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Free keywords:
validation method; glacial isostatic adjustment; south-west Fennoscandia; Hudson Bay; sea-level indicators, probability density function
Abstract:
Glacial isostatic adjustment (GIA) is the ongoing response of the viscoelastic solid Earth, oceans and the gravitational field to the previous burden of the ice loads. The Earth’s surface was once covered with massive ice sheets, and melting of these ice sheets is still reshaping coastlines and affecting sea-level. To reconstruct former sea level and be able to predict future changes, it is necessary to constrain the rheological properties of the Earth’s structure. Widely used data to constrain Earth’s interior are sea-level indicators. In the first part of the thesis, we propose a statistical method that quantifies a relationship between the sea-level indicator and a relative sea level in order to compare it to GIA predictions. A statistical method is based on consideration of spatial and temporal probability density functions, derived from the age and elevation of each indicator. This method allows a more rigorous approach to validation with sea-level data and possibility to include low-quality data. We verified method performance in the Hudson Bay, Canada as a test run before applying it to the SW Fennoscandia. SW Fennoscandia identifies as an area where lateral heterogeneity is likely to exist. The south-western part of Fennoscandia lies on the crustal boundary called the Trans-European Suture Zone (TESZ), or the Tornquist Zone. GIA models have two representations of Earth’s structure; radially symmetric (1D), where the rheology only varies vertically, and lateral or 3D variations of viscosity structure. In this thesis, we compare glacial isostatic adjustment reconstructions with both representations of the rheology. Results from the 1D model show variations in the viscosity structure between the area near to the centre of the former ice sheet and the areas at the margin of the ice sheet. Hence, we verify the importance of including lateral variations in GIA models in this region. Application of 3D models displays the sensitivity of model parameters to crustal deformation. German Baltic coast yields thinner lithosphere than TESZ region and near-centre region. Additionally, in the TESZ region, we notice a steep increase in viscosity of the asthenosphere and upper-mantle. Furthermore, we compared two different global ice histories (ICE5G and ICE6G_C) and concluded that the marginal areas are more sensitive to different deglaciations, and we propose to use regional ice histories to constrain GIA models better. Apart from the new statistical method, this study sets a ground for future GIA studies in complex tectonic regions and demonstrates the importance of including laterally heterogeneous Earth structure in GIA models.
