Picture of  Saman Razavi

Saman Razavi PhD Associate Professor | Joint Appointment College of Engineering, Department of Civil, Geological and Environmental Engineering

Member, Global Institute for Water Security

National Hydrology Research Centre

Research Area(s)

  • Hydrologic models development and calibration
  • Environmental and water resources systems planning and management
  • Single- and multi-objective optimization, sensitivity analysis, and uncertainty quantification; surrogate modelling, artificial intelligence, and machine learning
  • Climate change and impacts on hydrology and water resources
  • Reconstruction of paleo-hydrology and its implications for climate change analysis

Academic Credentials

  • Doctor of Philosophy, Civil and Environmental Engineering, University of Waterloo
  • Master of Science, Civil and Environmental Engineering, Amirkabir University, Iran
  • Bachelor of Science,Civil Engineering, Iran University of Science and Technology, Iran

Selected Publications

Razavi, S., and Gupta, H.V.  2016.  A new framework for comprehensive, robust, and efficient global sensitivity analysis: I. Theory.  Water Resources Research, 52(1): 423-439.  https://doi.org/10.1002/2015WR017558

Razavi, S., and Gupta, H.V.  2015.  What do we mean by sensitivity analysis? The need for comprehensive characterization of ‘‘global’’ sensitivity in Earth and Environmental systems models.  Water Resources Research, 51: 3070–3092.  https://doi.org/10.1002/2014WR016527

Razavi, S., Elshorbagy, A., Wheater, H., and Sauchyn, D.  2015.  Toward understanding nonstationarity in climate and hydrology through tree ring proxy records.  Water Resources Research, 51: 1813–1830.  https://doi.org/10.1002/2014WR015696

Asadzadeh M., Razavi, S., Tolson, B.A., Fay, D., and Fan, Y.  2014.  Pre-emption Strategies for Efficient Multi-objective Optimization: Application to the development of Lake Superior Regulation Plan. Environmental Modelling and Software, 54: 128-141. https://doi.org/10.1016/j.envsoft.2014.01.005

Razavi, S. and Tolson, B.A.  2013.  An efficient framework for hydrologic model calibration on long data periods.  Water Resources Research, 49(12): 8418-8431.  https://doi.org/10.1002/2012WR013442