Location
219 EWRE
Phone
- VNU University of Science (Hanoi, Vietnam) Hydrology Bachelor 2009-2014
- University of Ulsan (Ulsan, South Korea) Hydrology Ph.D. 2018-2022
- Ensemble (urban) Flood/Drought Forecasting
- Uncertainty Quantification, Data Assimilation, Optimization
- Modeling and Developing a fully coupled numerical model
- Artificial Intelligence, Machine Learning, Surrogate Modeling
- Climate Change, Downscaling, and Future projection of extremes at global and local scales
- Geomorphic/Climate internal variability and scale-dependent controls of hydrologic response
- Erosion and sediment transport
- Dam safety
- Tran, V. N., & Kim, J. (2022), Robust and Efficient Uncertainty Quantification for Extreme Events that Deviate Significantly from the Training Dataset Using Polynomial Chaos-Kriging, Journal of Hydrology, 609, 127716. https://doi.org/10.1016/j.jhydrol.2022.127716
- Tran, V. N., & Kim, J. (2021). A robust surrogate data assimilation approach to real-time forecasting using polynomial chaos expansion. Journal of Hydrology, 598, 126367. https://doi.org/10.1016/j.jhydrol.2021.126367
- Ivanov, V. Y., Xu, D., Dwelle, M. C., Sargsyan, K., Wright, D. B., Katopodes, N., Kim, J., Tran, V. N., Warnock, A., Fatichi, S., Burlando, P., Caporali, E., Restrepo, P., Sanders, B. F., Chaney, M. M., Nunes, A. M. B., Nardi, F., Vivoni, E. R., Istanbulluoglu, E., . . . Bras, R. L. (2021). Breaking Down the Computational Barriers to Real-Time Urban Flood Forecasting. Geophysical Research Letters, 48(20), e2021GL093585.
- Tran, T. D., Tran, V. N., & Kim, J. (2021). Improving the Accuracy of Dam Inflow Predictions Using a Long Short-Term Memory Network Coupled with Wavelet Transform and Predictor Selection. Mathematics, 9(5), 551. https://doi.org/10.3390/math9050551
- Tran, V. N., & Kim, J. (2021). Toward an Efficient Uncertainty Quantification of Streamflow Predictions Using Sparse Polynomial Chaos Expansion. Water, 13(2), 203. https://doi.org/10.3390/w13020203
- Tran, V. N., Dwelle, M. C., Sargsyan, K., Ivanov, V. Y., & Kim, J. (2020). A Novel Modeling Framework for Computationally Efficient and Accurate Real-Time Ensemble Flood Forecasting With Uncertainty Quantification. Water Resources Research, 56(3), e2019WR025727. https://doi.org/10.1029/2019wr025727
- Tran, V. N., & Kim, J. (2019). Quantification of predictive uncertainty with a metamodel: toward more efficient hydrologic simulations. Stochastic Environmental Research and Risk Assessment, 33(7), 1453-1476. https://doi.org/10.1007/s00477-019-01703-0