Funded PhD project on drought monitoring and forecasting in Morocco

Climate change is increasing pressure on the world's water resources. Arid regions such as North Africa are most vulnerable, as water resources are already limited. Morocco is particularly affected by the intensification of drought, which is already causing major water shortages, requiring optimized resource management in the face of climate change. At present, Morocco has no drought early warning system (DEWS), which would enable water and agricultural management practices to be adapted to drought hazards. The aim of this PhD project is therefore to develop a drought monitoring and drought early warning system for the Oum Er Rbia basin, one of Morocco's "granaries", in order to strengthen the governance and resilience of its population to the impacts of water scarcity. The candidate will develop multi-source indicators (climatic, hydrological, vegetation, observational and satellite) that best reflect the impacts of drought on populations. He or she will develop and test seasonal forecasting approaches for these indicators based on artificial intelligence algorithms. Tasks will also include field visits to carry out surveys of farmers and water users in the Oum Er Rbia agricultural zone. This Ph.D. project will be co-supervised between the Department of Environmental Sciences at UQTR in Canada and Mohammed VI university in Morocco.

Skills and qualifications sought:
- Master's degree in geography, science or engineering
- Data processing and analysis skills (programming language: R, Matlab, Python or other)
- Skills in geomatics and remote sensing
- Ability to work as part of a team
- Good command of written and spoken English

If interested, please send a CV, transcript and cover letter to Christophe Kinnard (christophe.kinnard@uqtr.ca).

Deadline:  30 November 2023.

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Doctoral thesis on the spatial heterogeneity of Arctic snow cover

Climate warming is transforming northern ecosystems. Among these transformations, the snow cover represents the component of the cryosphere that is most sensitive to climate and whose changes affect the stability of permafrost. The projection of climate impacts on northern ecosystems requires a better understanding and representation of snow cover within land surface models. This is a challenge because of the high spatial heterogeneity of snow cover in the Arctic, where unvegetated surfaces and periglacial microtopography are conducive to snow transport by wind and accumulation in depressions. Current snow cover projections for the century project do not adequately consider the effects of spatial heterogeneity of snow cover in Arctic environments.

This PhD project aims to develop new methods to represent spatial heterogeneity of Arctic snow cover within land surface models. Spatial heterogeneity parameterizations will be developed from drone observations collected at Bylot Island (73°N) and around the community of Kangirsualujjuak (58°N), and then on a larger scale from the Sentinel 2 satellite image collection. The new parameterizations will then be implemented in the CLASSIC land surface model, validated by field observations. Sensitivity experiments of the model to the representation of spatial heterogeneity will then be performed.
A grant of 22 000 $CAN/year is available for 4 years. The project will begin in May 2023. The student will be based at the Glaciolab of the Université du Québec à Trois-Rivières (www.uqtr.ca/glaciolab), and will be directed by Professor Christophe Kinnard (UQTR/CEN). The PhD candidate will work within a pool of researchers and students associated with the northern pole of the Centre de recherche sur les interactions bassins versants - écosystèmes aquatiques (RIVE) at UQTR and the Centre d'études nordiques (CEN), an inter-university strategic research cluster.

Skills sought:
- Master's degree in geography, science or engineering (completed or near completion)
- Good aptitudes in numerical data analysis (programming language: R, Matlab, Python or other)
- Skills in geomatics
- Ability to work as part of a team and in remote field areas
- Good knowledge of English and/or French, oral and written

If interested, please send a CV, transcripts and motivation letter to Christophe Kinnard (christophe.kinnard@uqtr.ca). Applications from under-represented groups are welcome.

Deadline: none