Daehyok Shin
- Global and Planetary Change top 10%
- Water Science and Technology top 10%
- Environmental Engineering
- Atmospheric Science
- Ecology, Evolution, Behavior and Systematics
- Co-authors
- Guillermo A. BaigorriaJames W. JonesAshok MishraNarendra TutejaJ. J. O’BrienDavid M. KentMA BariDmitri Kavetski
- Topics
- Hydrology and Watershed Management Studies (9 papers)Flood Risk Assessment and Management (5 papers)Hydrological Forecasting Using AI (4 papers)
- Journals
- Hydrology and earth system sciencesJAWRA Journal of the American Water Resources AssociationClimate Research
- Partner nations
- AustraliaUnited States
In The Last Decade
Daehyok Shin
10 papers receiving 256 citations
Peers
Comparison fields: 5 of 29
- Global and Planetary Change 215
- Water Science and Technology 155
- Environmental Engineering 52
- Atmospheric Science 50
- Ecology, Evolution, Behavior and Systematics 40
Countries citing papers authored by Daehyok Shin
This map shows the geographic impact of Daehyok Shin'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 Daehyok Shin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daehyok Shin more than expected).
Fields of papers citing papers by Daehyok Shin
This network shows the impact of papers produced by Daehyok Shin. 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 Daehyok Shin. The network helps show where Daehyok Shin may publish in the future.
Co-authorship network of co-authors of Daehyok Shin
This figure shows the co-authorship network connecting the top 25 collaborators of Daehyok Shin. A scholar is included among the top collaborators of Daehyok Shin 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 Daehyok Shin. Daehyok Shin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 39 | |
| 3 | 93 | |
| 4 | Dynamic streamflow forecasts within an uncertainty framework for 100 catchments in Australia | 1 |
| 5 | Hydrologic reference stations to monitor climate-driven streamflow variability and trends | 13 |
| 6 | 3 | |
| 7 | 1 | |
| 8 | Experimental evaluation of the dynamic seasonal streamflow forecasting approach | 12 |
| 9 | 84 | |
| 10 | 6 |
About Daehyok Shin
Daehyok Shin is a scholar working on Water Science and Technology, Environmental Engineering and Global and Planetary Change, having authored 10 papers that have together received 260 indexed citations. Recurring topics across this work include Hydrology and Watershed Management Studies (9 papers), Flood Risk Assessment and Management (5 papers) and Hydrological Forecasting Using AI (4 papers). The work is most often cited by research in Water Science and Technology (155 citations), Global and Planetary Change (215 citations) and Environmental Engineering (52 citations). Daehyok Shin has collaborated with scholars based in Australia and United States. Frequent co-authors include Guillermo A. Baigorria, James W. Jones, Ashok Mishra, Narendra Tuteja, J. J. O’Brien, David M. Kent, MA Bari, Dmitri Kavetski, Fitsum Woldemeskel and David McInerney. Their work appears in journals such as Hydrology and earth system sciences, JAWRA Journal of the American Water Resources Association and Climate Research.
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.