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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » People » Sangchul Lee

Sangchul Lee

Visiting Scientist


/ARSUserFiles/53110/SangchulLee.jpg 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:


Education:


Professional Experience:


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

 

 

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