Hydrological response of snow-dominated catchments to winter rainfall events

Project

In winter, rain-on-snow (ROS) events can have catastrophic consequences for riverside populations. The combination of rainwater and snowmelt can indeed lead to major floods. The catchment response to such an event depends on multiple factors, which makes its modeling very complex.

The proposed project aims to study the hydrological impact of winter ROS events in a humid continental climate. We are interested in better understanding the impact of initial snowpack conditions (temperature, height, structure), vegetation and underlying soil thermal regime on the routing of liquid water from its entry into the snowpack to the catchment outlet. The methodological approach is based on the analysis of original data collected across study watersheds and on intensive snow sampling campaigns using cutting-edge technologies. The evaluation and development of models simulating snowmelt runoff during these events is also planned. This project is partially funded by the Quebec Ministry of Public Safety.

Funding of $24,000/year available for 4 years. Possible start in September 2022 or January 2023. The student will be advised by Prof. Daniel Nadeau (Université Laval) and coadvised by Prof. Michel Baraer (École de Technologie Supérieure).

Institution

Université Laval (UL) is the oldest French-speaking university in North America. UL is a comprehensive university hosting some 48,000 students—a quarter of them graduates—as well as 17 faculties, 60 departments and schools, and nearly 400 undergraduate and graduate programs in every field of knowledge. Université Laval offers strong graduate programs in northern research. Although graduate studies at Université Laval can be carried out in English, the candidate will be strongly encouraged to learn French.

Required qualifications

• MSc degree in Engineering, Physics, Environmental Sciences or Geography
• Experience in data analysis and field work
• Motivation, teamwork capabilities and communication skills
• Programming in Python, R, MATLAB or equivalent
• Driver’s licence

Application

Please send an email to Prof. Daniel Nadeau (This email address is being protected from spambots. You need JavaScript enabled to view it.) and Prof. Michel Baraër (This email address is being protected from spambots. You need JavaScript enabled to view it.) with your CV, a short motivation letter, examples of previous research (M.Sc. thesis or published papers), as well as the names of two referees.