Hyunglok Kim bio photo

Hyunglok Kim

Terrestrial Water Cycle
Hydrology
Remote Sensing
Bayesian Inference
Machine Learning
Deep Learning

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Publications

Publications

A list is also available Google Scholar Page

Underlined = corresponding author.

Peer-Reviewed Journal Papers

(in review/revision/submission)

2022 [1] Impact of Vegetation Gradient and Land Cover Condition on Soil Moisture Retrievals from Different Frequencies and Acquisition Times of Satellite Observations, IEEE Transactions on Geoscience and Remote Sensing (major revision) (corresponding author)

2022 [2] Changes in the speed of the subdaily global terrestrial water cycle due to human intervention (re-submission) (first author)

2022 [3] Performance assessment of SM2RAIN-NWF using ASCAT soil moisture via supervised land cover-soil-climate classification, Remote Sensing of Environment (major revision) (co-author)

2022 [4] Toward streamflow estimation in ungauged regions using machine learning: Quantifying uncertainties in spatial extrapolation, Hydrology and Earth System Sciences (in-review) (corresponding author)

Peer-Reviewed Papers

2022

[23] Toward streamflow estimation in ungauged regions using machine learning: Quantifying uncertainties in spatial extrapolation, Hydrology and Earth System Sciences Discussion (pre-print) (corresponding author)

[22] A comprehensive assessment of SM2RAIN-NWF using ASCAT and a combination of ASCAT and SMAP soil moisture products for rainfall estimation, M. Saeedi, H. Kim, S. Nabaeia, L. Brocca, V. Lakshmi, H. Mosaffac [ in-press ]
Science of The Total Environment

[21] S. Lee, J. Qi, G. McCarty, M. Anderson, Y. Yang, X. Zhang, G. Moglen, D. Kwak, H. Kim, V. Lakshmi, S. Kim, Combined use of crop yield statistics and remotely sensed products for enhanced simulations of evapotranspiration within an agricultural watershed [link]
Agricultural Water Management

2021 [20] H. Kim, V. Lakshmi, Y. Kwon, and S. Kumar, First attempt of global-scale assimilation of subdaily scale soil moisture estimates from CYGNSS and SMAP into a land surface model [PDF]
Environmental Research Letters

2021 [19] S. Lee, J. Qi, H. Kim, G. McCarty, G. Moglen, M. Anderson, X. Zhang, and L. Du, Utility of Remotely Sensed Evapotranspiration Products to Assess an Improved Model Structure [PDF]
Sustainability

2020 [18] H. Kim, J. Wigneron, S. Kumar, J. Dong, W. Wagner, M. Cosh, D. Bosch, C. Collins, P. Starks, M. Seyfried, and V. Lakshmi, Global scale error assessments of soil moisture estimates from microwave-based active and passive satellites and land surface models over forest and mixed irrigated/dryland agriculture regions [PDF]
Remote Sensing of Environment

2020 [17] H. Kim, S. Lee, M. Cosh, V. Lakshmi, Y. Kwon, and G. McCarty, Assessment and Combination of SMAP and Sentinel-1A/B-Derived Soil Moisture Estimates With Land Surface Model Outputs in the Mid-Atlantic Coastal Plain, USA [PDF]
IEEE Transactions on Geoscience and Remote Sensing

2020 [16] M. Le, H. Kim, H. Moon, R. Zhang, V. Lakshmi, and L. Nguyen, Assessment of drought conditions over Vietnam using standardized precipitation evapotranspiration index, MERRA-2 re-analysis, and dynamic land cover [PDF]
Journal of Hydrology: Regional Studies

2019 [15] H. Kim, M. Cosh, R. Bindlish, and V. Lakshmi, Field evaluation of portable soil water content sensors in a sandy loam [PDF]
Vadose Zone Journal

2019 [14] H. Kim and V. Lakshmi, Global dynamics of stored precipitation water in the topsoil layer from satellite and reanalysis data [PDF]
Water Resources Research

2019 [13] S. Parajuli, G. Stenchikov, A. Ukhov, H. Kim, Dust emission modeling using a new high‐resolution dust source function in WRF‐Chem with implications for air quality [PDF]
Journal of Geophysical Research: Atmospheres

2019 [12] M. Zohaib, H. Kim, M. Choi, Detecting global irrigated areas by using satellite and reanalysis products [PDF]
Science of The Total Environment

2018 [11] H. Kim and V. Lakshmi, Use of Cyclone Global Navigation Satellite System (CYGNSS) observations for estimation of soil moisture [PDF]
Geophysical Research Letters

2018 [10] H. Kim, R. Parinussa, A. Konings, W. Wagner, M. Cosh, V. Lakshmi, M. Zohaib, and M. Choi, Global-scale Assessment and Combination of SMAP with ASCAT (Active) and AMSR2 (Passive) Soil Moisture Products [PDF]
Remote Sensing of Environment

2018 [9] D. Kim, H. Moon, H. Kim, J. Im, and M. Choi, Intercomparison of Downscaling Techniques for Satellite Soil Moisture Products [PDF]
Advances in Meteorology

2017 [8] H. Kim, Z. Muhammad, E. Cho, Y. Kerr, and M. Choi, Development and Assessment of the Sand Dust Prediction Model by Utilizing Microwave Satellite Soil Moisture and Reanalysis Datasets in East Asian Desert Areas [PDF]
Advances in Meteorology

2017 [7] H. Nguyen, H. Kim, M. Choi, Evaluation of the soil water content using cosmic-ray neutron probe in a heterogeneous monsoon climate-dominated region [PDF]
Advances in Water Resources

2017 [6] M. Zohaib, H. Kim, and M. Choi, Evaluating the Patterns of Spatiotemporal Trends of Root Zone Soil Moisture in Major Climate Regions in East Asia [PDF]
Journal of Geophysical Research: Atmospheres

2017 [5] M. Choi, Q. Mu, H. Kim, K. Hwang, and J. Hur, Ecosystem-dynamics link to hydrologic variations for different land-cover types [PDF]
Terrestrial Atmospheric and Oceanic Sciences

2017 [4] E. Cho, C. Su, D. Ryu, H. Kim, and M. Choi, Does AMSR2 produce better soil moisture retrievals than AMSR-E over Australia? [PDF]
Remote Sensing of Environment

2016 [3] D. Kim, J. Lee, H. Kim, and M. Choi, Spatial composition of AMSR2 soil moisture products by conditional merging technique with ground soil moisture data [PDF]
Stochastic Environmental Research and Risk Assessment

2015 [2] H. Kim, and M. Choi. “Impact of soil moisture on dust outbreaks in East Asia: Using satellite and assimilation data [PDF]
Geophysical Research Letters

2014 [1] Y. Jung, H. Kim, J. Baek, and M. Choi, Rain Gauge Network Evaluations using Spatiotemporal Correlation Structures for Semi-mountainous Regions [PDF]
Terrestrial, Atmospheric and Oceanic Sciences

Conference Papers

2021 [13] R. Zhang, H. Kim, E. Lien, D. Zheng, L. Band, and V. Lakshmi, Deep Learning Approach to Predict Peak Floods and Evaluation of Socioeconomic Vulnerability to Flood Events: A Case Study in Baltimore, MD, IEEE SIEDS [PDF]

2020 [12] H. Kim and V. Lakshmi, Producing Satellite-based Diurnal Time-scale Soil Moisture Retrievals using Existing Microwave Satellites and GNSS-R Data (invited),
AGU Fall Meeting

2020 [11] H. Kim, J. Wigneron, S. Kumar, J. Dong, W. Wagner, M. Cosh, D. Bosch, C. Collins, P. Starks, M. Seyfried, and V. Lakshmi, Error Characteristic Assessments of Soil Moisture Estimates from Satellites and Land Surface Models: Focusing on Forested and Irrigated Regions,
AGU Fall Meeting

2020 [10] R. Zhang, H. Kim, L. Band, V. Lakshmi, An Integrated Framework to Predict Peak Flood and Map Inundation Areas in the Chesapeake Bay Using Machine Learning Methods with High-Resolution Lidar DEM and Satellite Data,
AGU Fall Meeting

2020 [9] V. Sunkara, C. Doyle, H. Kim, B. Tellman, and V. Lakshmi, Leveraging Soil Moisture for Early Flood Detection,
AGU Fall Meeting

2020 [8] G. Pavur, H. Kim, and V. Lakshmi, Detecting Inland Waterbodies Using GNSS-R Data: Intercomparison of Previous Methods and a New Machine Learning Approach,
AGU Fall Meeting

2020 [7] H. Kim, V. Lakshmi, S. Kumar, and Y. Kwon, Assimilation of SMAP-enhanced and SMAP/Sentinel-1A/B soil moisture data into land surface models,
EGU General Assembly Conference

2019 [6] H. Kim, Y. Kwon, S. Kumar, and V. Lakshmi, Assimilation of GPS soil moisture data from CYGNSS into land surface models,
AGU Fall Meeting

2018 [5] H. Kim and V. Lakshmi, The Impact of Irrigation on the Water Cycle in the Continental United States (CONUS),
AGU Fall Meeting

2017 [4] H. Kim and V. Lakshmi, Evaluating the Long-term Water Cycle Trends at a Global-scale using Satellite and Assimilation Datasets,
AGU Fall Meeting

2016 [3] H. Kim, R. Parinussa, A. Konings, W. Wagner, M. Cosh, M. Choi, Assessment and Combination of SMAP with ASCAT (Active) and AMSR2 (Passive) Soil Moisture Products: A Case Study in Northeast Asia,
AGU Fall Meeting

2015 [2] H. Kim and M. Choi, Blending and Comparison of Passive and Active Satellite-Based Microwave Soil Moisture Retrievals (ASCAT, MIRAS, AMSR2, FY-3B, and SMAP) with Modeled Simulations (GLDAS) over Different Land Covers in East Asia,
AGU Fall Meeting

2015 [1] H. Kim, E. Cho, and M. Choi, Identifying Vulnerability Regions of Dust Outbreaks in East Asian Desert Areas: using ASCAT, MIRAS, AMSR2, MWRI, MODIS, and GLDAS,
AGU Fall Meeting

Theses

[3] Ph.D. Thesis (TBD)

[2] An Integrated Framework to Predict Peak Flood and Map Inundation Areas Using Machine Learning Methods with High-Resolution Lidar DEM and Satellite Data,
University of Virginia (M.S. in Data Science)

[1] Estimation and Application of Satellite-based Soil Moisture Retrievals: Data Inter-comparison, Fusion, and Application in Natural Disasters,
Sungkyunkwan University (M.S.E. in Water Resources)

Korean Peer-Reviewed Papers

2016 [7] H. Kim, S. Kim, J. Jeong, I. Shin, J. Shin, M. Choi, Revising Passive Satellite-based Soil Moisture Retrievals over East Asia using SMOS (MIRAS) and GCOM-W1 (AMSR2) satellite and GLDAS Assimilation Dataset,
Journal of Wetlands Research (link)

2016 [6] S. Kim, H. Kim, M. Choi, Evaluation of satellite-based soil moisture retrieval over the korean peninsula: using AMSR2 LPRM algorithm and ground measurement data,
Journal of Korea Water Resources Association (link)

2016 [5] L. Li, H. Kim, K. Jun, M. Choi, Estimation of River Discharge using Satellite-derived Flow Signals and Artificial Neural Network Model: Application to Imjin River, Korea Water Resources Association (link)

2016 [4] H. Kim, W. Sunwoo, S. Kim, M. Choi, Construction and estimation of soil moisture site with FDR and COSMIC-ray (SM-FC) sensors for calibration/validation of satellite-based and COSMIC-ray soil moisture products in Sungkyunkwan university, South Korea,
Korea Water Resources Association (link)

2016 [3] M. Choi, H. Kim, S. Kim, and M. Choi, Effects of Morbidity in Korean Peninsula due to Sand Dust using Satellite Aerosol Observations,
Korea Journal of Remote Sensing (link)

2015 [2] H. Kim and M. Choi, An Inter-comparison of Active and Passive Satellite Soil Moisture Products in East Asia for Dust-Outbreak Prediction,
Korean Society of Hazard Mitigation (link)

2015 [1] J. Lim, J. Baik, H. Kim, M. Choi, Estimation of Water Quality using Landsat 8 Images for Geum-river, Korea,
Journal of Korea Water Resources Association (link)

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