Kun Zhang

headshot phot of Kun Zhang
Professional Title
Assistant Professor

Hydrology and Water Resources Engineering






  • Ph.D. Civil Engineering, The University of Hong Kong (2020)
  • M.S. Environmental Engineering, Beijing University of Civil Engineering and Architecture (2016)
  • B.S. Civil Engineering, Sichuan University (2013)


Academic & Professional Experience:

  • Assistant Professor, Department of Civil Engineering, University of Minnesota Duluth (beginning August 2023)
  • Assistant Teaching Professor, Department of Civil and Environmental Engineering, Seattle University (2023)
  • Postdoctoral Scholar, Department of Civil, Construction and Environmental Engineering, Marquette University (2020-2022)
  • Graduate Teaching Assistant, Department of Civil Engineering, The University of Hong Kong (2016-2020)


Research Interests:

I'm a hydrologic researcher who is interested in studying the hydrologic impacts of climate and urbanization stressors and exploring solutions to increase the resilience of urban water infrastructure. Our lab aims to explain urban hydrologic processes and support the design and planning of watershed management practices through physically based hydrologic modeling, data-driven analytics, and hydrologic sensing and automation.


Courses Taught:

  • CEEGR 3710 - Water Resources I (Seattle University)
  • CEEGR 3350 - Applied Hydraulics (Seattle University)
  • CEEN 4230 - Urban Hydrology and Stormwater Management (Marquette University)


Selected Journal Publications:

Full publication list also available on Google Scholar (https://scholar.google.com/citations?user=COErs5sAAAAJ&hl=en):

Zhang, K., Luhar, M., Brunner, M.I., Parolari, A.J. (2023). Streamflow prediction in ungauged watersheds in the United States through data-driven sparse sensing, Water Resources Research, 59, e2022WR034092. (https://doi.org/10.1029/2022WR034092)


Zhang, K., Bin Mammoon, W., Schwartz, E, & Parolari, A.J. (2023). Reconstruction of sparse stream flow and concentration time-series through compressed sensing. Geophysical Research Letters, 50, e2022GL101177. (https://doi.org/10.1029/2022GL101177)


Horvath, I.R., Zhang, K., Mayer, B.K., & Parolari, A.J. (2023). Regional climate influences the nutrient removal performance of vegetated stormwater best management practices. Environmental Science and Technology, 57(12), 5079–5088. (https://doi.org/10.1021/acs.est.2c05942)


Zhang, K., Sebo, S., McDonald, W., Bhaskar, A., Shuster, W., Stewart, R., Parolari, A.J. (2023). The role of inflow and infiltration (I/I) in urban water balances and streamflow regimes: A hydrograph analysis along the sewershed-watershed continuum, Water Resources Research, 59, e2022WR032529. (https://doi.org/10.1029/2022WR032529)


Zhang, K., Parolari, A. (2022). Impact of stormwater infiltration on rainfall-derived inflow and infiltration at watershed scale: A physically based surface-subsurface urban hydrologic model. Journal of Hydrology, 610, 127938. (https://doi.org/10.1016/j.jhydrol.2022.127938)


Zhang, K., Chui, T.F.M, Yang, Y. (2018). Simulating the hydrologic performance of low impact development practices in shallow groundwater via a modified SWMM. Journal of Hydrology, 566, 313-331. (https://doi.org/10.1016/j.jhydrol.2018.09.006)


Zhang, K., Chui, T.F.M. (2018). A comprehensive review of spatial allocation of LID-BMP-GI practices: Strategies and optimization tools. Science of the Total Environment, 621, 915-929. (https://doi.org/10.1016/j.scitotenv.2017.11.281)