McMaster University has a diverse and multidisciplinary group of researchers working in water-related science, policy, and practice to deliver local and global impacts. All researchers (and research groups) seek to build capacity and advance community engagement through relationships with other institutes, industry, and government. McMaster’s researchers specialize in several water-related areas including: freshwater ecology, flood forecasting, hydrological modelling, climate change impact and adaptation, water and wastewater treatment, water security, stormwater management, water quality (contaminants and effluents), water quality sensors, indigenous water issues, ecohydrology, wildfire mitigation, wetland restoration.

RESEARCH CENTRES AND INSTITUTES

MacWater is a group of university-based scientists who believe that interacting experts from very different fields must work together to solve water quality problems.

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Contact: Ravi Selvaganapathy

selvaga@mcmaster.ca

Centre for Research in Macro- and Nano-Systems (MNSL) develops environmental sensors.

Contact: Ravi Selvaganapathy

selvaga@mcmaster.ca

PHYSICAL FACILITIES

Hyper-converged simulator for water and environmental modeling

The hyper-converged simulator in Zoe Li’s group is a high-performance computing system for water and environmental modeling, climate modeling, and infrastructure network research, as well as machine learning tasks in water and environmental areas.

Contact: Zoe Li

zoeli@mcmaster.ca

RESEARCH GROUPS AND LABS

Nutrient recovery from wastewater, PHA (polyhydroxyalkanoate), production from organic waste/CO2, anaerobic digestion, electrodialysis, microbial electrochemistry, numerical modelling of water/wastewater treatment processes.

Contact: Younggy Kim

younggy@mcmaster.ca

Developing sensors to detect/monitor bacteria in water for real-time and on-site water pollution detection/monitoring.

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Contact: Chang-qing Xu

cqxu@mcmaster.ca

Development of environmental sensors.

Contact: Ravi Selvaganapathy

selvaga@mcmaster.ca

Focus on water and environmental risk management. By leveraging advanced machine-learning and probabilistic techniques, her team introduces novel uncertainty quantification methods to water and environmental modeling and develop robust tools to support pertinent risk analysis and management.

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Contact: Zoe Li

zoeli@mcmaster.ca

Contact: Charles de Lannoy

delannoy@mcmaster.ca

Contact: Herb Schellhorn

shell@mcmaster.ca