Binquan Li

2.3k total citations
84 papers, 1.8k citations indexed

About

Binquan Li is a scholar working on Water Science and Technology, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Binquan Li has authored 84 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Water Science and Technology, 54 papers in Global and Planetary Change and 27 papers in Environmental Engineering. Recurrent topics in Binquan Li's work include Hydrology and Watershed Management Studies (54 papers), Flood Risk Assessment and Management (34 papers) and Hydrology and Drought Analysis (33 papers). Binquan Li is often cited by papers focused on Hydrology and Watershed Management Studies (54 papers), Flood Risk Assessment and Management (34 papers) and Hydrology and Drought Analysis (33 papers). Binquan Li collaborates with scholars based in China, United States and Georgia. Binquan Li's co-authors include Zhongmin Liang, Yiming Hu, Özgür Kişi, Rana Muhammad Adnan, Mohammad Zounemat‐Kermani, Zhongbo Yu, Kumud Acharya, Salim Heddam, Slaviša Trajković and Jun Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Water Resources Research and Journal of Hydrology.

In The Last Decade

Binquan Li

78 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Binquan Li China 22 1.1k 1.0k 761 326 156 84 1.8k
Zhongmin Liang China 25 1.3k 1.2× 1.3k 1.3× 916 1.2× 381 1.2× 170 1.1× 92 2.1k
Elena Toth Italy 20 1.2k 1.1× 1.1k 1.1× 1.1k 1.4× 262 0.8× 176 1.1× 50 1.8k
Rakesh Khosa India 17 726 0.7× 774 0.8× 685 0.9× 249 0.8× 141 0.9× 57 1.4k
Caihong Hu China 21 1.1k 1.0× 1.1k 1.1× 1.0k 1.4× 264 0.8× 116 0.7× 68 1.8k
Rasoul Mirabbasi Iran 27 831 0.8× 1.6k 1.5× 529 0.7× 332 1.0× 93 0.6× 81 2.1k
Mehdi Vafakhah Iran 24 899 0.8× 1.0k 1.0× 864 1.1× 241 0.7× 111 0.7× 112 1.9k
A. K. Gosain India 19 1.3k 1.2× 1.2k 1.2× 1.1k 1.4× 424 1.3× 168 1.1× 80 2.1k
Bahaa Khalil Canada 18 883 0.8× 956 0.9× 972 1.3× 205 0.6× 164 1.1× 33 1.8k
V. V. Srinivas India 23 944 0.9× 1.6k 1.6× 686 0.9× 611 1.9× 81 0.5× 63 2.1k
Jiancang Xie China 19 560 0.5× 756 0.7× 497 0.7× 237 0.7× 114 0.7× 76 1.4k

Countries citing papers authored by Binquan Li

Since Specialization
Citations

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

Fields of papers citing papers by Binquan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Binquan Li

This figure shows the co-authorship network connecting the top 25 collaborators of Binquan Li. A scholar is included among the top collaborators of Binquan Li 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 Binquan Li. Binquan Li 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.
Li, Binquan, et al.. (2025). Exploring coupled coordination and synergistic evolution in a multi-dimensional water system of the Yellow River Basin. Ecological Indicators. 176. 113687–113687. 1 indexed citations
2.
Liang, Zhongmin, Jianhong Zhou, Quanxi Shao, et al.. (2025). Multi-layer grid-scale soil moisture estimation using spatiotemporal deep learning methods with physical constraints. Journal of Hydrology. 657. 133086–133086. 5 indexed citations
3.
Chen, Cheng, et al.. (2025). Performance enhancement of deep learning model with attention mechanism and FCN model in flood forecasting. Journal of Hydrology. 658. 133221–133221. 2 indexed citations
4.
Li, Binquan, et al.. (2025). Parameter optimization method of hydrological model based on neural ordinary differential equations. Journal of Lake Sciences. 37(3). 1000–1010.
5.
Chen, Xu, et al.. (2025). Spatial-temporal correlation-based analysis of multi-source flood coincidence risks: A case study of the middle and lower Yangtze River basin. Journal of Hydrology Regional Studies. 58. 102265–102265. 1 indexed citations
6.
Li, Binquan, et al.. (2024). Hydrological and hydrodynamic coupling simulation under composite underlying surfaces in urban polder areas. Journal of Hydrology Regional Studies. 57. 102154–102154. 2 indexed citations
7.
Zhang, Mingjin, Zhongmin Liang, Jian Wang, et al.. (2024). Improved Multi-objective Butterfly Optimization Algorithm and its Application in Cascade Reservoirs Optimal Operation Considering Ecological Flow. Water Resources Management. 38(12). 4803–4821. 5 indexed citations
8.
9.
Zhang, Tuantuan, et al.. (2024). Statistical Post-Processing for Precipitation Forecast Through Deep Learning Coupling Large-Scale and Local-Scale Spatiotemporal Information. Water Resources Management. 39(1). 145–160. 2 indexed citations
10.
Liang, Zhongmin, et al.. (2023). An improved butterfly optimization algorithm and its application in cascade hydropower generation operation. Journal of Hydroinformatics. 25(3). 1121–1138. 7 indexed citations
11.
Wang, Jun, et al.. (2023). Flood risk mapping for the area with mixed floods and human impact: a case study of Yarkant River Basin in Xinjiang, China. Environmental Research Communications. 5(9). 95005–95005. 3 indexed citations
12.
Hu, Yiming, et al.. (2023). The numerical error of the Xinanjiang model. Journal of Hydrology. 619. 129324–129324. 9 indexed citations
13.
14.
Zhang, Tuantuan, Zhongmin Liang, Wentao Li, et al.. (2023). Statistical post-processing of precipitation forecasts using circulation classifications and spatiotemporal deep neural networks. Hydrology and earth system sciences. 27(10). 1945–1960. 9 indexed citations
15.
Li, Binquan, et al.. (2023). Surface Subsidence over a Coastal City Using SBAS-InSAR with Sentinel-1A Data: A Case of Nansha District, China. Remote Sensing. 16(1). 55–55. 8 indexed citations
16.
Li, Yongsheng, et al.. (2021). Sentinel-1 SAR-Based coseismic deformation monitoring service for rapid geodetic imaging of global earthquakes. SHILAP Revista de lepidopterología. 1(1). 11–19. 25 indexed citations
17.
Adnan, Rana Muhammad, Zhongmin Liang, Salim Heddam, et al.. (2019). Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as inputs. Journal of Hydrology. 586. 124371–124371. 213 indexed citations
18.
Li, Dayang, et al.. (2019). Multicriteria assessment framework of flood events simulated with vertically mixed runoff model in semiarid catchments in the middle Yellow River. Natural hazards and earth system sciences. 19(9). 2027–2037. 13 indexed citations
19.
Liang, Zhongmin, Yujie Li, Yiming Hu, Binquan Li, & Jun Wang. (2017). A data-driven SVR model for long-term runoff prediction and uncertainty analysis based on the Bayesian framework. Theoretical and Applied Climatology. 133(1-2). 137–149. 72 indexed citations
20.
Hu, Yiming, et al.. (2016). Study on the estimation of design value under non-stationary environment. 14(1). 83. 12 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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