Publications

Google Scholar

*: corresponding author

SCI(E)

Under Review

Kwon, S., Kim, J. S.*, Flood-scale shifts in effective sediment source zones and signal transmission through a gated-weir cascade. Communications Earth & Environment (under review).

Gwon, Y., Kim, D., Seo, I. W., Jung, S., Kwon, S.*, Quantifying Reach-Scale River Dispersion From Hyperspectral Drone Tracer Imaging. Water Resources Research (under review).

Woo, S., Yang, J. E., Bugaj, A., Black, A., Gin, R., Kwon, S., Bauser, H. H., Troch, P. A., Kim, M.*, Visualizing groundwater dynamics in VR: From animated rendering to interactive and immersive experiences of the Landscape Evolution Observatory, Biosphere 2. Hydrological Processes (in revision).

preprint: https://doi.org/10.22541/au.176474250.07235074/v1

Noh, H., Park, Y. S.*, Seo, I. W., Kwon, S., A unified bedload transport formula from synthesized flume and river observations using shear stress rescaling. Earth Surface Processes and Landforms (under review).

2026

[30] Yoon, S., Lee, C., Kwon, S., Kim, Y. D.*, Lateral heterogeneity of thermal stratification and mixing dynamics in a regulated multi-inflow reservoir. Advances in Water Resources, 217, 105476.  https://doi.org./10.1016/j.advwatres.2026.105476

[29] Kim, J. S., Kwon, S.*, Microplastic transport in meandering open-channel flows: coupled effects of sinuosity and particle density. Journal of Contaminant Hydrology, 282, 105040. https://doi.org/10.1016/j.jconhyd.2026.105040

[28] Kim, J. S., Beak, K. O., Kwon, S.*, A Depth-dependent machine learning framework for satellite-derived bathymetry of morphologically complex reservoirs. Geocarto International, 41(1). https://doi.org/10.1080/10106049.2026.2694889

[27] Kang, Y., Nam, S. H., Kwon, S., Kim, Y. D.*,  A cluster-based virtual sensing framework for estimating total nitrogen and total phosphorus using sensor-measurable water quality variables. Journal of Contaminant Hydrology, 282, 105024. https://doi.org/10.1016/j.jconhyd.2026.105024

2025

[26] Kwon, S.*, Passalacqua, P., Nghiem, J., Lamb, M., Mixing patterns of river deltas obtained from remotely-sensed Rouse number. Journal of Geophysical Research: Earth Surface, 130, e2024JF008077. https://doi.org/10.1029/2024JF008077

[25] Kwon, S., Kang, Y., Nam, S. H., Kim, Y. D.*, Intelligent river water quality monitoring using hybrid physical–soft sensors in digital twins: a comprehensive review. Water Science & Technology, 92(9), 1286–1307.  https://doi.org/10.2166/wst.2025.145

[24] Kwon, S.*, Noh, H., Seo, I. W.*, Lee, Y. H., CCTV-hyperspectral imaging for suspended sediment transport (HISST): proof-of-concept for a continuous day-and-night monitoring approach. Water Resources Research, 61(10).

https://doi.org/10.1029/2025WR040402

[23] Kwon, S., Seo, I. W.*, Park, I., Kim, J. S., Suspended material retention in riverine reservoirs: role of hydropeaking, density currents, and settling velocity. Journal of Hydrology-Regional Studies, 61, 102706. https://doi.org/10.1016/j.ejrh.2025.102706

[22] Barile, G.*, Passalacqua, P., Kwon, S., Tubino, M., Controlling factors on water and sediment partitioning at deltaic bifurcations. Journal of Geophysical Research: Earth Surface, 130(7).  https://doi.org/10.1029/2024JF008152

[21] Kim, J., Kwon, S., Chung, S. W., Kim, Y. D.*, Turbidity and suspended sediment relationship based on sediment composition and particle size distribution. Scientific Reports, 15, 16286. https://doi.org/10.1038/s41598-025-00435-2

[20] Kim, T., Shahriar, A. R., Lee, W. D.*, Choi, Y., Kwon, S., Gabr, M. A., Field data-based prediction of local scour depth around bridge piers using interpretable machine learning. Transportation Geotechnics, 52, 101567. https://doi.org/10.1016/j.trgeo.2025.101567

2024

[19] Kwon, S.*, Passalacqua, P., Soloy, A., Jensen, D., Simard, M. Depth mapping in turbid and deep waters using AVIRIS-NG imagery: a study in Wax Lake Delta, Louisiana, USA. Water Resources Research, 60(11). https://doi.org/10.1029/2023WR036875

[18] Park, I., Seo, I.W.*, Cho, S., Kim, D., Park, S., Kwon, S., Analysis of microplastic behaviors in river-type lakes using a quasi-three-dimensional microplastic transport model. Science of the Total Environment, 956, 177204. https://doi.org/10.1016/j.scitotenv.2024.177204

[17] Kwon, S., Seo, I.W., Kim, B., Jung, S.H.*, Kim, Y. D., Assessment of river recreation safety using hydrodynamic model and fuzzy logic: a spatial river recreational index approach. Journal of Hydro-environment Research, 55, p.30-45.

https://doi.org/10.1016/j.jher.2024.06.002

[16] Kwon, S.,  Seo, I.W.*, Kim., D., Effects of hydropeaking by an upstream dam on thermal mixing in a riverine lake. Journal of Hydrology, 633, 130992. https://doi.org/10.1016/j.jhydrol.2024.130992.

[15] Noh, H., Kwon, S.,  Park, Y.S.*, Woo, S-B, Application of RGB UAV imagery to sea surface suspended sediment concentration monitoring in coastal construction site. Applied Ocean Research, 145, 103940. https://doi.org/10.1016/j.apor.2024.103940.

[14] Nam, S.H.,  Kwon, S., Kim., Y.D.*, Development of a basin-scale total nitrogen prediction model by integrating clustering and regression methods. Science of the Total Environment, 920, 170765. https://doi.org/10.1016/j.scitotenv.2024.170765.

[13] Jung, S.H., Kwon, S., Seo, I.W., Kim, J.S.*, Comparison between hyperspectral and multispectral retrievals of suspended sediment concentration in rivers. Water, 16(9), 1275. https://doi.org/10.3390/w16091275.

2023

[12] Gwon, Y., Kwon, S.*, Kim., D., Seo, I.W., You, H., Estimation of shallow stream bathymetry under varying suspended sediment concentrations and compositions using hyperspectral imagery. Geomorphology, 433(15), 108722. https://doi.org/10.1016/j.geomorph.2023.108722

[11] Kwon, S., Noh, H., Seo, I.W.*, Park, Y.S., Effects of spectral variability due to sediment and bottom characteristics on remote sensing for suspended sediment in shallow rivers. Science of the Total Environment, 833, 155168.  https://doi.org/10.1016/j.scitotenv.2023.163125

[10] Kim, B., Seo, I.W.*, Kwon, S., Baek, D.,  Estimating Net Retention Time of Solute in Storage Zones of a Stream. Water Resources Research, 59(5). https://doi.org/10.1029/2022WR032243

[9] Kwon, S., Gwon, Y.*, Kim., D., Seo, I.W., You, H., Unsupervised classification of bottom materials for bathymetry estimation using UAV-based hyperspectral imagery in shallow rivers. Remote Sensing, 15(11), 2803. https://doi.org/10.3390/rs15112803

[8] Kwon, S., Seo, I.W.*, Lyu. S., Investigating mixing patterns of suspended sediment in a river confluence using high-resolution hyperspectral imagery. Journal of Hydrology, 620PB, 129505. https://doi.org/10.1016/j.jhydrol.2023.129505

[7] Kim, B., Kwon, S.*, Seo, I.W., An explicit solution for characterizing non-Fickian solute transport in natural streams. Water, 15(9), 1702. https://doi.org/10.3390/w15091702

2022

[6] Kim, B., Kwon, S., Noh, H., Seo, I.W.*, Surrogate prediction of the breakthrough curve of solute transport in rivers using its reach length dependence. Journal of Contaminant Hydrology. 249, 104024. https://doi.org/10.1016/j.jconhyd.2022.104024.

[5] Kwon, S., Seo, I.W.*, Noh, H., Kim, B., Hyperspectral retrievals of suspended sediment using cluster-based machine learning regression in shallow waters. Science of the Total Environment, 833, 155168. https://doi.org/10.1016/j.scitotenv.2022.155168

[4] Kwon, S., Shin, J., Seo, I.W.*, Noh, H., Jung, S.H., You, H., Measurement of suspended sediment concentration in open channel flows based on hyperspectral imagery from UAVs. Advances in Water Resources, 159, 104076. https://doi.org/10.1016/j.advwatres.2021.104076

2021

[3] Kim, B., Seo, I.W.*, Kwon, S., Jung, S.H., Choi, Y., Modeling one-dimensional reactive transport of toxic contaminants in natural rivers. Environmental Modeling and Software, 137, 104971. https://doi.org/10.1016/j.envsoft.2021.104971

[2] Kwon, S., Noh, H., Seo, I.W.*, Jung, S.H., Baek, D., Identification framework of contaminant spill in rivers using machine learning with breakthrough curve analysis. International Journal of Environmental Research and Public Health, 18, 1–28. https://doi.org/10.3390/ijerph18031023

2020

[1] Noh, H., Kwon, S., Seo, I.W.*, Baek, D., Jung, S.H., Multi-gene genetic programming regression model for prediction of transient storage model parameters in natural rivers. Water, 13, 76. https://doi.org/10.3390/w13010076

Other Publications

[9] Kim, D., Kim, D., You, H., Lee, S., Kwon, S.*, 2026. Bed Morphology Measurement Capability in Large Korean Rivers Extending Maximum Measurable Depth using CMR-OV Hyperspectral Bathymetry Method. Journal of Korea Water Resources Association (accepted).

[8] Kwon, S., Noh, H., Seo, I. W.*, 2026. Applicability Assessment of Hyperspectral CCTV for Suspended Sediment Monitoring: A Sediment Tracer Experiment in the Gam Creek. Journal of Korea Water Resources Association 59(4), 405-417. https://doi.org/ 10.3741/JKWRA.2026.59.4.405

[7] Seo, I. W., Kwon, S.*, 2025. Longitudinal and transverse mixing coefficients of two-dimensional advection-dispersion model for river water quality analysis. KSCE Journal of Civil and Environmental Engineering Research, 45(5), 533-547.  https://doi.org/10.12652/Ksce.2025.45.5.0533

[6] Kim, J., Kim, G. S., Kwon, S., Kim, Y.*, 2024. Review of applicability of turbidity-SS relationship in hyperspectral imaging-based turbid water monitoring. Journal of Korea Water Resources Association, 56(12), 919-928. https://doi.org/10.3741/JKWRA.2023.56.12.919

[5] Gwon, Y., Kim, D.*, Kwon, S., 2023. Riverine bathymetry survey using unmanned aerial vehicle-based multispectral image. Geo Data, 5(3), 195-206. https://doi.org/10.22761/GD.2023.0033

[4] Kim, J., Lee, S.U., Kwon, S., Chung, S.W., Kim, Y.*, 2022. Improvement of turbid water prediction accuracy using sensor-based monitoring data in Imha Dam reservoir. Journal of Korea Water Resources Association, 55(11), 931-939. 

https://doi: 10.3741/JKWRA.2022.55.11.931

[3] Gwon, Y., Kim, D.*, You, H., Han, E., Kwon, S., Kim, Y., 2022. Development of tracer concentration analysis method using drone-based spatio-temporal hyperspectral image and RGB image. Journal of Korea Water Resources Association, 55(8), 623-634. https://doi.org/10.3741/JKWRA.2022.55.8.623

[2] Kim, B., Seo, I. W.*, Kwon, S., Jung, S. H., Yun, S. H., 2021. Analysis of solute transport in rivers using a stochastic storage model. Journal of Korea Water Resources Association, 54(5), 335-345. https://doi.org/10.3741/JKWRA.2021.54.5.335.

[1] Kwon, S., Seo. I. W.*, and Baek, D., 2021. Development of suspended solid concentration measurement technique based on multi-spectral satellite imagery in Nakdong River using machine learning model. Journal of Korea Water Resources Association, 54(2), 121-133. https://10.3741/JKWRA.2021.54.2.121

Pantents

Korean Patent 10-2933549: CCTV-based hyperspectral image classification system and method for continuous non-contact monitoring of suspended sediment under daytime and nighttime conditions.

Korean Patent 10-2614520: Mixing prediction method and device based on flow distance-concentration curve correlation.

Korean Patent 10-2355001: Method of estimating the spatial distribution of suspended sediment concentration from hyperspectral imagery using machine learning regression model and probabilistic clustering method.

Korean Patent 10-2210698: Method for back-tracing the source of chemical accidents by combining a machine learning model based on a river hazardous chemical spill scenario and a recursive feature elimination method.

Korean Patent 10-2189254: Method of providing pollutants transport and backtracking information through GIS-based irregular river topography characteristic analysis.