Sangwoo Kim
Focus: Hydrologic and Environmental Modeling; Salinity Intrusion; Drought and Flood Forecasting; Land–Atmosphere Interactions; Remote Sensing and Soil Moisture Inversion; Agricultural Water Management
Sangwoo's research focuses on understanding and modeling hydrologic and environmental processes, particularly the dynamics of salinity intrusion in coastal regions under drought and flood conditions. He integrates land–atmosphere interactions, remote sensing data, and process-based hydrological models to assess drought severity, forecast extreme events, and support sustainable water and agricultural management. His work also involves developing inverse modeling and downscaling techniques to estimate soil hydraulic properties and improve near-surface water balance assessments across spatial and temporal scales.
Chun, B., Lee, T., Kim, S., Lim, K., Jung, Y., Do, J. and Shin, Y. 2022. Estimation of Optimal
Training Period for the Deep-Learning LSTM Model to Forecast CMIP5-based Streamflow. Journal
of The Korean Society of Agricultural Engineers, 64(1), 39-50.