Associate Professor

Contact InformationBruce MacVicar

Phone: 519-888-4567 x38897
Location: E2 2317


Biography Summary

Bruce MacVicar is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Waterloo. He is affiliated with ASCE: Environmental & Water Resources Engineering, CWRA and River Restoration Northwest.

His research interests lie in river engineering, understanding the effect of urbanisation on sediment transport, studying the hydrodynamics of straight pools, and quantifying wood transport in rivers.

Professor MacVicar conducts research on hydraulic engineering and fluvial geomorphology, while placing a particular emphasis on river dynamics. His research uses field measurements, physical experiments and computer simulations to understand various aspects of river processes such as sediment transport and flow turbulence. He ultimately aims to improve engineering designs, protect and restore critical habitats in rivers and floodplains, and preserve the integrity of these complex systems.

In addition to his research work, Professor MacVicar recruits graduate students for a field and GIS project in Toronto, where their potential funding is available through an NSERC IPS grant with an excellent mid-size firm specializing in river geomorphology and restoration. He also recruited graduate students for a laboratory-based project on sediment transport over complex boundaries using a new experimental channel that was constructed in 2012. Professor MacVicar has published several journals, and has also taken part in numerous global conference presentations.

Research Interests

  • Rivers
  • Sediment transport
  • Turbulence
  • Floods
  • Complex systems
  • Wood jams
  • Pool-riffle bedforms
  • Stream restoration
  • Natural channel design
  • Eco-hydraulics
  • Connectivity and Internet of Things
  • River engineering
  • Fluvial geomorphology
  • Urban stormwater management
  • Maintenance of critical habitats in rivers
  • Water
  • IoT
  • Devices
  • Application Domains


  • 2006, Doctorate, Fluvial Geomorphology, University of Michigan
  • 1999, Master of Applied Science, Civil Engineering, University of British Columbia
  • 1996, Bachelor of Applied Science, Water Resources Engineering, University of Guelph


  • CIVE 381 - Hydraulics
    • Taught in 2015, 2016, 2017
  • ENVE 398 - Seminar
    • Taught in 2015
  • GEOE 398 - Seminar
    • Taught in 2015
  • ENVE 214 - Fluid Mechanics and Thermal Sciences
    • Taught in 2016
  • ENVE 498 - Seminar
    • Taught in 2016
  • GEOE 498 - Seminar
    • Taught in 2016
  • CIVE 382 - Hydrology and Open Channel Flow
    • Taught in 2017, 2018, 2019
  • ENVE 280 - Fluid Mechanics
    • Taught in 2018, 2019
  • CIVE 770 - Topics in Environmental Engineering
    • Taught in 2018
  • CIVE 682 - Free Surface Hydraulics
    • Taught in 2016, 2018
* Only courses taught in the past 5 years are displayed.

Selected/Recent Publications

  • MacVicar, BJ, Good, bad and the ugly: Seasonal filtering and Autoregressive Moving Average (ARMA) models for detecting and replacing spikes in velocimetric profile data, River Flow 2016: Iowa City, USA, July 11-14, 2016, 2016
  • MacVicar, Bruce and Chapuis, Margot and Buckrell, Emma and Roy, André, Assessing the Performance of In-Stream Restoration Projects Using Radio Frequency Identification (RFID) Transponders, Water, 7(10), 2015, 5566 - 5591
  • MacVicar, Bruce and Obach, Lana, Shear Stress and Hydrodynamic Recovery over Bedforms of Different Lengths in a Straight Channel, Journal of Hydraulic Engineering, 141(11), 2015
  • Chapuis, Margot and Bright, Christina J and Hufnagel, John and MacVicar, Bruce, Detection ranges and uncertainty of passive Radio Frequency Identification (RFID) transponders for sediment tracking in gravel rivers and coastal environments, Earth Surface Processes and Landforms, 39(15), 2014, 2109 - 2120
  • MacVicar, Bruce and Dilling, Scott and Lacey, Jay, Multi-instrument turbulence toolbox (MITT): Open-source MATLAB algorithms for the analysis of high-frequency flow velocity time series datasets, Computers & Geosciences, 73, 2014, 88 - 98