PhD in Data-Driven Modeling and Prediction of Wildfires in the Boreal and Arctic

KU Leuven, Belgium
Closing date not specified

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 the 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 causing that they sometimes ‘overwinter’ (link). 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@kuleuven.be


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