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Yu Zhang


[Zhang, Yu]
  • Associate Professor


Yu Zhang joins the Civil Engineering Department after nearly a decade as a physical scientist at the National Oceanic and Atmospheric Administration. He has been PI or Co-I for NOAAs GPM and GOES-R missions, US Weather Research and Joint Polar Satellite System programs, and Climate Program Offices MAPP.  He has published more than 30 referred journal articles, and currently serves as associate editor for Elseviers Journal of Hydrology, and AMSs Journal of Hydrometeorology. 

Research interests: Active and passive remote sensing of water and water fluxes; Climate change and hazard resilience of water infrastructure; Physical and statistical modeling of hydrological and climatological extremes; Downscaling and conditioning of ensemble hydrologic predictions; Surface water, ground water and water quality modeling; and numerical methods. 

Professional Preparation

    • 1999 Master of Art in Civil Engineering and Operational ResearchPrinceton University
    • 2003 PhD in Civil and Environmental EngineeringPrinceton University


    • Jan 2017 to Present Associate Professor
      UT Arlington
    • Aug 2007 to Jan 2017 Physical Scientist
      Department of Commerce (DoC)   National Oceanic and Atmospheric Administration (NOAA)
    • July 2005 to Sept 2006 Hydrologist


  • Membership
    • Dec 2016 to Present American Geophysical Union (AGU)  Technical Committee on Precipitation
    • Feb 2011 to Present American Meteorological Society (AMS)  Hydrology Committee

Research and Expertise

  • Extreme value analysis and risk management

    Understanding tail behavior of hydrologic variables such as precipitation and streamflow. 

  • Remote sensing of water fluxes

    Active and passive remote sensing of water fluxes (precipitation and evapotranspiration), soil moisture, and snow.


      Journal Article 2017
      • Zhang, Y. and L. Wu, J. Schaake, and M. Scheurer, 2017: Comparison of probabilistic quantitative precipitation forecast from two postprocessing mechanisms. In press, J. of Hydromet.

        {Journal Article} [Refereed/Juried]
      • Zhang, Y. and D-J. Seo, 2017: Recursive Estimators of Mean-areal and Local Bias in Precipitation Products that Account for Conditional Bias, Adv. Wat. Res. 101. 49-59

        {Peer Reviewed} [Refereed/Juried]

      Journal Article 2016
      • Zhang, Y., Reed, S., Gourley, J.J., Cosgrove, B., Kitzmiller, D., Seo, D.J. and Cifelli, R., 2016. The impacts of climatological adjustment of quantitative precipitation estimates on the accuracy of flash flood detection. Journal of Hydrology541, pp.387-400.

        {Journal Article} [Refereed/Juried]
      • Kuligowski, R.J., Li, Y., Hao, Y. and Zhang, Y., 2016. Improvements to the GOES-R Rainfall Rate Algorithm. Journal of Hydrometeorology17(6), pp.1693-1704.

        {Journal Article} [Refereed/Juried]

      Journal Article 2015
      • Lee, H., Y. Zhang, D-J. Seo, and P. Xie, 2015: Assimilation of satellite QPEs and the impacts on runoff prediction and rainfall estimates J. Hydrology 529, 779-794.

        {Journal Article} [Refereed/Juried]

      Journal Article 2014
      • Zhang, Y., D-J. Seo, E. Habib, and J. McCollum 2014: Differences in Scale-dependent, Climatological Variation of Mean Areal Precipitation based on a Satellite and Radar-Gauge Observations J. of Hydrology,  522, pp.35-48.

        {Journal Article} [Refereed/Juried]


      • CE 3342-001 Water Resources Engineeing

        CE3342 - Water Resource Engineering (3 - 0)
        Hydrologic cycle, water balance analysis, rainfall estimation, design storm, infiltration and runoff, unit hydrograph, groundwater flow, reservoir routing, hydrologic modeling, floodplain and frequency analysis.   The class will be a combination of lectures, problem solution sessions, and guest lectures.   

        Spring - Regular Academic Session - 2018 Download Syllabus Contact info & Office Hours

        CE5300 - Hydrometeorology and Remote Sensing (3 - 0)
        Atmospheric composition, radiative fluxes,  thermodynamics,  water vapor,  stability,  circulation, precipitation processes, fronts, thunderstorms and tropical storms; basics of remote sensing; observing precipitation using weather radar and satellite-borne sensors; prediction of precipitation by numerical weather models. The class will be a combination of lectures and in-class computer-based laboratory exercises.   

        Fall - Regular Academic Session - 2017 Download Syllabus Contact info & Office Hours