Dapeng Feng
- Water Science and Technology top 1%
- Environmental Engineering top 1%
- Global and Planetary Change top 5%
- Atmospheric Science top 10%
- Nature and Landscape Conservation
- Topics
- Hydrology and Watershed Management Studies (13 papers)Hydrological Forecasting Using AI (10 papers)Flood Risk Assessment and Management (7 papers)
- Partner nations
- United StatesChinaSaudi Arabia
In The Last Decade
Dapeng Feng
13 papers receiving 870 citations
Hit Papers
Peers
Comparison fields: 5 of 47
- Water Science and Technology 707
- Environmental Engineering 632
- Global and Planetary Change 456
- Atmospheric Science 112
- Nature and Landscape Conservation 44
Countries citing papers authored by Dapeng Feng
This map shows the geographic impact of Dapeng Feng'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 Dapeng Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dapeng Feng more than expected).
Fields of papers citing papers by Dapeng Feng
This network shows the impact of papers produced by Dapeng Feng. 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 Dapeng Feng. The network helps show where Dapeng Feng may publish in the future.
Co-authorship network of co-authors of Dapeng Feng
This figure shows the co-authorship network connecting the top 25 collaborators of Dapeng Feng. A scholar is included among the top collaborators of Dapeng Feng 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 Dapeng Feng. Dapeng Feng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 12 | |
| 3 | 33 | |
| 4 | 15 | |
| 5 | 64 | |
| 6 | 25 | |
| 7 | 86 | |
| 8 | Differentiable, Learnable, Regionalized Process‐Based Models With Multiphysical Outputs can Approach State‐Of‐The‐Art Hydrologic Prediction Accuracybreakdown → | 142 |
| 9 | 121 | |
| 10 | 66 | |
| 11 | 71 | |
| 12 | From Hydrometeorology to River Water Quality: Can a Deep Learning Model Predict Dissolved Oxygen at the Continental Scale?breakdown → | 204 |
| 13 | 42 |
About Dapeng Feng
Dapeng Feng is a scholar working on Water Science and Technology, Environmental Engineering and Global and Planetary Change, having authored 13 papers that have together received 883 indexed citations. Recurring topics across this work include Hydrology and Watershed Management Studies (13 papers), Hydrological Forecasting Using AI (10 papers) and Flood Risk Assessment and Management (7 papers). The work is most often cited by research in Water Science and Technology (707 citations), Environmental Engineering (632 citations) and Global and Planetary Change (456 citations). Dapeng Feng has collaborated with scholars based in United States, China and Saudi Arabia. Frequent co-authors include Chaopeng Shen, Kathryn Lawson, Wen‐Ping Tsai, Jiangtao Liu, Gary Sterle, A. A. Harpold, Wei Zhi, Li Li, Kuai Fang and Daniel Kifer. Their work appears in journals such as Environmental Science & Technology, Water Resources Research and Geophysical Research Letters.
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.