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2018 PhD Opportunities

Ph.D. students are sought for a research project entitled, “Linking stream network process models to robust data management systems for the purpose of land-use decision support “

The research project is to develop a digital platform to improve the science, communications, and outcomes surrounding land-use decision making in river networks.  The proposed system is a ‘big data’ effort at the University of Waterloo to combine monitoring and modelling efforts from the ecological restoration and river hydraulics groups with a data management platform created by the computer systems group that supports environmental decision making.  Funding has been secured through the Global Water Futures initiative ( with the overall goal of forecasting, preparing for and managing water futures in the face of dramatically increasing risks.

As collective systems, rivers integrate the incremental land cover changes from pervious natural or agricultural surfaces to impervious urban cover.  Common impacts include increased flooding, unstable streams, and degraded aquatic ecosystems, which together describe an ‘urban stream syndrome’.  People have developed strategies to mitigate these effects, but many questions remain, particularly in the face of a changing climate.  Deleterious impacts are poorly quantified, climate change increases risk, and the benefits of mitigation strategies remain uncertain.  Given the capital expense and importance for long-term finances and the ecological sustainability of the rivers, it is essential to obtain a better understanding of disturbance and response in these environments. Informed decision making would draw from diverse fields of biology, water chemistry, morphology, hydrology, and hydraulics, but available information is typically siloed, with little to link it across disciplines and between stakeholders

Stakeholders need a spatial decision support system that will gather and analyse stream network information to support land-development decision making.  Scientifically, such a system is needed to understand watershed-scale adjustment processes and fuel a search for solutions that address not just isolated symptoms of the urban stream syndrome, but also the root causes of physical and ecological imbalances and degradation.  For such a system to be effective it needs to be built upon a robust data management framework, incorporate analysis modules based on the best supported science in the respective subfields, allow users to interact with the data, and formalize outputs that can be used to support decision making.  By providing a data management and modelling system that connects raw data with relevant results for a variety of stakeholders, the system will allow users to visualize and compare the long-term and larger scale impact of local land use and stream management decisions on channel morphology and ecology, while also considering the additional risk posed by climate change.  Supported decisions include choices on where and how to build cities, what hydrological or ecological mitigation strategies to choose, and where/what restoration would be the most effective.  Much of the work will be done through case studies due to the present-day needs of the stakeholders and the availability of rare data sets in these catchments from previous work.

Currently we are looking for 4 PhD students.  Our vision is to treat this group as a team by encouraging them to follow a similar timeline to their degrees and co-locating the office space on campus.  Regular workshops and strategy meetings will be held with other GWF researchers and system developers to brainstorm ideas, spark creativity, clarify the methods, and forge the transdisciplinary links that will allow this nexus-type system to produce transformative results. The students will be co-supervised across departments to ensure adequate training in computer science, hydraulics, and ecology.  They will be encouraged to enroll in the Collaborative Water Program at UW to expose them to a wide range of water-related fields.  Students will be encouraged to complete industrial internships to develop a first-hand appreciation of the problem of decision making in for river management, disseminate knowledge to the partners, and improve the practical impact of the project.

Students based in ERS:

·         PhD in ecological modelling at a stream network scale.  Activities 3, 4, and 6. Home department in Environment, Resource, and Sustainability with co-supervision in Civil and Environmental Engineering.  (contact Stephen Murphy)

·         PhD in adaptive management modelling. Activities 4, 5, and 6.  Home department in Environment, Resource, and Sustainability with co-supervision in Computer Science. (contact Simon Courtenay and Stephen Murphy jointly as Simon is on sabbatical)


Student based in Engineering, co-supervised in ERS

·         PhD in modelling of stream network sediment transport and morphological change.  Experience with river engineering, fluvial geomorphology, sediment transport, computer programming, hydrologic and hydraulic modelling, and stormwater management are assets.  Home department Civil and Environmental Engineering with co-supervision in Environment, Resource, and Sustainability


Student based in Computing Science and in Engineering

·         PhD in ontology and decision support system design. Activities 1 and 5. Home department in Computer Science with co-supervision in Civil and Environmental Engineering.


If you are interested, please contact one of the researchers from the list below; as this is posted in the ERS webspace, the most relevant projects and contacts are those from ERS itself.

ERS contacts:

Stephen Murphy

Professor & Director, School of Environment, Resources & Sustainability
University of Waterloo


Simon Courtenay

Professor, Canadian Rivers Institute at the School of Environment, Resources and Sustainability

University of Waterloo


(Collaborating professors)

Bruce MacVicar

Associate Professor, Civil and Environmental Engineering

University of Waterloo


Paulo Alencar

Adjunct Professor, Cheriton School of Computer Science

University of Waterloo


Don Cowan

Distinguished Professor Emeritus, Cheriton School of Computer Science

University of Waterloo