Sungwon Kim
Impact in
- Environmental Engineering top 0.2%
- Hydrological Forecasting Using AI
- Water Science and Technology top 0.5%
- Hydrology and Watershed Management Studies
- Water Quality Monitoring Technologies
Papers in
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- Hydrological Forecasting Using AI 86
-
- Hydrology and Watershed Management Studies 30
- Water Quality Monitoring Technologies 21
- Co-authors
- Özgür Kişi (43 shared papers)Vijay P. Singh (24 shared papers)Youngmin Seo (22 shared papers)Meysam Alizamir (24 shared papers)Jalal Shiri (12 shared papers)Hung Soo Kim (4 shared papers)Mohammad Zounemat‐Kermani (20 shared papers)Salim Heddam (39 shared papers)
- Journals
- Water Resources Management (8 papers)Water (6 papers)Hydrology research (4 papers)PLoS ONE (4 papers)Scientific Reports (4 papers)
- Partner nations
- South KoreaIranAlgeria
In The Last Decade
Sungwon Kim
130 papers receiving 4.0k citations
Sungwon Kim's Hit Papers
Peers
Comparison fields: 5 of 127
- Environmental Engineering 2.4k
- Water Science and Technology 1.5k
- Global and Planetary Change 1.3k
- Artificial Intelligence 881
- Waste Management and Disposal 207
Countries citing papers authored by Sungwon Kim
This map shows the geographic impact of Sungwon Kim'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 Sungwon Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sungwon Kim more than expected).
Fields of papers citing papers by Sungwon Kim
This network shows the impact of papers produced by Sungwon Kim. 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 Sungwon Kim. The network helps show where Sungwon Kim may publish in the future.
Co-authors
The 25 scholars most cited alongside Sungwon Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 143 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Groundwater level prediction using machine learning models: A comprehensive review Hit paper breakdown → | 2022 | 286 |
| 2 | 2014 | 257 | |
| 3 | 2007 | 206 | |
| 4 | 2020 | 130 | |
| 5 | 2018 | 112 | |
| 6 | 2019 | 105 | |
| 7 | 2020 | 101 | |
| 8 | 2020 | 101 | |
| 9 | 2019 | 98 | |
| 10 | 2020 | 98 | |
| 11 | 2014 | 86 | |
| 12 | 2012 | 84 | |
| 13 | 2008 | 80 | |
| 14 | 2023 | 76 | |
| 15 | 2013 | 76 | |
| 16 | 2019 | 75 | |
| 17 | 2020 | 69 | |
| 18 | 2012 | 69 | |
| 19 | 2018 | 67 | |
| 20 | 2020 | 59 |
About Sungwon Kim
Sungwon Kim is a scholar working on Environmental Engineering, Water Science and Technology, Global and Planetary Change, Artificial Intelligence and Atmospheric Science, having authored 143 papers that have together received 4.1k indexed citations. Recurring topics across this work include Hydrological Forecasting Using AI (86 papers), Energy Load and Power Forecasting (31 papers), Hydrology and Watershed Management Studies (30 papers), Water Quality Monitoring Technologies (21 papers), Machine Learning and ELM (14 papers), Plant Water Relations and Carbon Dynamics (14 papers), Solar Radiation and Photovoltaics (14 papers) and Flood Risk Assessment and Management (12 papers). The work is most often cited by research in Environmental Engineering (2.4k citations), Water Science and Technology (1.5k citations), Global and Planetary Change (1.3k citations), Artificial Intelligence (881 citations) and Waste Management and Disposal (207 citations). Sungwon Kim has collaborated with scholars based in South Korea, Iran and Algeria. Frequent co-authors include Özgür Kişi, Vijay P. Singh, Youngmin Seo, Meysam Alizamir, Jalal Shiri, Hung Soo Kim, Mohammad Zounemat‐Kermani, Salim Heddam, Zaher Mundher Yaseen and Mohammad Ali Ghorbani. Their work appears in journals such as Water Resources Management, Water, Hydrology research, PLoS ONE and Scientific Reports.
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.