Qingyun Duan

39.7k total citations · 15 hit papers
326 papers, 26.9k citations indexed

About

Qingyun Duan is a scholar working on Global and Planetary Change, Atmospheric Science and Water Science and Technology. According to data from OpenAlex, Qingyun Duan has authored 326 papers receiving a total of 26.9k indexed citations (citations by other indexed papers that have themselves been cited), including 163 papers in Global and Planetary Change, 126 papers in Atmospheric Science and 119 papers in Water Science and Technology. Recurrent topics in Qingyun Duan's work include Hydrology and Watershed Management Studies (114 papers), Climate variability and models (95 papers) and Meteorological Phenomena and Simulations (78 papers). Qingyun Duan is often cited by papers focused on Hydrology and Watershed Management Studies (114 papers), Climate variability and models (95 papers) and Meteorological Phenomena and Simulations (78 papers). Qingyun Duan collaborates with scholars based in China, United States and Australia. Qingyun Duan's co-authors include Soroosh Sorooshian, Vijai Kumar Gupta, Chiyuan Miao, Qiaohong Sun, John C. Schaake, Kenneth E. Mitchell, Newsha Ajami, Aizhong Ye, Ego Seeman and Wei Gong and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Chemical Physics and Journal of Geophysical Research Atmospheres.

In The Last Decade

Qingyun Duan

320 papers receiving 25.9k citations

Hit Papers

Effective and efficient global optimization for conceptua... 1992 2026 2003 2014 1992 2017 1993 1994 2011 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qingyun Duan China 74 15.8k 12.8k 9.5k 6.8k 1.7k 326 26.9k
Vijay P. Singh United States 90 22.9k 1.4× 16.5k 1.3× 5.5k 0.6× 9.1k 1.3× 3.9k 2.3× 757 35.9k
Taha B. M. J. Ouarda Canada 63 8.9k 0.6× 6.1k 0.5× 2.9k 0.3× 3.4k 0.5× 1.0k 0.6× 387 13.4k
M. B. Parlange United States 68 7.4k 0.5× 3.2k 0.2× 5.3k 0.6× 7.3k 1.1× 1.3k 0.7× 368 17.1k
Xin Li China 78 9.9k 0.6× 4.5k 0.4× 10.7k 1.1× 5.8k 0.8× 3.5k 2.0× 1.1k 26.7k
Hoshin V. Gupta United States 77 20.6k 1.3× 23.8k 1.9× 8.5k 0.9× 14.0k 2.0× 1.9k 1.1× 290 33.9k
Amir AghaKouchak United States 83 18.1k 1.1× 6.1k 0.5× 9.0k 0.9× 2.9k 0.4× 1.4k 0.8× 295 24.6k
Taikan Oki Japan 63 11.4k 0.7× 11.5k 0.9× 5.1k 0.5× 4.0k 0.6× 2.1k 1.2× 380 21.7k
Soroosh Sorooshian United States 90 24.9k 1.6× 21.5k 1.7× 15.8k 1.7× 14.6k 2.1× 4.0k 2.3× 382 40.9k
Sonia I. Seneviratne Switzerland 102 30.9k 2.0× 7.6k 0.6× 17.7k 1.9× 8.3k 1.2× 3.4k 2.0× 331 41.3k
Alberto Montanari Italy 52 6.5k 0.4× 5.8k 0.4× 1.7k 0.2× 2.4k 0.4× 926 0.5× 228 9.7k

Countries citing papers authored by Qingyun Duan

Since Specialization
Citations

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

Fields of papers citing papers by Qingyun Duan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingyun Duan

This figure shows the co-authorship network connecting the top 25 collaborators of Qingyun Duan. A scholar is included among the top collaborators of Qingyun Duan 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 Qingyun Duan. Qingyun Duan 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.
Miao, Chiyuan, et al.. (2025). Vegetation and wind speed dominate precipitation-evaporation recycling processes during 1980–2021. Science Bulletin. 70(15). 2426–2430.
2.
Wysession, M. E., Lisa M. Beal, Graziella Caprarelli, et al.. (2025). The Executive Order “Restoring Gold Standard Science” is Dangerous for America. AGU Advances. 6(4).
3.
Xenopoulos, Marguerite A., Lisa M. Beal, Graziella Caprarelli, et al.. (2025). Commitment to Advance Excellence and Inclusion in the Earth and Space Sciences Scholarly Publications. AGU Advances. 6(2).
4.
Sun, Ruochen, et al.. (2024). Surrogate modelling-based multi-objective optimization for best management practices of nonpoint source pollution. Water Research. 269. 122788–122788. 5 indexed citations
5.
6.
Sun, Ruochen, Baoxiang Pan, & Qingyun Duan. (2023). A surrogate modeling method for distributed land surface hydrological models based on deep learning. Journal of Hydrology. 624. 129944–129944. 20 indexed citations
7.
Zhao, Tongtiegang, et al.. (2023). Reliability of Ensemble Climatological Forecasts. Water Resources Research. 59(9). 5 indexed citations
8.
Florindo, Fabio, Valerio Acocella, Annmarie G. Carlton, et al.. (2023). 60 Years and Beyond of Reviews of Geophysics. Reviews of Geophysics. 61(2). 2 indexed citations
9.
Fan, Yurui, L. Yu, Xiaogang Shi, & Qingyun Duan. (2021). Tracing Uncertainty Contributors in the Multi‐Hazard Risk Analysis for Compound Extremes. Earth s Future. 9(12). 11 indexed citations
10.
Yin, Yuanyuan, Lei Wang, Zhongjing Wang, et al.. (2020). Quantifying Water Scarcity in Northern China Within the Context of Climatic and Societal Changes and South‐to‐North Water Diversion. Earth s Future. 8(8). 58 indexed citations
11.
Gan, Yanjun, Xin‐Zhong Liang, Qingyun Duan, et al.. (2019). Assessment and Reduction of the Physical Parameterization Uncertainty for Noah‐MP Land Surface Model. Water Resources Research. 55(7). 5518–5538. 38 indexed citations
12.
Ma, Feng, Lifeng Luo, Aizhong Ye, & Qingyun Duan. (2018). Seasonal drought predictability and forecast skill in the semi-arid endorheic Heihe River basin in northwestern China. Hydrology and earth system sciences. 22(11). 5697–5709. 20 indexed citations
13.
Sun, Qiaohong, Chiyuan Miao, & Qingyun Duan. (2017). Changes in the Spatial Heterogeneity and Annual Distribution of Observed Precipitation across China. Journal of Climate. 30(23). 9399–9416. 60 indexed citations
14.
Wang, Chen, Qingyun Duan, Charles Tong, Zhenhua Di, & Wei Gong. (2015). A GUI platform for uncertainty quantification of complex dynamical models. Environmental Modelling & Software. 76. 1–12. 49 indexed citations
15.
Wang, Chen, Qingyun Duan, Wei Gong, et al.. (2014). An evaluation of adaptive surrogate modeling based optimization with two benchmark problems. Environmental Modelling & Software. 60. 167–179. 189 indexed citations
16.
Duan, Qingyun, Aizhong Ye, & Wei Gong. (2014). Evaluation of North American Multi-Model Ensemble (NMME) Climate Forecasts in China. 2014 AGU Fall Meeting. 2014.
17.
Gan, Yanjun, Qingyun Duan, Wei Gong, et al.. (2013). A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model. Environmental Modelling & Software. 51. 269–285. 270 indexed citations breakdown →
18.
Li, Jianduo, Qingyun Duan, Wei Gong, et al.. (2013). Assessing parameter importance of the Common Land Model based on qualitative and quantitative sensitivity analysis. Hydrology and earth system sciences. 17(8). 3279–3293. 68 indexed citations
19.
Duan, Qingyun, et al.. (2009). Quantification of Parameter Uncertainty of the Common Land Model (CoLM). AGU Fall Meeting Abstracts. 2009. 2 indexed citations
20.
Schaake, John C., et al.. (2006). The US MOPEX data set.. University of North Texas Digital Library (University of North Texas). 9–28. 2 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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