Characterizing Past and Future Soil Water Stress in Quebec Forests: Enhancing Resilience to Drought
A PhD project to model soil water stress in Quebec’s managed forests using climate dynamics and hydrological modeling.
Best for:Best for candidates with a master’s in forestry, environmental science, or related fields, strong programming skills (Python/R/Matlab), and experience in hydrological modeling or data analysis.
Overview
This PhD position at Université Laval focuses on assessing and predicting soil water stress in Quebec’s forested regions, which cover over 50% of the province. With climate change intensifying drought risks, the project aims to simulate water and energy exchanges between soil, forest, and atmosphere using the CLASSIC land-surface model. The research will adapt the model to Canadian conditions, validate it against experimental data, and generate insights to support sustainable forest management and climate-resilient decision-making. Collaboration with Québec’s Ministry of Natural Resources and Forests will ensure practical applications for forest resource managers.
What you'll do
- Develop and validate the CLASSIC land-surface model for simulating water and energy exchanges in Quebec’s forested ecosystems.
- Conduct spatial and temporal analyses of soil water stress using climate data and experimental site observations.
- Adapt the model to regional conditions in Eastern Canada, ensuring accuracy and relevance for forest management.
- Collaborate with Québec’s Ministry of Natural Resources and Forests to translate research findings into practical forestry policies.
- Present research findings at academic conferences and publish results in peer-reviewed journals.
- Contribute to interdisciplinary discussions on climate change impacts and sustainable forestry practices.
Requirements
Degree required: Master’s degree in forestry, environmental engineering, physics, environmental sciences, or geography
Degree offered: PhD in Water Engineering
Language: English; proficiency sufficient for academic research and collaboration
Instruction: French (primary) and English (secondary)
- Proven experience in data analysis and hydrological modeling
- Proficiency in programming languages such as Python, R, or MATLAB
- Strong analytical and problem-solving skills
- Ability to work collaboratively in interdisciplinary teams
- Open to international applicants
- No specific residency or age restrictions mentioned
Funding & terms
How to apply
Deadline: 2026-11-15
Applicants must submit their CV, a cover letter outlining their motivation and qualifications, and a research proposal (if required) through the ABG France portal. Additional documents such as academic transcripts and letters of recommendation may be requested during the evaluation process.
- CV
- Cover letter
- Research proposal (if applicable)
- Academic transcripts (BSc + MSc)
- Letters of recommendation (if required)
Contact
First Last· PhD Supervisor
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