Guangyuan Kan

1.7k total citations · 1 hit paper
54 papers, 1.3k citations indexed

About

Guangyuan Kan is a scholar working on Global and Planetary Change, Water Science and Technology and Environmental Engineering. According to data from OpenAlex, Guangyuan Kan has authored 54 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Global and Planetary Change, 29 papers in Water Science and Technology and 26 papers in Environmental Engineering. Recurrent topics in Guangyuan Kan's work include Hydrology and Watershed Management Studies (28 papers), Hydrological Forecasting Using AI (21 papers) and Flood Risk Assessment and Management (18 papers). Guangyuan Kan is often cited by papers focused on Hydrology and Watershed Management Studies (28 papers), Hydrological Forecasting Using AI (21 papers) and Flood Risk Assessment and Management (18 papers). Guangyuan Kan collaborates with scholars based in China, United States and Switzerland. Guangyuan Kan's co-authors include Xiaoyan He, Liuqian Ding, Jiren Li, Minglei Ren, F. Wang, Haijun Yu, Ke Liang, Wei Shao, Dawei Zhang and Gang Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Energy and Journal of Hydrology.

In The Last Decade

Guangyuan Kan

52 papers receiving 1.3k citations

Hit Papers

align trajectories

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.

Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

2020 274 citations F. Wang, Wei Shao et al. Frontiers in Earth Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Guangyuan Kan China	22	858	554	406	312	152	54	1.3k
Ping Feng China	24	1.1k 1.3×	790 1.4×	380 0.9×	279 0.9×	103 0.7×	134	1.7k
Goutam Konapala United States	16	1.1k 1.3×	782 1.4×	434 1.1×	373 1.2×	125 0.8×	21	1.6k
S. Adarsh India	22	769 0.9×	345 0.6×	481 1.2×	208 0.7×	98 0.6×	141	1.4k
Darshan Mehta India	20	688 0.8×	469 0.8×	482 1.2×	186 0.6×	82 0.5×	60	1.1k
Jiancang Xie China	19	756 0.9×	560 1.0×	497 1.2×	237 0.8×	131 0.9×	76	1.4k
Peyman Abbaszadeh United States	23	938 1.1×	608 1.1×	581 1.4×	553 1.8×	165 1.1×	34	1.7k
Đào Nguyên Khôi Vietnam	21	913 1.1×	869 1.6×	434 1.1×	201 0.6×	162 1.1×	52	1.4k
Sutat Weesakul Thailand	19	1.2k 1.4×	552 1.0×	637 1.6×	456 1.5×	156 1.0×	48	1.8k
Philippe Gourbesville France	20	800 0.9×	580 1.0×	311 0.8×	249 0.8×	132 0.9×	80	1.2k

Countries citing papers authored by Guangyuan Kan

Since Specialization

Citations

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

Fields of papers citing papers by Guangyuan Kan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guangyuan Kan

This figure shows the co-authorship network connecting the top 25 collaborators of Guangyuan Kan. A scholar is included among the top collaborators of Guangyuan Kan 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 Guangyuan Kan. Guangyuan Kan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Lu, Guo-Wei, Yao Li, Jinbo Tang, et al.. (2025). A Semantic-Guided Cross-Attention Network for Change Detection in High-Resolution Remote Sensing Images. Remote Sensing. 17(10). 1749–1749.

Kan, Guangyuan, et al.. (2023). A Hybrid Theory-Driven and Data-Driven Modeling Method for Solving the Shallow Water Equations. Water. 15(17). 3140–3140. 3 indexed citations

Kan, Guangyuan, et al.. (2023). Research on Rain Pattern Classification Based on Machine Learning: A Case Study in Pi River Basin. Water. 15(8). 1570–1570. 7 indexed citations

Kan, Guangyuan, et al.. (2023). Massively Parallel Monte Carlo Sampling for Xinanjiang Hydrological Model Parameter Optimization Using CPU-GPU Computer Cluster. Water. 15(15). 2810–2810. 2 indexed citations

Li, Zhi, Xianwu Xue, Robert A. Clark, et al.. (2023). A decadal review of the CREST model family: Developments, applications, and outlook. SHILAP Revista de lepidopterología. 20. 100159–100159. 2 indexed citations

Chen, Sijie, et al.. (2022). Inverse Estimation of Soil Hydraulic Parameters in a Landslide Deposit Based on a DE-MC Approach. Water. 14(22). 3693–3693. 4 indexed citations

Zhang, Jianyun, Zhenxin Bao, Guoqing Wang, et al.. (2022). The impacts of natural and anthropogenic factors on vegetation change in the Yellow-Huai-Hai River Basin. Frontiers in Earth Science. 10. 9 indexed citations

Zuo, Depeng, Guangyuan Kan, Hongquan Sun, Hongbin Zhang, & Ke Liang. (2021). Improving computational efficiency of GLUE method for hydrological model uncertainty and parameter estimation using CPU-GPU hybrid high performance computer cluster. 3 indexed citations

Zuo, Depeng, Zongxue Xu, Wenchao Sun, et al.. (2021). Time-lag effects of climatic change and drought on vegetation dynamics in an alpine river basin of the Tibet Plateau, China. Journal of Hydrology. 600. 126532–126532. 76 indexed citations

10.

Zuo, Depeng, Zongxue Xu, Wenchao Sun, et al.. (2021). Dynamic changes of land use/cover and landscape pattern in a typical alpine river basin of theQinghai‐TibetPlateau, China. Land Degradation and Development. 32(15). 4327–4339. 34 indexed citations

11.

Wang, Kai, et al.. (2021). Analysis of Impact Factors for Flood Early Warning, a Case Study in Wangjiaba Basin of Huai River. IOP Conference Series Earth and Environmental Science. 668(1). 12040–12040. 1 indexed citations

12.

Wang, F., Wei Shao, Haijun Yu, et al.. (2020). Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series. Frontiers in Earth Science. 8. 274 indexed citations breakdown →

13.

Lei, Tianjie, Shuguang Li, Yang Wang, et al.. (2020). Review of drought impacts on carbon cycling in grassland ecosystems. Frontiers of Earth Science. 14(2). 462–478. 25 indexed citations

14.

He, Xiaoyan, Guangyuan Kan, F. Wang, et al.. (2017). A Comparison of Flood Control Standards for Reservoir Engineering for Different Countries. Water. 9(3). 152–152. 23 indexed citations

15.

Kan, Guangyuan, et al.. (2017). Air quality analysis and forecast for environment and public health protection: a case study in Beijing, China. Transylvanian Review. 1 indexed citations

16.

Kan, Guangyuan. (2017). Study on Application and Comparison of Data-driven Model and Semi-data-driven Model for Rainfall-runoff Simulation. SHILAP Revista de lepidopterología. 3 indexed citations

17.

Kan, Guangyuan, Liuqian Ding, Jiren Li, et al.. (2017). Daily streamflow simulation based on the improved machine learning method. Tecnología y Ciencias del Agua. 8(2). 51–60. 5 indexed citations

18.

Kan, Guangyuan, et al.. (2017). A heterogeneous computing accelerated SCE-UA global optimization method using OpenMP, OpenCL, CUDA, and OpenACC. Water Science & Technology. 76(7). 1640–1651. 14 indexed citations

19.

Kan, Guangyuan, Xiaoyan He, Liuqian Ding, et al.. (2017). Fast hydrological model calibration based on the heterogeneous parallel computing accelerated shuffled complex evolution method. Engineering Optimization. 50(1). 106–119. 21 indexed citations

20.

Lei, Tianjie, Zhiguo Pang, Lin Li, et al.. (2016). Drought and Carbon Cycling of Grassland Ecosystems under Global Change: A Review. Water. 8(10). 460–460. 56 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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