Sungho Jung

1.3k total citations · 1 hit paper
13 papers, 929 citations indexed

About

Sungho Jung is a scholar working on Water Science and Technology, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, Sungho Jung has authored 13 papers receiving a total of 929 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Water Science and Technology, 9 papers in Environmental Engineering and 9 papers in Global and Planetary Change. Recurrent topics in Sungho Jung's work include Hydrology and Watershed Management Studies (10 papers), Flood Risk Assessment and Management (8 papers) and Hydrological Forecasting Using AI (7 papers). Sungho Jung is often cited by papers focused on Hydrology and Watershed Management Studies (10 papers), Flood Risk Assessment and Management (8 papers) and Hydrological Forecasting Using AI (7 papers). Sungho Jung collaborates with scholars based in South Korea, Vietnam and Canada. Sungho Jung's co-authors include Giha Lee, Xuan-Hien Le, Duc Hai Nguyen, Giang V. Nguyen, Seong-Won Kim, Đoàn Văn Bình, Younghun Kim, Hyunuk An and Hongjoon Shin and has published in prestigious journals such as Journal of Hydrology, IEEE Access and Remote Sensing.

In The Last Decade

Sungho Jung

13 papers receiving 883 citations

Hit Papers

Application of Long Short... 2019 2026 2021 2023 2019 200 400 600
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. Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting
    2019 614 citations Xuan-Hien Le, Giha Lee et al. Water profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Sungho Jung 541 448 408 170 130 13 929
I-Feng Kao 776 1.4× 427 1.0× 381 0.9× 165 1.0× 97 0.7× 9 1.0k
Xuan-Hien Le 599 1.1× 532 1.2× 470 1.2× 250 1.5× 145 1.1× 34 1.2k
Seyed Mostafa Biazar 424 0.8× 341 0.8× 232 0.6× 108 0.6× 143 1.1× 22 784
Özlem Terzi 727 1.3× 427 1.0× 430 1.1× 159 0.9× 159 1.2× 45 1.0k
Youngmin Seo 589 1.1× 281 0.6× 389 1.0× 85 0.5× 147 1.1× 38 878
Pouya Aghelpour 478 0.9× 439 1.0× 262 0.6× 73 0.4× 97 0.7× 27 791
Ju‐Young Shin 423 0.8× 429 1.0× 234 0.6× 217 1.3× 70 0.5× 42 1.0k
Vahid Karimi 514 1.0× 266 0.6× 317 0.8× 75 0.4× 102 0.8× 21 808
Doudja Souag-Gamane 581 1.1× 557 1.2× 451 1.1× 77 0.5× 157 1.2× 17 1.0k

Countries citing papers authored by Sungho Jung

Since Specialization
Citations

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

Fields of papers citing papers by Sungho Jung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sungho Jung

This figure shows the co-authorship network connecting the top 25 collaborators of Sungho Jung. A scholar is included among the top collaborators of Sungho Jung 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 Sungho Jung. Sungho Jung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Le, Xuan-Hien, Younghun Kim, Đoàn Văn Bình, et al.. (2024). Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks. Journal of Hydrology. 630. 130762–130762. 20 indexed citations
2.
Le, Xuan-Hien, et al.. (2023). Towards an efficient streamflow forecasting method for event-scales in Ca River basin, Vietnam. Journal of Hydrology Regional Studies. 46. 101328–101328. 11 indexed citations
3.
Le, Xuan-Hien, Duc Hai Nguyen, Sungho Jung, & Giha Lee. (2023). Deep neural network-based discharge prediction for upstream hydrological stations: a comparative study. Earth Science Informatics. 16(4). 3113–3124. 8 indexed citations
4.
Le, Xuan-Hien, et al.. (2023). Comparison of bias-corrected multisatellite precipitation products by deep learning framework. International Journal of Applied Earth Observation and Geoinformation. 116. 103177–103177. 24 indexed citations
5.
Nguyen, Giang V., et al.. (2023). Machine learning approaches for reconstructing gridded precipitation based on multiple source products. Journal of Hydrology Regional Studies. 48. 101475–101475. 12 indexed citations
6.
Le, Xuan-Hien, et al.. (2021). Investigating Behavior of Six Methods for Sediment Transport Capacity Estimation of Spatial-Temporal Soil Erosion. Water. 13(21). 3054–3054. 4 indexed citations
7.
Le, Xuan-Hien, et al.. (2021). Comparison of Deep Learning Techniques for River Streamflow Forecasting. IEEE Access. 9. 71805–71820. 116 indexed citations
8.
Nguyen, Giang V., et al.. (2021). Application of Random Forest Algorithm for Merging Multiple Satellite Precipitation Products across South Korea. Remote Sensing. 13(20). 4033–4033. 46 indexed citations
9.
Kim, Seong-Won, et al.. (2021). Analysis of Net Erosion Using a Physics-Based Erosion Model for the Doam Dam Basin in Korea. Water. 13(19). 2663–2663. 3 indexed citations
10.
Lee, Giha, et al.. (2020). Future Runoff Analysis in the Mekong River Basin under a Climate Change Scenario Using Deep Learning. Water. 12(6). 1556–1556. 31 indexed citations
11.
Le, Xuan-Hien, et al.. (2019). Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting. Water. 11(7). 1387–1387. 614 indexed citations breakdown →
12.
Jung, Sungho. (2018). Prediction of water level in a tidal river using a deep-learning based LSTM model. Journal of Korea Water Resources Association. 51(12). 1207–1216. 23 indexed citations
13.
Jung, Sungho, et al.. (2017). Prediction of River Water Level Using Deep-Learning Open Library. Korean Society of Hazard Mitigation. 18(1). 1–11. 17 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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