Hyunje Yang

PUBLICATIONS

Preprints

1. Yang, H., Lee, J.W., Lee, W. “Where, When, and How Do Physics-Informed Deep Learning Models Improve Hurricane-Induced Compound Flooding Predictions?” ESS Open Archive, 2026.
   https://doi.org/10.22541/essoar.15005345/v1

Journal Articles

1. Yang, H., Lee, J.W., Santos Cruz, A.U. “Machine Learning-Enhanced Static Flood Models for High-Resolution Peak Storm Surge Inundation Mapping in Southeast Texas, USA” Journal of Hydrology: Regional Studies, 2026, 63: p. 103056.
   https://doi.org/10.1016/j.ejrh.2025.103056
2. Yang, H., Lee, J.W., Klepac, S., Santos Cruz, A.U., Subgranon, A., Jiao, J. “Reconstructing Missing Data of Damaged Buildings From Post-Hurricane Reconnaissance Data Using XGBoost” Frontiers in Built Environment, 2024, 10: p. 1444001.
   https://doi.org/10.3389/fbuil.2024.1444001
3. Yang, H., Lim, H., Moon, H., Li, Q., Nam, S., Choi, B., and Choi, H.T. “Identifying the Minimum Number of Flood Events for Reasonable Flood Peak Prediction of Ungauged Forested Catchments in South Korea” Forests, 2023, 14(6): p. 1131.
   https://doi.org/10.3390/f14061131
4. Nam, S., Yang, H., Lim, H., Kim, J., Li, Q., Moon, H., and Choi, H.T. “Short-Term Effects of Forest Fire on Water Quality Along a Headwater Stream in the Immediate Post-Fire Period” Water, 2023, 15(1): p. 131.
   https://doi.org/10.3390/w15010131
5. Yang, H., Lim, H., Moon, H., Li, Q., Nam, S., Kim, J., and Choi, H.T. “Simple Optimal Sampling Algorithm to Strengthen Digital Soil Mapping Using the Spatial Distribution of Machine Learning Predictive Uncertainty: A Case Study for Field Capacity Prediction” Land, 2022, 11(11): p. 2098.
   https://doi.org/10.3390/land11112098
6. Yang, H., Yoo, H., Lim, H., Kim, J., and Choi, H.T. “Impacts of Soil Properties, Topography, and Environmental Features on Soil Water Holding Capacities (SWHCs) and Their Interrelationship” Land, 2021, 10(12): p. 1290.
   https://doi.org/10.3390/land10121290
7. Lim, H., Yang, H., et al. “Development of Pedo-Transfer Functions for the Saturated Hydraulic Conductivity of Forest Soil in South Korea Considering Forest Stand and Site Characteristics” Water, 2020, 12(8): p. 2217.
   https://doi.org/10.3390/w12082217
8. Yang, H., Choi, H.T., and Lim, H. “Effects of Forest Thinning on the Long-Term Runoff Changes of Coniferous Forest Plantation” Water, 2019, 11(11): p. 2301.
   https://doi.org/10.3390/w11112301
9. Yang, H., Choi, H.T., and Lim, H. “Applicability Assessment of Estimation Methods for Baseflow Recession Constants in Small Forest Catchments” Water, 2018, 10(8): p. 1074.
   https://doi.org/10.3390/w10081074
10. Yang, H., Lee, S., and Im, S. “Hydraulic Relation of Discharge and Velocity in Small, Steep Mountain Streams Using Salt Dilution Method” Journal of Korean Society of Forest Science, 2018, 107(2): p. 158-165.
    https://doi.org/10.14578/jkfs.2018.107.2.158
11. Yang, H., Im, S., Lee, Q., Eu, S., and Lee, E. “Flow Measurement of Mountain Streams using Salt Dilution Method” Journal of the Korean Society of Forest Engineering, 2016, 14(1): p. 1-6.
    https://www.earticle.net/Article/A276485

CONFERENCES PRESENTATIONS

Oral Presentations

1. Yang, H., Lee, J.W., Santos Cruz, A.U., Subgranon, A., Klepac, S.P., Jiao, J. “Can Hurricane, Surge, and Damage Data Assist in Reconstructing Structural Features?” 10th Young Coastal Scientists and Engineers Conference - Americas, Quebec, Canada, Jun. 4-6, 2024.
2. Yang, H., Lee, J.W. “Towards Resilient Texas: Rapid Storm Surge Prediction Using Machine Learning” Planet Texas 2050 Symposium, Texas, USA, Feb. 27-29, 2024.
3. Yang, H., Choi, H.T., and Lim, H. “Estimating Flood Peaks in Ungauged Forested Catchments” Joint Symposium on Forest Science, Seoul, Korea, Feb. 15-16, 2023.
4. Yang, H., Lim, H., Li, Q., Nam, S., Choi, H.T., Kim, J., and Moon, H. “Developing Flash Flood Predictive Model Using LSTM Neural Networks for Mountainous Areas” Proceeding of the International Symposium on Forest Science, Daegu, Korea, Aug. 24-26, 2022.
5. Yang, H., Lim, H., Choi, H.T., and Lee, J. “Development of Throughfall Simulation Models and Prediction Uncertainty Estimation by Different Forest Stand Characteristics” EGU General Assembly 2022, Vienna, Austria, May 23-27, 2022. Online.
6. Yang, H., Lim, H., Choi, H.T., Kim, J., and Nam, S. “Comparing Machine Learning Algorithms for Developing Optimal PTF and DSM Models in South Korea” Joint Symposium on Forest Science, Seoul, Korea, Feb. 9-10, 2022.
7. Yang, H., Lim, H., Choi, H.T., and Kim, J. “Identifying the Characteristics of Forest Water Cycle in Different Forest Stands and Rainfall Events” Proceedings of the International Symposium on Forest Science, Pyeongchang, Korea, Aug. 18-20, 2021. Online.
8. Yang, H., Lim, H., Choi, H.T., and Kim, J. “Estimating the Spatial Distribution of Forest Soil Water Retention using the Machine Learning Model” Joint Symposium on Forest Science, Seoul, Korea, Feb. 17-18, 2021. Online.
9. Yang, H., Choi, H.T., and Lim, H. “Pedo-Transfer Functions (PTFs) Development for the Saturated Hydraulic Conductivity of Forest Soil” Proceedings of the International Symposium on Forest Science, Seoul, Korea, Aug. 19-20, 2020. Online.
10. Yang, H., Choi, H.T., and Lim, H. “Hydraulic Properties of Forest Soils in Different Soil Texture” Proceeding of Summer Meeting of the Korean Society of Forest Science, Seoul, Korea, Aug. 29, 2019.
11. Yang, H., Choi, H.T., and Lim, H. “Effects of Forest Thinning on the Water Yield Increase Based on the Long-term Rainfall and Streamflow Monitoring” Joint Symposium of Forest Science, Jinju, Korea, Feb. 20-21, 2019.
12. Yang, H., Choi, H.T., and Lim, H. “Selection of the Proper Baseflow Recession Constant Estimation Methods for the Reasonable Hydrograph Analysis in Small Forest Catchments” Joint Symposium of Forest Science, Seoul, Korea, Aug. 29-30, 2018.
13. Yang, H., Lee, S., and Im, S. “Development of Estimation Formula for the Mean Stream Velocity in Steep Mountain with Salt-dilution Method” Joint Symposium of Forest Science, Chuncheon, Korea, Feb. 21, 2018.

Poster Presentations

1. Yang, H., Lee, J.W., Lee, W. “Development of a Physics-Informed Deep Learning Model for Hurricane-Induced Compound Flooding Prediction” HydroML 2026, Texas, USA, May 19-21, 2026.
2. Yang, H., Lee, J.W., Lee, W. “Spatiotemporally Heterogeneous Improvements in Compound Flooding Prediction through Physics-Constrained Learning and Their Implications for Coastal Risk” Project SHIELD Workshop, Texas, USA, May 7, 2026.
3. Kim, M., Yang, H., Chowdhury, M.E., Lee, J.W. “Compound Flooding and Power Grid Resilience in Puerto Rico: Evaluating Extreme Forcing Duration using Mixed Hurricane Irma and Maria Scenarios” 2026 Energy Research Poster Competition, Texas, USA, Apr. 6-7, 2026.
4. Yang, H., Lee, J.W., Santos Cruz, A.U. “A Hybrid AI-Driven and Static Flood Modeling for Real-Time Peak Storm Surge Inundation Mapping” American Geophysical Union (AGU) Fall Meeting 2025, Louisiana, USA, Dec. 15-19, 2025.
5. Yang, H., Lee, J.W., Santos Cruz, A.U. “A Hybrid Approach Integrating Machine Learning and Static Flood Models for Efficient Real-Time Peak Storm Surge Inundation Mapping” Artificial Intelligence and Digital Twins for Earth Systems, Texas, USA, Sep. 22-24, 2025.
6. Yang, H., Lee, J.W. “Storm Surge Hazard Estimation for Texas Coastal Areas Using Machine Learning” 2024 CAEE Graduate Symposium, Texas, USA, Feb. 23, 2024.
7. Yang, H., Moon, H., Lim, H., Kim, J., and Choi, H.T. “Expected Amount of Data Accumulation to Develop Reasonable Flash Flood Predictive Models Using Machine Learning Approaches” American Geophysical Union (AGU) Fall Meeting 2022, Illinois, USA, Dec. 12-16, 2022. Online.
8. Yang, H., Lim, H., Choi, H.T., Kim, J., and Nam, S. “A Novel Method for Selecting Priority Soil Sample Sites using Prediction Uncertainty of Machine Learning Model Based on Geospatial Information” Frontiers in Hydrology Meeting 2022, San Juan, Puerto Rico, Jun. 19-24, 2022. Online.
9. Yang, H., Lim, H., Kim, J., and Choi, H.T. “Effects of Soil Topographical Properties on the Forest Soil Field Capacity using Machine Learning Approach” AGU Fall Meeting 2021, Louisiana, USA, Dec. 13-17, 2021. Online.
10. Yang, H. and Im, S. “Salt-dilution Velocity Prediction in Naturalized Channels” SNU and U. of Tokyo Joint Workshop, Seoul, Korea, May 9, 2017.
11. Yang, H. and Im, S. “Flow Measurement of Mountain Rivers using Salt-dilution Method” The 7th International Symposium of the Asian University Forests Consortium, Hokkaido, Japan, Oct. 11-14, 2016.

RESEARCH EXPERIENCE

A Study on the Quantification and Promotion of Forest Water Yield for Sustainable Supply of Freshwater

• Calibrate interest parameters and analyze their uncertainties on physical hydrological simulation model via Bayesian approach and Generalized Likelihood Uncertainty Estimation (GLUE), using in situ measurement of the water cycle in different forest stands.
• Investigated forest stand characteristics and collected soil samples in various forested areas.
• Installed various hydrological instruments and collected in situ datasets via datalogger, water level gauge, sap flow measure, and automatic water sampler.

Estimation of Forest Soil Hydraulic Characteristics Based on the National Scale Forest Geographic Information

• Soil hydraulic characteristics measurement: soil water holding capacities (using pressure plate), hydraulic conductivity, organic matter, and soil texture analysis.
• Soil hydraulic properties prediction and its predictive uncertainty estimation on a national scale based on spatial big dataset and machine learning prediction models.
• Priority sample site selection to strengthen the Digital Soil Mapping (DSM) model for a 10-year national R&D research project using predictive uncertainty.

Long-term Monitoring of the Flow Characteristics in Different Forest Stands and Locations

• Select the optimal sites for water level gauge dams in different forest sites, and survey the sites to install the dam.
• Construction management of the water level gauge dam.
• Collect the long-term water level and meteorological data from 52 sites and compare their hydrological characteristics.
• Evaluate the effect of forest thinning on the forest water cycle changes based on double mass curves and nonparametric statistics.

Development of Forest Water Management Technology to Reduce Nonpoint Source (NPS) Pollution

• Monitor and collect data on changes in water quality after forest fire and forest thinning as the preliminary stage for analysis.

Construction of Big Data and Development of Integrated Utilization System on the Flash Flood in Forest Watershed

• Find the optimal devices and algorithms for the flash flood warning system suited to forested areas.
• Measured in situ stream velocity when a flash flood has occurred.
• Develop flash flood prediction models.

Hydraulic Relation of Discharge and Velocity in Mountain Streams Using the Salt-dilution Method

• Stream velocity and discharge measurement with the salt-dilution method, and developing a model for stream velocity prediction with topographical information and discharge.

BOOKS

Choi, H.T., Kim, J., Lim, H., and Yang, H. Standard Manual for Developing Forest Soil Water Map. National Institute of Forest Science: Seoul, South Korea, 2021.
ISBN: 9791160195859

Choi, H.T., Kim, J., Lim, H., Yang, H., and Yoo, H. Long-term Monitoring of Forest Catchment Runoff Characteristics by Different Forest Sites and Stands. National Institute of Forest Science: Seoul, South Korea, 2021.
ISBN: 9791160195514

Choi, H.T., Kim, J., Seol, A., Jang, J., Jung, S., Kim, S., Lim, H., Yang, H., and Yoo, H. A Study on the Quantification and Improvement of Forest Water Yield for Sustainable Supply of Freshwater. National Institute of Forest Science: Seoul, South Korea, 2021.
ISBN: 9791160195507

Choi, H.T., Kim, J., Lim, H., Yang, H., and Yoo, H. Development and Utilization of the Forest Water Map. National Institute of Forest Science: Seoul, South Korea, 2020.
ISBN: 9791160194999

Kim, J., Choi, H.T., Lim, H., Yang, H., and Yoo, H. Analysis on the Current Status of River Survey Methodology for the Effective Investigation of Forest Drought. National Institute of Forest Science: Seoul, South Korea, 2020.
ISBN: 9791160194913

Choi, H.T., Lim, H., and Yang, H. Development Method and Application of Forest Water Map. National Institute of Forest Science: Seoul, South Korea, 2019.
ISBN: 9791160193800

AWARDS AND HONORS

PEER-REVIEW SERVICE

• Journal of Hydrology
• Geomatics, Natural Hazards and Risk

TECHNICAL SKILLS