Joint inversion of physical and chemical state variable data within a multi-model subsurface hydrology framework

Promoter

Kristine Walraevens, (Universiteit Gent (UGent)), kristine.walraevens@ugent.be

SCK•CEN Mentor

Rogiers Bart, brogiers@sckcen.be, +32 (0)14 33 31 23

Expert group

Engineered and Geosystems Analysis

SCK•CEN Co-mentor

Beerten Koen , kbeerten@sckcen.be , +32 (0)14 33 32 41

NIRAS/ONDRAF Mentor

Wouters Laurent

Short project description

Hydrogeological models are often calibrated solely on hydraulic heads. Collection of other observations, such as temperature and flux measurements, and age tracer concentrations would help the calibration an uncertainty estimatiion of groundwater flow and solute transport models. On the example of the Neogene aquifer in the Nete catchment, the PhD thesis shall focus on integrating the new types of observations in coupled nummerical models at the catchment scale. The main innovative aspects are: (1) sampling, analysis and integration of 4He tracer concentration (constraining flow in the deep aquifers) along with the young age tracers; (2) perform spatially distributed material parameter inversion, to deal with heterogeneities which are not part of the conceptual model, across coupled models. The modelling tool which shall be used is this year’s new MODFLOW release (MODFLOW 6), which allows for including multiple models, both loosely or thightly coupled, in a single simulation.

The minimum diploma level of the candidate needs to be

Master of industrial sciences , Master of sciences , Master of sciences in engineering

The candidate needs to have a background in

Physics , Mathematics
Before applying, please consult the guidelines for application for PhD.