Prieto Spain 10 656 1.1× 494 0.9× 550 1.2× 108 0.9× 54 1.2× 23 819
Martin Gauch United States 13 771 1.3× 718 1.2× 650 1.4× 187 1.6× 24 0.5× 25 1.0k
Kuai Fang United States 8 406 0.7× 464 0.8× 307 0.7× 134 1.1× 27 0.6× 17 653
Marie‐Amélie Boucher Canada 18 598 1.0× 459 0.8× 465 1.0× 275 2.3× 100 2.2× 44 899
Guy Shalev United States 8 372 0.6× 348 0.6× 345 0.7× 133 1.1× 24 0.5× 11 577
Kabir Rasouli Canada 14 426 0.7× 263 0.5× 361 0.8× 317 2.6× 37 0.8× 29 771
D. Nalley Canada 8 292 0.5× 320 0.6× 523 1.1× 206 1.7× 22 0.5× 13 760
D. L. Blodgett United States 11 497 0.8× 252 0.4× 399 0.9× 119 1.0× 41 0.9× 17 621
Edward P. Campbell Australia 10 330 0.6× 213 0.4× 424 0.9× 141 1.2× 72 1.6× 14 640

Countries citing papers authored by Jonathan Frame

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Frame

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan Frame

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Frame. A scholar is included among the top collaborators of Jonathan Frame 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 Jonathan Frame. Jonathan Frame 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.
2.
Frame, Jonathan, et al.. (2025). Machine Learning for a Heterogeneous Water Modeling Framework. JAWRA Journal of the American Water Resources Association. 61(1). 5 indexed citations
3.
Frame, Jonathan, et al.. (2024). Rapid Inundation Mapping Using the US National Water Model, Satellite Observations, and a Convolutional Neural Network. Geophysical Research Letters. 51(17). 4 indexed citations
4.
Frame, Jonathan, Frederik Kratzert, Hoshin V. Gupta, Paul Ullrich, & Grey Nearing. (2023). On strictly enforced mass conservation constraints for modelling the Rainfall‐Runoff process. Hydrological Processes. 37(3). 32 indexed citations
5.
Frame, Jonathan, et al.. (2023). Long short-term memory models to quantify long-term evolution of streamflow discharge and groundwater depth in Alabama. The Science of The Total Environment. 901. 165884–165884. 19 indexed citations
6.
Frame, Jonathan, Frederik Kratzert, Daniel Klotz, et al.. (2022). Deep learning rainfall–runoff predictions of extreme events. Hydrology and earth system sciences. 26(13). 3377–3392. 156 indexed citations breakdown →
7.
Nearing, Grey, Daniel Klotz, Jonathan Frame, et al.. (2022). Technical note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks. Hydrology and earth system sciences. 26(21). 5493–5513. 26 indexed citations
8.
Frame, Jonathan, et al.. (2022). Hydrology research articles are becoming more topically diverse. Journal of Hydrology. 614. 128551–128551. 7 indexed citations
9.
Wei, Song, Yi Zheng, Xiuyu Liang, et al.. (2022). A distributed domain model coupling open channel flow and groundwater flow to quantify the impact of lateral hydrologic exchange on hydrograph. Journal of Hydrology. 611. 128010–128010. 3 indexed citations
10.
11.
Frame, Jonathan, Frederik Kratzert, Daniel Klotz, et al.. (2021). Deep learning rainfall-runoff predictions of extreme events. 17 indexed citations
12.
13.
Brenner, Claire, Jonathan Frame, Grey Nearing, & Karsten Schulz. (2021). Schätzung der Verdunstung mithilfe von Machine- und Deep Learning-Methoden. Österreichische Wasser- und Abfallwirtschaft. 73(7-8). 295–307. 2 indexed citations
14.
Frame, Jonathan, et al.. (2020). Improving U.S. National Water Model Streamflow with Long Short-Term Memory Networks. 1 indexed citations
15.
Nearing, Grey, Frederik Kratzert, Craig Pelissier, et al.. (2020). Machine Learning is Central to the Future of Hydrological Modeling. 3 indexed citations
16.
Nearing, Grey, Frederik Kratzert, Alden Keefe Sampson, et al.. (2020). What Role Does Hydrological Science Play in the Age of Machine Learning?. Water Resources Research. 57(3). 391 indexed citations breakdown →
17.
Nearing, Grey, Craig Pelissier, Frederik Kratzert, et al.. (2019). Physically Informed Machine Learning for Hydrological Modeling Under Climate Nonstationarity. Maryland Shared Open Access Repository (USMAI Consortium). 5 indexed citations
18.
Peeters, Alain & Jonathan Frame. (2002). Quality and promotion of animal products in mountain.. DIAL (Catholic University of Leuven). 2 indexed citations
19.
Frame, Jonathan, et al.. (2000). XML for Immediate Discharge Letters in Scotland. Studies in health technology and informatics. 77. 1040–4. 5 indexed citations
20.
Frame, Jonathan, et al.. (1956). BATCH VERSUS CONTINUOUS PROCESSING. Chemical engineering progress.

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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