J. R. Arnold

6.0k total citations · 1 hit paper
80 papers, 3.7k citations indexed

About

J. R. Arnold is a scholar working on Global and Planetary Change, Atmospheric Science and Water Science and Technology. According to data from OpenAlex, J. R. Arnold has authored 80 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Global and Planetary Change, 42 papers in Atmospheric Science and 39 papers in Water Science and Technology. Recurrent topics in J. R. Arnold's work include Hydrology and Watershed Management Studies (39 papers), Climate variability and models (28 papers) and Flood Risk Assessment and Management (18 papers). J. R. Arnold is often cited by papers focused on Hydrology and Watershed Management Studies (39 papers), Climate variability and models (28 papers) and Flood Risk Assessment and Management (18 papers). J. R. Arnold collaborates with scholars based in United States, Canada and United Kingdom. J. R. Arnold's co-authors include Martyn Clark, L. D. Brekke, Raghavan Srinivasan, E. D. Gutmann, Andrew W. Wood, Andrew J. Newman, Roy Rasmussen, Bart Nijssen, Naoki Mizukami and Lauren E. Hay and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and PLoS ONE.

In The Last Decade

J. R. Arnold

80 papers receiving 3.6k citations

Hit Papers

Development of a large-sample watershed-scale hydrometeor... 2015 2026 2018 2022 2015 100 200 300 400

Peers

J. R. Arnold
David E. Rupp United States
Rory Nathan Australia
Douglas B. Clark United Kingdom
Venkataramana Sridhar United States
Neil R. Viney Australia
J. R. Arnold
Citations per year, relative to J. R. Arnold J. R. Arnold (= 1×) peers Oldřich Rakovec

Countries citing papers authored by J. R. Arnold

Since Specialization
Citations

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

Fields of papers citing papers by J. R. Arnold

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. R. Arnold. 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 J. R. Arnold. The network helps show where J. R. Arnold may publish in the future.

Co-authorship network of co-authors of J. R. Arnold

This figure shows the co-authorship network connecting the top 25 collaborators of J. R. Arnold. A scholar is included among the top collaborators of J. R. Arnold 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 J. R. Arnold. J. R. Arnold 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.
Yan, Hongxiang, Zhuoran Duan, Mark S. Wigmosta, et al.. (2025). How Flood Hazards in a Warming Climate Could Be Amplified by Changes in Spatiotemporal Patterns and Mechanisms of Water Available for Runoff. Earth s Future. 13(3). 2 indexed citations
2.
Newman, Andrew J., E. D. Gutmann, Rachel McCrary, et al.. (2025). Lack of clear standards and usable comparisons of downscaled climate projections pose a roadblock for US climate discovery and adaptation. Environmental Research Letters. 20(5). 54067–54067. 1 indexed citations
3.
Mach, Katharine J., Kripa Jagannathan, Linda Shi, et al.. (2024). Research to Confront Climate Change Complexity: Intersectionality, Integration, and Innovative Governance. Earth s Future. 12(6). 1–17. 4 indexed citations
4.
Szalińska, Ewa, et al.. (2024). Sediment load assessments under climate change scenarios and a lack of integration between climatologists and environmental modelers. Scientific Reports. 14(1). 21727–21727. 1 indexed citations
5.
Yan, Hongxiang, Zhuoran Duan, Mark S. Wigmosta, et al.. (2024). Observation-Based Evaluation of Flood Estimation Techniques for a Small Snow-Dominated Basin in the Washington Cascade Mountains. Journal of Hydrologic Engineering. 29(3). 1 indexed citations
6.
Yan, Hongxiang, Ning Sun, Mark S. Wigmosta, et al.. (2023). The Role of Snowmelt Temporal Pattern in Flood Estimation for a Small Snow‐Dominated Basin in the Sierra Nevada. Water Resources Research. 59(10). 10 indexed citations
7.
Yan, Hongxiang, Zhuoran Duan, Mark S. Wigmosta, et al.. (2023). Next-Generation Intensity-Duration-Frequency Curves for Diverse Land across the Continental United States. Scientific Data. 10(1). 863–863. 1 indexed citations
8.
Newman, Andrew J., Martyn Clark, Andrew W. Wood, & J. R. Arnold. (2020). Probabilistic Spatial Meteorological Estimates for Alaska and the Yukon. Journal of Geophysical Research Atmospheres. 125(22). 17 indexed citations
9.
Wood, Andrew W., Naoki Mizukami, Martyn Clark, et al.. (2020). A new SUMMA and MizuRoute hydrologic modeling resource for US water applications. AGU Fall Meeting Abstracts. 2020. 1 indexed citations
10.
Mizukami, Naoki, Andrew J. Newman, Joseph Hamman, et al.. (2018). High-resolution statistically downscaled climate and hydrology projections over Alaska. AGU Fall Meeting Abstracts. 2018. 2 indexed citations
11.
Longman, Ryan J., Thomas W. Giambelluca, Michael A. Nullet, et al.. (2018). Compilation of climate data from heterogeneous networks across the Hawaiian Islands. Scientific Data. 5(1). 180012–180012. 38 indexed citations
12.
Mendoza, Pablo A., Andrew W. Wood, E. Clark, et al.. (2017). An intercomparison of approaches for improving operational seasonal streamflow forecasts. Hydrology and earth system sciences. 21(7). 3915–3935. 60 indexed citations
13.
Mendoza, Pablo A., Andrew W. Wood, E. Clark, et al.. (2017). An intercomparison of approaches for improving predictability in operational seasonal streamflow forecasting. 7 indexed citations
14.
Mizukami, Naoki, Martyn Clark, K. M. Sampson, et al.. (2016). mizuRoute version 1: a river network routing tool for a continental domain water resources applications. Geoscientific model development. 9(6). 2223–2238. 64 indexed citations
15.
Newman, Andrew J., Martyn Clark, K. M. Sampson, et al.. (2015). Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance. Hydrology and earth system sciences. 19(1). 209–223. 417 indexed citations breakdown →
16.
Dunbar, John A., et al.. (2015). Characterizing a Shallow Groundwater System beneath Irrigated Sugarcane with Electrical Resistivity and Radon (222Rn), Puunene, Hawaii. Journal of Environmental and Engineering Geophysics. 20(2). 165–181. 7 indexed citations
17.
Hossain, Faisal, J. R. Arnold, R. Edward Beighley, et al.. (2015). What Do Experienced Water Managers Think of Water Resources of Our Nation and Its Management Infrastructure?. PLoS ONE. 10(11). e0142073–e0142073. 9 indexed citations
19.
Shisanya, Chris A., Daniel N. Moriasi, Jakob Steiner, et al.. (2007). Fort Cobb Reservoir Watershed, Oklahoma and Thika River Watershed, Kenya Twinning Pilot Project. AGUFM. 2007. 1 indexed citations
20.
Luke, Winston T., J. R. Arnold, Thomas Watson, et al.. (2003). Aircraft Observations of the Tampa Urban Plume during BRACE: Transport, Photochemical, and Depositional Processes. AGUFM. 2003. 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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