Shenglian Guo

16.0k total citations · 2 hit papers
321 papers, 12.5k citations indexed

About

Shenglian Guo is a scholar working on Water Science and Technology, Global and Planetary Change and Ocean Engineering. According to data from OpenAlex, Shenglian Guo has authored 321 papers receiving a total of 12.5k indexed citations (citations by other indexed papers that have themselves been cited), including 237 papers in Water Science and Technology, 223 papers in Global and Planetary Change and 101 papers in Ocean Engineering. Recurrent topics in Shenglian Guo's work include Hydrology and Watershed Management Studies (196 papers), Flood Risk Assessment and Management (139 papers) and Hydrology and Drought Analysis (112 papers). Shenglian Guo is often cited by papers focused on Hydrology and Watershed Management Studies (196 papers), Flood Risk Assessment and Management (139 papers) and Hydrology and Drought Analysis (112 papers). Shenglian Guo collaborates with scholars based in China, Norway and United States. Shenglian Guo's co-authors include Pan Liu, Lihua Xiong, Chong‐Yu Xu, Yanlai Zhou, Jiabo Yin, Hua Chen, Dedi Liu, Jie Chen, Vijay P. Singh and Fi‐John Chang and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Renewable and Sustainable Energy Reviews.

In The Last Decade

Shenglian Guo

312 papers receiving 12.1k citations

Hit Papers

Large increase in global storm runoff extremes driven by ... 2018 2026 2020 2023 2018 2023 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shenglian Guo China 61 7.7k 7.5k 3.3k 2.3k 1.7k 321 12.5k
Jery R. Stedinger United States 58 6.8k 0.9× 6.6k 0.9× 3.9k 1.2× 1.5k 0.7× 1.2k 0.7× 178 11.8k
Donald H. Burn Canada 50 6.6k 0.9× 5.6k 0.7× 1.1k 0.3× 2.2k 1.0× 2.1k 1.2× 162 9.5k
Ashish Sharma Australia 66 11.2k 1.5× 6.4k 0.9× 990 0.3× 3.6k 1.6× 5.5k 3.2× 402 14.9k
Vahid Nourani Iran 52 3.7k 0.5× 4.7k 0.6× 666 0.2× 6.0k 2.6× 1.0k 0.6× 298 9.8k
Paulin Coulibaly Canada 45 4.7k 0.6× 4.7k 0.6× 699 0.2× 4.5k 2.0× 2.2k 1.3× 157 8.4k
Jun Xia China 62 8.8k 1.1× 7.9k 1.1× 1.6k 0.5× 3.8k 1.7× 2.6k 1.5× 528 15.2k
Dawen Yang China 68 9.7k 1.3× 9.0k 1.2× 1.4k 0.4× 2.5k 1.1× 4.5k 2.6× 275 14.9k
Mukand S. Babel Thailand 50 3.6k 0.5× 3.2k 0.4× 1.2k 0.4× 1.6k 0.7× 1.3k 0.8× 205 6.8k
Hamid Moradkhani United States 64 7.2k 0.9× 5.6k 0.7× 692 0.2× 3.4k 1.5× 3.9k 2.3× 219 11.4k
François Anctil Canada 43 4.0k 0.5× 4.3k 0.6× 456 0.1× 3.3k 1.4× 1.9k 1.1× 212 7.4k

Countries citing papers authored by Shenglian Guo

Since Specialization
Citations

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

Fields of papers citing papers by Shenglian Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shenglian Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Shenglian Guo. A scholar is included among the top collaborators of Shenglian Guo 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 Shenglian Guo. Shenglian Guo 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.
Guo, Shenglian, et al.. (2025). Deep learning model for flood probabilistic forecasting considering spatiotemporal rainfall distribution and hydrologic uncertainty. Journal of Hydrology. 655. 132879–132879. 4 indexed citations
3.
Zhou, Yanlai, et al.. (2024). Compromising power generation and flood control: Optimizing flood operating water levels in mega reservoirs. Sustainable Energy Technologies and Assessments. 70. 103963–103963. 3 indexed citations
4.
Zhou, Yanlai, et al.. (2024). Sustainable energy integration: Enhancing the complementary operation of pumped-storage power and hydropower systems. Renewable and Sustainable Energy Reviews. 210. 115175–115175. 11 indexed citations
5.
Guo, Shenglian, et al.. (2024). Improving flood forecast accuracy based on explainable convolutional neural network by Grad-CAM method. Journal of Hydrology. 642. 131867–131867. 12 indexed citations
6.
Guo, Shenglian, et al.. (2024). Flood Season Division Using Statistical Analysis Methods and Verifying by Regional Rainy Characteristics. Water. 16(24). 3677–3677. 1 indexed citations
7.
Zhou, Yanlai, et al.. (2024). Exploring a spatiotemporal hetero graph-based long short-term memory model for multi-step-ahead flood forecasting. Journal of Hydrology. 633. 130937–130937. 13 indexed citations
8.
Xiong, Jinghua, Abhishek Abhishek, Chong Zhang, et al.. (2024). Comparing evaporation from water balance framework and multiple models on a global scale. Journal of Hydrology. 643. 131924–131924.
9.
Guo, Shenglian, et al.. (2024). A novel multi-scale standardized index analyzing monthly to sub-seasonal drought-flood abrupt alternation events in the Yangtze River basin. Journal of Hydrology. 633. 130999–130999. 15 indexed citations
10.
Cui, Zhen, Shenglian Guo, Yanlai Zhou, & Jun Wang. (2023). Exploration of dual-attention mechanism-based deep learning for multi-step-ahead flood probabilistic forecasting. Journal of Hydrology. 622. 129688–129688. 23 indexed citations
11.
Liu, Dedi, Yadong Mei, Shenglian Guo, et al.. (2023). A Nonlinear Model for Evaluating Dynamic Resilience of Water Supply Hydropower Generation‐Environment Conservation Nexus System. Water Resources Research. 59(11). 1 indexed citations
12.
13.
Yin, Jiabo, et al.. (2022). Global Increases in Lethal Compound Heat Stress: Hydrological Drought Hazards Under Climate Change. Geophysical Research Letters. 49(18). 86 indexed citations
14.
Hong, Xingjun, Shenglian Guo, Guiya Chen, Na Guo, & Cong Jiang. (2022). A Modified Two-Parameter Monthly Water Balance Model for Runoff Simulation to Assess Hydrological Drought. Water. 14(22). 3715–3715. 5 indexed citations
15.
Guo, Shenglian, et al.. (2021). Nonstationary Design Flood Estimation in Response to Climate Change, Population Growth and Cascade Reservoir Regulation. Water. 13(19). 2687–2687. 10 indexed citations
16.
Yin, Jiabo, Shenglian Guo, Lei Gu, et al.. (2020). Blending multi-satellite, atmospheric reanalysis and gauge precipitation products to facilitate hydrological modelling. Journal of Hydrology. 593. 125878–125878. 88 indexed citations
17.
Chen, Hua, et al.. (2020). Temporal and spatial transferabilities of hydrological models under different climates and underlying surface conditions. Journal of Hydrology. 591. 125276–125276. 33 indexed citations
18.
Xiong, Feng, Shenglian Guo, Chong‐Yu Xu, et al.. (2019). A general framework of design flood estimation for cascade reservoirs in operation period. Journal of Hydrology. 577. 124003–124003. 31 indexed citations
19.
Wang, Yun, Shenglian Guo, Guang Yang, Xingjun Hong, & Ting Hu. (2014). Optimal early refill rules for Danjiangkou Reservoir. SHILAP Revista de lepidopterología. 13 indexed citations
20.
Liu, Pan, Shenglian Guo, Lihua Xiong, & Chen Lü. (2010). Flood season segmentation based on the probability change-point analysis technique. Hydrological Sciences Journal. 55(4). 540–554. 36 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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