[ES_JOBS_NET] PhD in Data-Driven Modeling and Prediction of Wildfires in the Boreal and Arctic (KU Leuven, Belgium)

[Michel Bechtold]

Title:
PhD in Data-Driven Modeling and Prediction of Wildfires in the Boreal 
and Arctic (KU Leuven, Belgium)

The Department of Earth and Environmental Sciences at the KU Leuven 
(Belgium) invites applications for a 4-year PhD position on the 
data-driven modeling and prediction of wildfires in the boreal and 
arctic zone. The PhD student will advance our understanding of the 
occurrence of wildfires in peatland-rich landscapes and make predictions 
of future occurrence in the course of climate change.

Background:
During the last decade, the Boreal and Arctic experienced several dry 
spells and heat waves that led to widespread wildfire occurrence over 
forests and peatlands. The interplay of flaming (dominantly biomass) and 
smoldering (dominantly peat) combustion makes peatland wildfires very 
persistent, even 'overwintering' (link 
<https://medium.com/sentinel-hub/zombie-fires-in-the-arctic-clickbait-or-real-a3eec97a70be>). 
Drying as a result of climate change and human activity already led to 
more frequent, larger and more severe peatland wildfires. Peatlands play 
a critical role in wildfire occurrence in peatland-rich regions in 
general, because peatlands can disrupt the "fuel landscape" when wet, 
but connect fuels when dry. More peatland fires will exacerbate global 
warming due to the instantaneous release of ‘legacy soil carbon’ that 
accumulated over millennia, and aggravate other adversities for the 
environment and humankind, such as respiratory diseases with the 
inhalation of noxious smoke and costs of extensive firefighting.

Project overview:
The project PEATBURN funded by FWO aims at fundamentally improving the 
large-scale modeling of peatland wildfires by the integration of crucial 
novel information about the subsurface fuel (=peat!) moisture conditions 
obtained from satellite data assimilation. Key objectives of PEATBURN are
- to further advance soil moisture satellite data assimilation over 
peatlands,
- to improve fire danger rating systems used in fire management, and
- to reveal unique large-scale insights into links between peatland 
moisture and wildfires.
The PhD student will create and analyze large data sets on wildfires and 
controlling factors (e.g. meteorology including lightning probability, 
vegetation, soil, multiple satellite observations and retrievals, future 
predictions of climate and land cover/land use change), and develop a 
data-driven modeling approach using machine learning techniques.

The research team:
The PhD student will be part of the land surface modeling and data 
assimilation research group at KU Leuven, Department of Earth and 
Environmental Sciences. PEATBURN is led by Dr. Michel Bechtold and Prof. 
Gabrielle De Lannoy. The PhD student will further collaborate with an 
international team of wildfire experts.

Further information on this and other vacancies of the research group, 
on the required profiles and on how to apply can be found here:
https://www.kuleuven.be/personeel/jobsite/jobs/55540142

Applications are continuously reviewed. The position can be filled by a 
suitable candidate at any time. Preferred starting date is beginning of 
September but a later date can be negotiated.

For more information, please contact Dr. Michel Bechtold, tel.: +32 16 
32 01 67, e-mail: michel.bechtold at kuleuven.be

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