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Jeffrey Kwang

(He/Him)

Jeffrey Kwang (he/him) is a Physical Scientist for the USGS Water Resources Mission Area

Jeffrey uses numerical modeling and remote sensing to study how landscapes evolve over a broad range of temporal and spatial scales. Prior to joining the USGS, Jeffrey researched the role of autogenic dynamics and rock heterogeneity in reorganizing river networks. Jeffrey also built high-resolution, region-scale models that predicted how agricultural practices have redistributed soil and soil organic carbon. 
 
As a physical scientist at the USGS, Jeffrey is part of the Data Science Branch where he will help create interactive data visualizations to better communicate USGS science and numerical models to improve our predictions of sediment dynamics.

Professional Experience

  • 2024 – present: Physical Scientist, Integrated Information Dissemination Division

  • 2022 – 2024: National Science Foundation Earth Science Postdoctoral Fellow, University of Minnesota Twin Cities

  • 2019 – 2022: Postdoctoral Associate, University of Massachusetts Amherst

Education and Certifications

  • ​​Ph.D., Civil Engineering, University of Illinois at Urbana-Champaign, 2019

  • ​M.S., Civil Engineering, University of Illinois at Urbana-Champaign, 2016

  • ​B.S., Environmental Engineering, Johns Hopkins University, 2013​ 

Honors and Awards

  • National Science Foundation Earth Sciences Postdoctoral Fellowship, 2022 - 2024

  • National Science Foundation Graduate Research Fellowship, 2015 - 2018

  • Ben Chie Yen Fellowship, Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 2013 - 2015

  • Lucien Brush Award for Excellence in Environmental Engineering, Department of Geography and Environment Engineering, Johns Hopkins University, 2013 - 2015​

Science and Products

Non-USGS Publications**

​​Kwang, J. S., Thaler, E. A.& Larsen, I. J. The Future of Soils in the Midwestern United States. Earth’s Future (2023). https://doi.org/10.1029/2022EF003104
​Kwang, J. S., Thaler, E. A., Quirk, B. J., Quarrier, C. L. & Larsen, I. J. A landscape evolution modeling approach for predicting three‐dimensional soil organic carbon redistribution in agricultural landscapes. Journal of Geophysical Research: Biogeosciences (2022). https://doi.org/10.1029/2021JG006616
​Kwang, J. S., Langston, A. L. & Parker, G. The role of lateral erosion in the evolution of non‐dendritic drainage networks to dendricity and the persistence of dynamic networks. Proceedings of the National Academy of Sciences of the United States of America 118, e2015770118 (2021). https://doi.org/10.1073/pnas.2015770118
​Kwang, J. S. & Parker, G. Extreme Memory of Initial Conditions in Numerical Landscape Evolution Models. Geophysical Research Letters 46, 6563–6573 (2019). https://doi.org/10.1029/2019GL083305
​Kwang, J. S. & Parker, G. Landscape evolution models using the stream power incision model show unrealistic behavior when m/n equals 0.5. Earth Surface Dynamics 5, 807–820 (2017). https://doi.org/10.5194/esurf‐5‐807‐2017​

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

Science and Products

Non-USGS Publications**

​​Kwang, J. S., Thaler, E. A.& Larsen, I. J. The Future of Soils in the Midwestern United States. Earth’s Future (2023). https://doi.org/10.1029/2022EF003104
​Kwang, J. S., Thaler, E. A., Quirk, B. J., Quarrier, C. L. & Larsen, I. J. A landscape evolution modeling approach for predicting three‐dimensional soil organic carbon redistribution in agricultural landscapes. Journal of Geophysical Research: Biogeosciences (2022). https://doi.org/10.1029/2021JG006616
​Kwang, J. S., Langston, A. L. & Parker, G. The role of lateral erosion in the evolution of non‐dendritic drainage networks to dendricity and the persistence of dynamic networks. Proceedings of the National Academy of Sciences of the United States of America 118, e2015770118 (2021). https://doi.org/10.1073/pnas.2015770118
​Kwang, J. S. & Parker, G. Extreme Memory of Initial Conditions in Numerical Landscape Evolution Models. Geophysical Research Letters 46, 6563–6573 (2019). https://doi.org/10.1029/2019GL083305
​Kwang, J. S. & Parker, G. Landscape evolution models using the stream power incision model show unrealistic behavior when m/n equals 0.5. Earth Surface Dynamics 5, 807–820 (2017). https://doi.org/10.5194/esurf‐5‐807‐2017​

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.