Qidong Peng

1.2k total citations · 1 hit paper
29 papers, 854 citations indexed

About

Qidong Peng is a scholar working on Water Science and Technology, Nature and Landscape Conservation and Environmental Engineering. According to data from OpenAlex, Qidong Peng has authored 29 papers receiving a total of 854 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Water Science and Technology, 12 papers in Nature and Landscape Conservation and 10 papers in Environmental Engineering. Recurrent topics in Qidong Peng's work include Fish Ecology and Management Studies (12 papers), Hydrology and Watershed Management Studies (11 papers) and Hydrological Forecasting Using AI (9 papers). Qidong Peng is often cited by papers focused on Fish Ecology and Management Studies (12 papers), Hydrology and Watershed Management Studies (11 papers) and Hydrological Forecasting Using AI (9 papers). Qidong Peng collaborates with scholars based in China, United States and Canada. Qidong Peng's co-authors include Tiantian Yang, Soroosh Sorooshian, Junqiang Lin, Di Zhang, Dongsheng Wang, Xuefei Liu, Ata Akbari Asanjan, Kuolin Hsu, Daqing Chen and Xinbin Duan and has published in prestigious journals such as Journal of Hydrology, Sustainability and Environmental Science and Pollution Research.

In The Last Decade

Qidong Peng

26 papers receiving 838 citations

Hit Papers

Modeling and simulating of reservoir operation using the ... 2018 2026 2020 2023 2018 50 100 150 200 250
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.

  1. Modeling and simulating of reservoir operation using the artificial neural network, support vector regression, deep learning algorithm
    2018 282 citations Di Zhang, Qidong Peng et al. Journal of Hydrology profile →

Peers

Qidong Peng
G. B. Sahoo United States
S. Rehana India
Huichao Dai China
Mohamad Javad Alizadeh Iran
Yiqing Guan China
Pengfei Shi China
Vassilis Z. Antonopoulos Greece
Gerald Corzo Netherlands
Cláudio José Cavalcante Blanco Brazil
Lingling Ni China
G. B. Sahoo United States
Qidong Peng
Citations per year, relative to Qidong Peng Qidong Peng (= 1×) peers G. B. Sahoo

Countries citing papers authored by Qidong Peng

Since Specialization
Citations

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

Fields of papers citing papers by Qidong Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qidong Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Qidong Peng. A scholar is included among the top collaborators of Qidong Peng 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 Qidong Peng. Qidong Peng 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.
Jiang, Aihui, et al.. (2025). Forty years of dynamics: Population trends and habitat changes of the Black-necked Crane (Grus nigricollis) in China. Global Ecology and Conservation. 61. e03651–e03651.
2.
Jiang, Aihui, Dongsheng Wang, Zhen Ning, et al.. (2025). Spatio-temporal characteristics and influencing factors of water quality in Xiangxi Bay under the operation of the three gorges reservoir. Journal of Contaminant Hydrology. 270. 104518–104518. 1 indexed citations
3.
Zhang, Di, Yiming Ma, Aihui Jiang, et al.. (2025). Long-Term Water Temperature Forecasting in Fish Spawning Grounds Downstream of Hydropower Stations Using Machine Learning. Sustainability. 17(10). 4514–4514.
4.
Zhang, Shaogeng, et al.. (2024). Water Quality by Spectral Proper Orthogonal Decomposition and Deep Learning Algorithms. Sustainability. 17(1). 114–114. 1 indexed citations
5.
Jin, Tiantian, et al.. (2023). Wetland Evolution and Driving Force Analysis in the Qingtongxia Reservoir Area. Land. 12(4). 930–930.
6.
Xu, Yi, Junqiang Lin, Xiaohui Lei, et al.. (2023). Assessment of the spatiotemporal water quality variations in the Middle Route of China’s South-to-North Water Diversion Project by multivariate analysis. Environmental Science and Pollution Research. 30(15). 44206–44222. 11 indexed citations
7.
Lin, Junqiang, Dongsheng Wang, Jin Huang, et al.. (2023). Experimental study of the behavioral response of fish to changes in hydrodynamic indicators in a near-natural environment. Ecological Indicators. 154. 110813–110813. 4 indexed citations
8.
Jin, Tiantian, et al.. (2022). Identifying the extent of the spatial expression of landscape fragmentation based on scale effect analysis in Southwest China. Ecological Indicators. 141. 109120–109120. 23 indexed citations
9.
Liu, Jun, et al.. (2022). Cascade reservoirs adaptive refined simulation model based on the mechanism-AI coupling modeling paradigm. Journal of Hydrology. 612. 128229–128229. 11 indexed citations
10.
Zhang, Di, Dongsheng Wang, Qidong Peng, et al.. (2022). Prediction of the outflow temperature of large-scale hydropower using theory-guided machine learning surrogate models of a high-fidelity hydrodynamics model. Journal of Hydrology. 606. 127427–127427. 25 indexed citations
11.
Espinoza, Vicky, Zhuo Hao, Wenjun Chen, et al.. (2021). Regional Hydrologic Classification for Sustainable Dam Operations in China: Exploratory Applications in the Yangtze River Basin. JAWRA Journal of the American Water Resources Association. 58(6). 1216–1229. 2 indexed citations
12.
13.
Peng, Qidong, et al.. (2019). ANALYSIS OF REDUCTIVE SUBSTANCES CONCENTRATION IN SURFACE WATER IN DIFFERENT WATER STAGES-SOME CASES FROM CHINA. Proceedings of the IAHR World Congress. 38. 3112–3117. 1 indexed citations
14.
Asanjan, Ata Akbari, Tiantian Yang, Kuolin Hsu, et al.. (2018). Short‐Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks. Journal of Geophysical Research Atmospheres. 123(22). 160 indexed citations
15.
16.
Zhang, Di, Qidong Peng, Dongsheng Wang, et al.. (2018). Modeling and simulating of reservoir operation using the artificial neural network, support vector regression, deep learning algorithm. Journal of Hydrology. 565. 720–736. 282 indexed citations breakdown →
17.
18.
Jiang, Yan, et al.. (2011). Analysis of spatial and temporal variation of water quality in Huaihe River Basin. 42(11). 1283–1288. 14 indexed citations
19.
Peng, Qidong. (2008). Experiment and Modelling of Adsorption of Phosphorus to Sediment in the Three Gorges Reservoir. Keji daobao. 1 indexed citations
20.
Peng, Qidong. (2005). Progress of research on numerical simulation of Pearl River Delta. Water Resources and Hydropower Engineering. 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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