Xuan-Hien Le***, N Koyama, and T Yamada (2025). Impacts of Elevation Bias and Topographic Uncertainty on Flood Modeling: Model Robustness and Floodplain Sensitivity Mapping in a Lowland River Basin. Journal of Hydrology, 666, 134832. https://doi.org/10.1016/j.jhydrol.2025.134832

Xuan-Hien Le***, DV Binh, and G Lee (2025). Performance and uncertainty analysis in deep learning frameworks for streamflow forecasting via Monte Carlo dropout technique. Journal of Hydrology: Regional Studies 61, 102668. https://doi.org/10.1016/j.ejrh.2025.102668

Xuan-Hien Le***, N Koyama, K Kikuchi, Y Yamanouchi, A Fukaya, and T Yamada (2025). Evaluating Geostatistical and Statistical Merging Methods for Radar–Gauge Rainfall Integration: A Multi-Method Comparative Study. Remote Sensing 17(15), 2622. https://doi.org/10.3390/rs17152622

Xuan-Hien Le and LTT Hien (2025). Integrating machine learning and empirical approaches for scour depth estimation at sluice gates: evaluating tree-based models, hyperparameter tuning, and proposing new formulas. Journal of Hydrology and Hydromechanics 73(1), 51-64. https://doi.org/10.2478/johh-2025-0004

OS Huong, Xuan-Hien Le, VL Nguyen, G Lee, and T Sok (2025). Convolutional Neural Networks-Driven Bias Correction of Satellite Precipitation Improves Rainfall-Runoff-Inundation Modeling. International Soil and Water Conservation, 14 (1), 100571. https://doi.org/10.1016/j.iswcr.2025.09.003

LTT Hien, NV Chien, and Xuan-Hien Le (2025). Integrating numerical and regression methods for estimating discharge coefficients of intake structures with wingwalls in irrigation networks. Flow Measurement and Instrumentation 106, 102989. https://doi.org/10.1016/j.flowmeasinst.2025.102989

DV Binh, NQ Binh, NTT Ha, Xuan-Hien Le, et. al. (2025). Quantifying the Impacts of Climate Change and Human Interventions on Flow Alterations in a Tropical River. Water Resources Management 39, 3537–3552. https://doi.org/10.1007/s11269-025-04121-w

Xuan-Hien Le***, Y Kim, DV Binh, S Jung, DH Nguyen and G Lee (2024). Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks. Journal of Hydrology 630, 130762. https://doi.org/10.1016/j.jhydrol.2024.130762

Xuan-Hien Le***, LTT Hien, HV Ho. and G Lee (2024). Benchmarking the performance and uncertainty of machine learning models in estimating scour depth at sluice outlets. Journal of Hydroinformatics 26(7), 1572-1588. https://doi.org/10.2166/hydro.2024.297

Xuan-Hien Le, Huynh T. T., Song M. and Lee G. (2024). Quantifying Predictive Uncertainty and Feature Selection in River Bed Load Estimation: A Multi-Model Machine Learning Approach with Particle Swarm Optimization. Water 16(14), 1945. https://doi.org/10.3390/w16141945

Xuan-Hien Le, Choi C., Eu S., Yeon M. and Lee G. (2024). Quantitative evaluation of uncertainty and interpretability in machine learning-based landslide susceptibility mapping through feature selection and explainable AI. Frontiers in Environmental Science 12, 1424988. https://doi.org/10.3389/fenvs.2024.1424988

Xuan-Hien Le and LTT Hien (2024). Predicting maximum scour depth at sluice outlet: a comparative study of machine learning models and empirical equations. Environmental Research Communications 6(1), 015010. https://doi.org/10.1088/2515-7620/ad1f94

LTT Hien, NV Chien, and Xuan-Hien Le. (2024). Advanced hybrid techniques for predicting discharge coefficients in ogee-crested spillways: integrating physical, numerical, and machine learning models. Environmental Research Communications 6(11), 115002. https://doi.org/10.1088/2515-7620/ad8a24

TTM Do, VL Nguyen, Xuan-Hien Le, VG Nguyen, M Yeon, and G Lee (2024). National variability in soil organic carbon stock predictions: Impact of bulk density pedotransfer functions. International Soil and Water Conservation Research 12(4), 868-884. https://doi.org/10.1016/j.iswcr.2024.04.002

Xuan-Hien Le, DH Nguyen, and G Lee (2023). Performance Comparison of Bias-Corrected Satellite Precipitation Products by Various Deep Learning Schemes. IEEE Transactions on Geoscience and Remote Sensing 61, 1-12. https://doi.org/10.1109/TGRS.2023.3299234

Xuan-Hien Le, S Eu, C Choi, DH Nguyen, M Yeon, and G Lee (2023). Machine learning for high-resolution landslide susceptibility mapping: case study in Inje County, South Korea. Frontiers in Earth Science 11. https://doi.org/10.3389/feart.2023.1268501

Xuan-Hien Le, VL Nguyen, DH Nguyen, VG Nguyen, S Jung, and G Lee (2023). Comparison of bias-corrected multisatellite precipitation products by deep learning framework. International Journal of Applied Earth Observation and Geoinformation 116, 103177. https://doi.org/10.1016/j.jag.2022.103177

Xuan-Hien Le, VL Nguyen, VG Nguyen, DH Nguyen, S Jung, and G Lee (2023). Towards an efficient streamflow forecasting method for event-scales in Ca River basin, Vietnam. Journal of Hydrology: Regional Studies 46, 101328. https://doi.org/10.1016/j.ejrh.2023.101328

Xuan-Hien Le***, DH Nguyen, S Jung, and G Lee (2023). Deep neural network-based discharge prediction for upstream hydrological stations: a comparative study. Earth Science Informatics 16, 3113–3124. https://doi.org/10.1007/s12145-023-01082-9

G Lee, DH Nguyen, and Xuan-Hien Le*** (2023). A Novel Framework for Correcting Satellite-Based Precipitation Products for Watersheds with Discontinuous Observed Data, Case Study in Mekong River Basin. Remote Sensing 15(3), 630. https://doi.org/10.3390/rs15030630

NT Trung, Xuan-Hien Le***, and TM Tuan (2023). Enhancing Contrast of Dark Satellite Images Based on Fuzzy Semi-Supervised Clustering and an Enhancement Operator. Remote Sensing 15(6), 1645. https://doi.org/10.3390/rs15061645

VL Nguyen, Xuan-Hien Le, VG Nguyen, M Yeon, TTM Do, and G Lee (2023). Evaluation of Numerous Kinetic Energy-Rainfall Intensity Equations Using Disdrometer Data. Remote Sensing 15(1), 156. https://doi.org/10.3390/rs15010156

VG Nguyen, Xuan-Hien Le, VL Nguyen, TTM Do, S Jung, and G Lee (2023). Machine learning approaches for reconstructing gridded precipitation based on multiple source products. Journal of Hydrology: Regional Studies 48, 101475. https://doi.org/10.1016/j.ejrh.2023.101475

HV Ho, DH Nguyen, Xuan-Hien Le***, and G Lee (2022). Multi-step-ahead water level forecasting for operating sluice gates in Hai Duong, Vietnam. Environmental Monitoring and Assessment 194(6), 442. https://doi.org/10.1007/s10661-022-10115-7

DH Nguyen, Xuan-Hien Le, DT Anh, SH Kim, and DH Bae (2022). Hourly streamflow forecasting using a Bayesian additive regression tree model hybridized with a genetic algorithm. Journal of Hydrology 606, 127445. https://doi.org/10.1016/j.jhydrol.2022.127445

Tuyen D. N., Tuan T. M., Xuan-Hien Le Tung N. T., Chau T. K., Van Hai P., Gerogiannis V. C. and Son L. H. (2022). RainPredRNN: A New Approach for Precipitation Nowcasting with Weather Radar Echo Images Based on Deep Learning. Axioms 11(3), 107. https://doi.org/10.3390/axioms11030107

VL Nguyen, Xuan-Hien Le, VG Nguyen, M Yeon, TTM Do, and G Lee (2022). Comprehensive relationships between kinetic energy and rainfall intensity based on precipitation measurements from an OTT Parsivel2 optical disdrometer. Frontiers in Environmental Science 10. https://doi.org/10.3389/fenvs.2022.985516

Xuan-Hien Le, DH Nguyen, S Jung, M Yeon, and G Lee (2021). Comparison of Deep Learning Techniques for River Streamflow Forecasting. IEEE Access 9, 71805-71820. https://doi.org/10.1109/ACCESS.2021.3077703

DH Nguyen, Xuan-Hien Le, JY Heo, and DH Bae (2021). Development of an Extreme Gradient Boosting Model Integrated With Evolutionary Algorithms for Hourly Water Level Prediction. IEEE Access 9, 125853-125867. https://doi.org/10.1109/ACCESS.2021.3111287

VG Nguyen, Xuan-Hien Le, VL Nguyen, S Jung, M Yeon, and G Lee (2021). Application of Random Forest Algorithm for Merging Multiple Satellite Precipitation Products across South Korea. Remote Sensing 13(20), 4033. https://doi.org/10.3390/rs13204033

VL Nguyen, Xuan-Hien Le, VG Nguyen, M Yeon, S Jung, and G Lee. (2021). Investigating Behavior of Six Methods for Sediment Transport Capacity Estimation of Spatial-Temporal Soil Erosion. Water 13(21), 3054. https://doi.org/10.3390/w13213054

Xuan-Hien Le, G Lee, K Jung, H An, S Lee, and Y Jung (2020). Application of Convolutional Neural Network for Spatiotemporal Bias Correction of Daily Satellite-Based Precipitation. Remote Sensing 12(17), 2731. https://doi.org/10.3390/rs12172731

Xuan-Hien Le, HV Ho, G Lee, and S Jung (2019). Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting. Water 11(7), 1387. https://doi.org/10.3390/w11071387

Xuan-Hien Le, HV Ho, and G Lee (2019). River streamflow prediction using a deep neural network: a case study on the Red River, Vietnam. Korean Journal of Agricultural Science 46(4), 843-856. https://doi.org/10.7744/kjoas.20190068

Xuan-Hien Le***, N Koyama, and T Yamada. Continual Deep Learning Framework for Spatiotemporal Radar Rainfall Bias Correction and Data Assimilation in Data-Scarce Regions. Submitted to Journal of Hydrology

S Jung, Xuan-Hien Le, GV Nguyen, D Lee, and G Lee. Rainfall-Runoff Modeling Using Bias-Corrected Near-Real-Time Satellite Precipitation Products by Machine Learning Technique. Submitted to Journal of Hydrology: Regional Study

GB Alena, Xuan-Hien Le, Linh NV and G Lee. Machine learning approach for flood susceptibility mapping in the Amazon River basin using explainable AI. Submitted to Hydrological Sciences Journal. 

DX Khanh and Xuan-Hien Le. Enhancing Floodwater Depth Mapping in Tropical Regions Using Multi-Temporal Sentinel-1 SAR, Supervised Classification, and Multi-DEM Sensitivity Analysis. Submitted to Environmental Research Communications.

(Scopus indexed) G. V. Nguyen, Xuan-Hien Le, L.N. Van, S. Jung, C. Choi, G. Lee (2023). Evaluating the performance of light gradient boosting machine in merging multiple satellite precipitation products over South Korea. Lecture Notes in Civil Engineering, Vol. 344, The 4th International Conference on Sustainability in Civil Engineering.  https://doi.org/10.1007/978-981-99-2345-8_52 

(Scopus indexed) L.N. Van, Xuan-Hien Le, G.V. Nguyen, M. Yeon, Y. Kim, G. Lee (2023). Use of Disdrometer Dataset to Detect Kinetic Energy Expenditure and Rainfall Intensity Relationships, Lecture Notes in Civil Engineering, Vol. 344, The 4th International Conference on Sustainability in Civil Engineering.. https://doi.org/10.1007/978-981-99-2345-8_51 

(Scopus indexed) Xuan-Hien Le, S. Jung, M. Yeon, and G. Lee (2021). River Water Level Prediction Based on Deep Learning: Case Study on the Geum River, South Korea. Lecture Notes in Civil Engineering, The 3rd International Conference on Sustainability in Civil Engineering, 319-325. https://doi.org/10.1007/978-981-16-0053-1_40

(Scopus indexed) Xuan-Hien Le, H.V. Ho, and G. Lee (2020). Application of gated recurrent unit (GRU) network for forecasting river water levels affected by tides.  APAC proceedings, The International Conference on Asian and Pacific Coasts (APAC), Hanoi, Vietnam, 673-680. https://doi.org/10.1007/978-981-15-0291-0_92

Xuan-Hien Le, HV. Ho, G. Lee, and S. Jung (2018). A Deep Neural Network Application for Forecasting the Inflow into the Hoa Binh Reservoir in Vietnam. ISLT proceedings, The International Symposium on Lowland Technology (ISLT 2018), Hanoi, Vietnam.