| Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four … T Kim, T Yang, S Gao, L Zhang, Z Ding, X Wen, JJ Gourley, Y Hong Journal of Hydrology 598, 126423, 2021 | 115 | 2021 |
| Identification of relationships between climate indices and long-term precipitation in South Korea using ensemble empirical mode decomposition T Kim, JY Shin, S Kim, JH Heo Journal of Hydrology 557, 726-739, 2018 | 60 | 2018 |
| Spatial and temporal variations in rainfall erosivity and erosivity density in South Korea JY Shin, T Kim, JH Heo, JH Lee Catena 176, 125-144, 2019 | 53 | 2019 |
| Flood frequency analysis for the annual peak flows simulated by an event-based rainfall-runoff model in an urban drainage basin J Ahn, W Cho, T Kim, H Shin, JH Heo Water 6 (12), 3841-3863, 2014 | 50 | 2014 |
| A large-scale comparison of Artificial Intelligence and Data Mining (AI&DM) techniques in simulating reservoir releases over the Upper Colorado Region T Yang, L Zhang, T Kim, Y Hong, D Zhang, Q Peng Journal of Hydrology 602, 126723, 2021 | 49 | 2021 |
| The use of large-scale climate indices in monthly reservoir inflow forecasting and its application on time series and artificial intelligence models T Kim, JY Shin, H Kim, S Kim, JH Heo Water 11 (2), 374, 2019 | 45 | 2019 |
| Evaluation of Subseasonal-to-Seasonal (S2S) precipitation forecast from the North American Multi-Model ensemble phase II (NMME-2) over the contiguous US L Zhang, T Kim, T Yang, Y Hong, Q Zhu Journal of Hydrology 603, 127058, 2021 | 41 | 2021 |
| Ensemble‐Based Neural Network Modeling for Hydrologic Forecasts: Addressing Uncertainty in the Model Structure and Input Variable Selection T Kim, JY Shin, H Kim, JH Heo Water Resources Research 56 (6), e2019WR026262, 2020 | 30 | 2020 |
| Near real-time hurricane rainfall forecasting using convolutional neural network models with Integrated Multi-satellitE Retrievals for GPM (IMERG) product T Kim, T Yang, L Zhang, Y Hong Atmospheric Research 270, 106037, 2022 | 29 | 2022 |
| Regional frequency analysis of extreme precipitation based on a nonstationary population index flood method H Kim, JY Shin, T Kim, S Kim, JH Heo Advances in Water Resources 146, 103757, 2020 | 20 | 2020 |
| Future inflow simulation considering the uncertainties of TFN model and GCMs on Chungju dam basin J Park, JH Kwon, T Kim, JH Heo Journal of Korea Water Resources Association 47 (2), 135-143, 2014 | 10 | 2014 |
| Evaluation of CMIP6 HighResMIP for hydrologic modeling of annual maximum discharge in Iowa AT Michalek, G Villarini, T Kim, F Quintero, WF Krajewski, E Scoccimarro Water Resources Research, e2022WR034166, 2023 | 8 | 2023 |
| Improvement of Extreme Value Modeling for Extreme Rainfall Using Large-Scale Climate Modes and Considering Model Uncertainty H Kim, T Kim, JY Shin, JH Heo Water 14 (3), 478, 2022 | 8 | 2022 |
| A study on a tendency of parameters for nonstationary distribution using ensemble empirical mode decomposition method H Kim, T Kim, H Shin, JH Heo Journal of Korea Water Resources Association 50 (4), 253-261, 2017 | 6 | 2017 |
| A study on the predictive power improvement of time series model with empirical mode decomposition method T Kim, H Shin, W Nam, JH Heo Journal of Korea Water Resources Association 48 (12), 981-993, 2015 | 5 | 2015 |
| Understanding the impact of precipitation bias‐correction and statistical downscaling methods on projected changes in flood extremes AT Michalek, G Villarini, T Kim Earth's Future 12 (3), e2023EF004179, 2024 | 4 | 2024 |
| Disentangling the sources of uncertainties in the projection of flood risk across the central United States (Iowa) AT Michalek, G Villarini, T Kim, F Quintero, WF Krajewski Geophysical Research Letters 50 (22), e2023GL105852, 2023 | 4 | 2023 |
| Projected changes in daily precipitation, temperature and wet‐bulb temperature across Arizona using statistically downscaled CMIP6 climate models T Kim, G Villarini International Journal of Climatology 44 (6), 1994–2010, 2024 | 3 | 2024 |
| A Study on Empirical Distribution Function with Unknown Shape Parameter and Extreme Value Weight for Three Parameter Weibull Distribution T Kim, H Shin, JH Heo Journal of Korea Water Resources Association 46 (6), 643-653, 2013 | 1 | 2013 |
| Dominant sources of uncertainty for downscaled climate: A military installation perspective T Kim, G Villarini, JM Done, DR Johnson, AF Prein, C Wang Journal of Geophysical Research: Atmospheres 129 (12), e2024JD040935, 2024 | | 2024 |
Jun-Haeng HeoYonsei University Civil and Environmental EngineeringE-mail confirmado em yonsei.ac.kr