Dynamic modelling of Soil-Vegetation-Atmosphere Transfer (SVAT) in perennial ecosystems (PhD)

Dynamic modelling of Soil-Vegetation-Atmosphere Transfer (SVAT) in perennial ecosystems (PhD)


Long-lived radionuclides released from an underground nuclear waste repository may reach the surface ecosystem via the groundwater and, therefore, constitute a potential risk for humans and biota through different pathways. Due to their perennial character, forest vegetation or perennial vegetation systems in general, may affect radionuclide dispersion and distribution in the biosphere in the long-term. The purpose of this project is to contribute to the development of a Soil-Vegetation-Atmosphere Transfer (SVAT) model to quantify this problem, aiding the assessment of long-term risks related to deep nuclear disposal.

The biogeochemical cycling and storage of elements in an ecosystem is dependent on a large number of variables, such as climate, geological heterogeneity, flux of water and vegetation. The interactions between elements and the living and non-living components of an ecosystem play an important role in defining the fluxes and storage of elements in the ecosystem. By describing the dynamic distribution of the elements, it will be possible to describe the potential environmental pathways of key radio-elements on a sounder scientific basis.

As part of the above, an important route for radionuclide distribution in the biosphere is through the water fluxes between the different biosphere compartments, like upper groundwater layers, soil and vegetation. Once assimilated into the vegetation tissues, the radionuclides most likely follow the path of the organic matter; i.e. growth of plant organs and litter fall. A descriptive ecosystem approach, describing pools and fluxes of organic matter and water, will therefore be applied to describe and quantify accumulation and transfer of radionuclides.

In cases where it is not possible to study the actual radionuclides that may originate from nuclear waste, the distribution patterns of naturally occurring radioelements or their stable isotopes will be used to study their long-term behaviour. The chemical behaviour of some radionuclides is similar to other elements, such as macronutrients or trace elements, and hence these analogues will also be utilised for modelling purposes, integrating radioactive and non-radioactive elements into the same model.


The research objective is to develop a modelling tool for the long-term assessment of the influence of a forest vegetation system on the radionuclide dispersion and accumulation in upper-soil layers. To assess the transport and accumulation of bio-available contaminants in a perennial ecosystem, this study aims to make use of a Soil-Vegetation-Atmosphere Transfer (SVAT) modelling approach.

SVAT models explicitly consider the role of vegetation in affecting water, energy and carbon balance by taking into account its physiological properties. These models are often process-based and therefore suitable to simulate the water, energy and carbon fluxes in natural and managed ecosystem under different environmental conditions, including climate change conditions. The rationale for using the carbon and water fluxes is that they can be used as a proxy for the rates at which contaminants will be partitioned in the environment, providing insight into where bio-available radionuclides are to be found. A long-term objective is therefore using this model to help to identify the magnitude of the potential assimilation and accumulation of bio-available radionuclides, as a basis for more detailed transport and exposure modelling at longer time scales.

Required education level of potential candidates: master in sciences, master in engineering sciences

Candidates must have a background in: Bio-engineering, Biology, Other

Please go here to apply: https://webmail.nerc.ac.uk/en/Education-Training/Guidance-for-young-researchers/A-career-in-nuclear-research/,DanaInfo=www.sckcen.be+Yearly-campaign-develop-your-career-in-nuclear-research


Could not connect: Array