Shengyue Chen Google Scholar: h-index, Total Citations, and Citation Map
Shengyue Chen's h-index is 7 (7 i10-index, 414+ total citations across 18+ publications) according to Google Scholar as of October 2026. Shengyue Chen is affiliated with Peking University.
Shengyue Chen is a researcher affiliated with Peking University, specializing in Hydroecology, Watershed Processes, Land Water Interaction. Their work has been cited 414 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Shengyue Chen's Citation Metrics
Bibliometric impact based on 18 indexed publications. Of these, 18 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 7
- i10-Index
- 7
- Total Citations
- 414
- Citing Countries
- 25
As of October 2026.
Shengyue Chen has an h-index of 7 and 414 total citations across 18 publications, with research cited by institutions in 25 countries.
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Global Impact Map
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Improving daily streamflow simulations for data-scarce watersheds using the coupled SWAT-LSTM approach
2023168
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
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Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
197 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed a coupled SWAT-LSTM framework to enhance hydrological and water quality modeling in data-scarce environments, addressing non-stationarity and enabling explainable analysis of harmful algal blooms.
The researcher developed a machine-learning framework to analyze dynamic river water quality patterns and drivers, subsequently integrating causal inference to assess surface water quality in coastal regions.
The researcher developed a framework integrating water quality restoration costs with ecosystem service flows to quantify ecological compensation standards, demonstrated in the Taoxi Creek Watershed.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Shengyue Chen's research
Shengyue Chen is a researcher in Hydroecology, Watershed Processes and Land Water Interaction at Peking University. Their work has been cited 414 times across 18 publications (h-index 7), according to Google Scholar.
Their most-cited work, “Improving daily streamflow simulations for data-scarce watersheds using the coupled SWAT-LSTM approach” (2023), has accumulated 168 citations. Other influential works include “A coupled model to improve river water quality prediction towards addressing non-stationarity and data limitation” (2024) with 102 citations and “Explainable deep learning identifies patterns and drivers of freshwater harmful algal blooms” (2025) with 31 citations.
Citations of Shengyue Chen's research come primarily from China, United States and Germany, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
