Ping‐an Zhong

2.2k total citations
78 papers, 1.7k citations indexed

About

Ping‐an Zhong is a scholar working on Ocean Engineering, Water Science and Technology and Global and Planetary Change. According to data from OpenAlex, Ping‐an Zhong has authored 78 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Ocean Engineering, 45 papers in Water Science and Technology and 42 papers in Global and Planetary Change. Recurrent topics in Ping‐an Zhong's work include Water resources management and optimization (47 papers), Flood Risk Assessment and Management (36 papers) and Hydrology and Watershed Management Studies (33 papers). Ping‐an Zhong is often cited by papers focused on Water resources management and optimization (47 papers), Flood Risk Assessment and Management (36 papers) and Hydrology and Watershed Management Studies (33 papers). Ping‐an Zhong collaborates with scholars based in China, United States and Canada. Ping‐an Zhong's co-authors include Bin Xu, Feilin Zhu, Juan Chen, Yufei Ma, Yimeng Sun, Qingwen Lü, Yenan Wu, Xinyu Wan, Jieyu Li and Xin Huang and has published in prestigious journals such as Water Resources Research, Applied Energy and Journal of Hydrology.

In The Last Decade

Ping‐an Zhong

75 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
Ping‐an Zhong China 26 794 788 665 493 307 78 1.7k
Guohua Fang China 24 383 0.5× 760 1.0× 462 0.7× 482 1.0× 226 0.7× 115 1.8k
Huicheng Zhou China 28 783 1.0× 972 1.2× 647 1.0× 266 0.5× 384 1.3× 132 2.2k
Yizi Shang China 23 373 0.5× 708 0.9× 258 0.4× 189 0.4× 169 0.6× 80 1.5k
Fangfang Li China 18 276 0.3× 366 0.5× 206 0.3× 460 0.9× 124 0.4× 104 1.3k
S. Jamshid Mousavi Iran 27 1.0k 1.3× 1.1k 1.4× 532 0.8× 207 0.4× 623 2.0× 88 2.1k
Parisa‐Sadat Ashofteh Iran 21 776 1.0× 908 1.2× 431 0.6× 77 0.2× 229 0.7× 76 1.5k
Lydia Vamvakeridou-Lyroudia United Kingdom 19 442 0.6× 425 0.5× 287 0.4× 120 0.2× 389 1.3× 60 1.0k
Changming Ji China 19 639 0.8× 405 0.5× 166 0.2× 374 0.8× 344 1.1× 73 1.1k
V. Jothiprakash India 26 492 0.6× 975 1.2× 958 1.4× 219 0.4× 382 1.2× 105 2.1k
Doosun Kang South Korea 27 543 0.7× 603 0.8× 207 0.3× 163 0.3× 1.2k 4.0× 93 1.9k

Countries citing papers authored by Ping‐an Zhong

Since Specialization
Citations

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

Fields of papers citing papers by Ping‐an Zhong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ping‐an Zhong. 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 Ping‐an Zhong. The network helps show where Ping‐an Zhong may publish in the future.

Co-authorship network of co-authors of Ping‐an Zhong

This figure shows the co-authorship network connecting the top 25 collaborators of Ping‐an Zhong. A scholar is included among the top collaborators of Ping‐an Zhong 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 Ping‐an Zhong. Ping‐an Zhong 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.
Zhu, Feilin, et al.. (2025). Multi-step ahead probabilistic runoff forecasting with SHAP interpretability: a GPR-enhanced deep learning ensemble approach integrating teleconnection factors. Environmental Modelling & Software. 193. 106647–106647. 1 indexed citations
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Chen, Xinbao, et al.. (2025). Analysis of the Distribution Characteristics and Influencing Factors of Apparent Temperature in Chang–Zhu–Tan. Sustainability. 17(16). 7225–7225. 1 indexed citations
5.
Wang, Huili, Bin Xu, Jianyun Zhang, et al.. (2025). Simulation of extreme flood events for risk assessment for flood control of a reservoir-lake-river system under spatially dependent uncertainties. Journal of Hydrology Regional Studies. 60. 102567–102567. 1 indexed citations
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Zhong, Ping‐an, et al.. (2025). Testing machine learning algorithms as post-processing tools for hydro-meteorological modelling over a small river basin. Environmental Modelling & Software. 193. 106592–106592.
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Mo, Ran, Xu Bin, Jianyun Zhang, et al.. (2025). Multiobjective risk-based optimization for real-time interbasin water diversion under decomposed chance-constrained total water use. Journal of Hydrology Regional Studies. 58. 102252–102252. 2 indexed citations
10.
Zhu, Feilin, et al.. (2024). A machine learning framework for multi-step-ahead prediction of groundwater levels in agricultural regions with high reliance on groundwater irrigation. Environmental Modelling & Software. 180. 106146–106146. 4 indexed citations
11.
Fan, Yukun, Weifeng Liu, Feilin Zhu, et al.. (2024). Short-term stochastic multi-objective optimization scheduling of wind-solar-hydro hybrid system considering source-load uncertainties. Applied Energy. 372. 123781–123781. 25 indexed citations
12.
Zhu, Feilin, et al.. (2024). A multi-layer nesting and integration approach for predicting groundwater levels in agriculturally intensive areas using data-driven models. Journal of Hydrology. 643. 132038–132038. 3 indexed citations
13.
Zhong, Ping‐an, et al.. (2024). A hybrid model coupling process-driven and data-driven models for improved real-time flood forecasting. Journal of Hydrology. 638. 131494–131494. 21 indexed citations
14.
Wang, Yiwen, et al.. (2024). A modified Xin'anjiang model and its application for considering the regulatory and storage effects of small-scale water storage structures. Journal of Hydrology. 630. 130675–130675. 9 indexed citations
15.
Wang, Sen, et al.. (2024). Multi-objective optimization operation of multiple water sources under inflow-water demand forecast dual uncertainties. Journal of Hydrology. 630. 130679–130679. 6 indexed citations
16.
Wang, Han, Ping‐an Zhong, Ervin Zsótér, et al.. (2023). Regional Adaptability of Global and Regional Hydrological Forecast System. Water. 15(2). 347–347. 4 indexed citations
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Zhong, Ping‐an, et al.. (2020). Research on intelligent prediction and zonation of basin-scale flood risk based on LSTM method. Environmental Monitoring and Assessment. 192(6). 387–387. 18 indexed citations
19.
Wu, Yenan, Upmanu Lall, Carlos Lima, & Ping‐an Zhong. (2018). Local and regional flood frequency analysis based on hierarchicalBayesian model: application to annual maximum streamflow for theHuaihe River basin. Biogeosciences (European Geosciences Union). 8 indexed citations
20.
Chen, Juan, et al.. (2014). Risk Analysis for Real-Time Flood Control Operation of a Reservoir. Journal of Water Resources Planning and Management. 141(8). 42 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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