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
- Climate change and impacts on hydrology and water resources
- Reconstruction of paleo-hydrology – implications for climate change analysis
- Surrogate modelling, artificial intelligence, and machine learning
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
Opportunities
Graduate students and post-doctoral fellows in the lab actively work on the different natural (e.g., rainfall-runoff, snow, permafrost, soil storage, etc.) and human-driven (e.g., reservoirs, water diversions and abstractions, agriculture, etc.) components and bring them together under a unified umbrella for the synthesis of systems behaviour.
We are always interested to hear from highly-motivated individuals wishing to pursue graduate studies within our group. If you are one of them, please apply directly to Dr. Saman Razavi.
Research Profile

Dr. Razavi's research focuses on developing systems theoretic approaches and tools to better understand, simulate, and predict hydrologic and water resources systems. Such systems consist of many interrelated, dynamical components working across a range of spatio-temporal scales. His work also focuses on watershed modelling, water resources systems analysis and management, and optimization and decision making under change and non-stationarity in climate and the environment. In particular, his research work has provided leadership in the areas of sensitivity analysis (for uncertainty quantification) and surrogate modelling (for improved computational efficiency).
News and Media
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Current Research
- Development of a New Framework for Watershed Systems Analysis and Modelling Under Climate and Environmental Changes
- Delivering Global Water Futures solutions for forecasting, prediction and management of change for Canada’s major river basins
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
Razavi, S., Asadzadeh, M., Tolson, B.A., Fay, D., Moin, S., Bruxer, J., and Fan, Y. 2013. Evaluation of new control structures for regulating the Great Lakes system: a multi-scenario, multi-reservoir optimization approach. Journal of Water Resources Planning Management, 140(8). https://doi.org/10.1061/(ASCE)WR.1943-5452.0000375
Razavi, S., Tolson, B.A., and Burn, D.H. 2012. Review of surrogate modelling in water resources, Water Resources Research, 48(7): W07401. https://doi.org/10.1029/2011WR011527
Razavi, S., Tolson, B.A., and Burn, D.H. 2012. Numerical assessment of metamodelling strategies in computationally intensive optimization, Environmental Modelling and Software, 34(0), 67-86. https://doi.org/10.1016/j.envsoft.2011.09.010
Razavi, S., Asadzadeh, M., Tolson, B.A., Fay, D., Moin, S., Bruxer, J., and Fan, Y. 2013. Evaluation of new control structures for regulating the Great Lakes system: a multi-scenario, multi-reservoir optimization approach, Journal of Water Resources Planning Management, 140(8). https://doi.org/10.1061/(ASCE)WR.1943-5452.0000375
Courses Taught
- ENVS 805 - Data Analysis and Management
- ENVS 827 - Breakthroughs in Water Security
- ENVS 898 - Watershed Modelling
- CE 319 - Hydrology