Visiting Scientist
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Sangchul Lee, Ph.D. Postdoctoral Research Associate USDA-ARS Hydrology and Remote Sensing Laboratory Bldg. 007, Rm. 104, BARC-West Beltsville, MD 20705-2350 USA Voice: (301) 504-7490 Fax: (301) 504-8931 Sangchul.Lee@ars.usda.gov |
Research Interests:
- Assessment of conservation practice impacts on water quantity and quantity at the watershed scale.
- Integration of remotely sensed data into hydrologic modeling.
- Simulation of wetland impacts on downstream flow at multiple spatial scales.
Education:
- 2007 B.S. Environmental Science & Ecological Engineering, Korea University, Seoul, South Korea.
- 2011 M.S. Environmental Science & Ecological Engineering, Korea University, Seoul, South Korea.
- 2017 Ph.D. Department of Geographical Sciences, University of Maryland, College Park.
Professional Experience:
- 2017 – present: Postdoctoral Associate, University of Maryland, College Park & Visiting Scientist, United States Department of Agriculture (USDA) – Agricultural Research Service (ARS), Beltsville, MD.
- 2011 – 2017: Research Assistant, University of Maryland, College Park & Visiting Student, USDA – ARS, Beltsville, MD.
- 2009 – 2011: Research Fellowship, Korea University, Seoul, South Korea.
- 2007 – 2009: First Lieutenant, Republic of Korea Marine Corps, Pohang, South Korea.
Selected Publications: (please contact the author to determine reprint availability)
Lee, S., McCarty, G., Moglen, G., Lang, M.W., Sadeghi, A.M., Yeo, I.–Y, & Rabenhorst, M.C., 2018. Impacts of subsurface soil characteristics on inundation duration of depressional wetlands on the Coastal Plain of the Chesapeake Bay watershed. Hydrological Processes (in review).
Lee, S.*, Wallace, C., Sadeghi, A., McCarty, G., Zhong, H., & Yeo, I.–Y, 2018. Impacts of Global Circulation Model (GCM) bias and WXGEN on modeling hydrologic variables. Water. 10:764.
Lee, S.*, Yeo, I. –Y, Lang, M., Sadeghi, A.M., McCarty, G., Moglen, G., & Evenson, G., 2018. Assessing the cumulative impacts of geographically isolated wetlands on watershed hydrology using the SWAT model coupled with improved wetland modules. Journal of Environmental Management. 223: 37-48.
Lee, S.*, Sadeghi, A.M., McCarty, G., Baffaut, C., Lohani, S., Thompson, A., Yeo, I. –Y., & Wallace, C., 2018. Assessing the suitability of the Soil Vulnerability Index (SVI) classification scheme using the SWAT model. Catena. 167:1-12.
Wallace, C., McCarty, G., Lee, S., Brooks, R. P., Veith, T. L., Kleinman, P. J. A., & Sadeghi, A.M., 2018. Evaluating Concentrated Flowpaths in Riparian Forest Buffer Contributing Areas using LiDAR Imagery and Topographic Metrics. Remote Sensing. 10(4):614.
Lee, S.*, Yeo, I. –Y, Sadeghi, A.M., McCarty, G., Hively, D.W., Lang, M., & Sharifi, A., 2018. Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change scenarios using SWAT model. Hydrology and Earth System Sciences. 22(1): 689-708.
Sharifi, A., Wallace, C., McCarty, G., Crow, W., Momen, B., Lang, M., Sadeghi, A.M., Yen, H., Lee, S., Denver, J., & Rabenhorst, M.C., 2017. Effect of Water Quality Sampling Approaches on Nitrate Load Predictions of a Prominent Regression-based Model. Water. 9(11):895.
Lee, S., Yeo, I. –Y, Lang, M., McCarty, G., Sadeghi, A. M., Sharifi, A., Jin, H., & Liu, Y., 2017. Improving the catchment scale wetland modeling using remotely sensed data. Environmental Modelling & Software (in press)
Lee, S.*, Sadeghi, A. M., Yeo, I. –Y, McCarty, G., & Hively, D.W., 2017. Assessing the impacts of future climate conditions on the effectiveness of winter cover crops in reducing nitrate loads into the Chesapeake Bay Watershed using SWAT model. Transactions of the ASABE. 60(6): 1939-1955.
Lee, S., Yeo, I. –Y, Sadeghi, A.M., Hively, D.W., McCarty, G., & Lang, M., 2016. Impacts of Watershed Characteristics and Crop Rotations on Winter Cover Crop Nitrate Uptake Capacity within Agricultural Watersheds in the Chesapeake Bay Region. PLoS ONE. 11(6):e0157637
Sharifi, A., Lang, M., McCarty, G., Sadeghi, A.M., Lee, S., Yen, H., Jeong, J., & Rabenhorst, M.C., 2016. Improving Model Prediction Reliability through Enhanced Representation of Wetland Soil Processes and Constrained Model Auto Calibration – A Paired Watershed Study. Journal of Hydrology. 541: 1088-1103
Yeo, I. –Y, Lee, S., Sadeghi, A.M., Beeson, P., Hively, D.W., McCarty, G., & Lang, M., 2014. Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model. Hydrology and Earth System Sciences. 18(12): 5239-5253
