The active layer thickness has become an important indicator in climate change research as permafrost degradation has long been documented. The thawing of permafrost causes the release of greenhouse gases accelerating Arctic warming. Monitoring and quantifying spatial and temporal changes of the active layer are challenging but crucial for reliable climate projections. Geophysical methods offer a non-invasive investigation of electrical properties and their distribution in permafrost areas, revealing phase transitions from water to ice. Subsurface electrical resistivity images can be obtained through inversion of electromagnetic data, yet are inherently ambiguous because of the ill-posed nature of the inverse problem. Since regularization methods offer the possibility to stabilize the inversion, lateral and spatial constraints are incorporated in the inversion algorithm to produce quasi-2D and quasi-3D subsurface models. The developed methodology is evaluated based on synthetic data sets to determine suitable inversion parameters, which are subsequently applied to a field example from the Seward Peninsula, Alaska. Laterally constrained inversion methods based on a few-layer starting model succeed in resolving sharp interfaces in quasi-layered environments. In more complex settings minimum-structure models can retrieve accurate subsurface representations leveraging on vertical and horizontal smoothness constraints. Enforcing lateral and spatial consistency between neighboring soundings thereby yields a similar degree of model smoothness. The inverted field data confirms the conclusions drawn from the synthetic study, as meaningful three-layered models with regard to electrical resistivities are recovered, indicating resistive snow overlying the conductive active layer and highly resistive permafrost. However, the inversion results imply that the snow layer has a significant effect on the predicted model. The implemented constraints help in reducing the ambiguity of the models, but uncertainties introduced by limited data availability cannot be overcome. The potential of adopting spatial and lateral constraints to the inversion is shown, although it becomes evident that additional a priori information needs to be integrated in the objective function in order to comprehensively image the active layer.

Concrete is the most widely used building material in the world and its stability assessment is of utmost importance for society. Ultrasonic measurements are one tool for investigation of concrete stability. The goal of those measurements is the derivation of damage sensitive parameters. The way ultrasound diffuses through concrete is affected by cracks in the specimen, so the description of diffusion can show potential damage indicators. Furthermore, the velocity of the wave propagation changes in damaged specimen. With the analysis of the late part of the seismic signal, small velocity changes can be detected and possibly linked to damage. When concrete is loaded, stress and strain change. This is linked non-linearly to velocity changes with the acoustoelastic theory, defining classical and non-classical non-linear parameters as possible damage indicators. In this work, the aforementioned methods and measures are applied to data from loading experiments on specimen of the size and structure of reinforced bridge girders. Ultrasound measurements with embedded sensors, as well as strain measurements were conducted until the girder failed. The analysis shows, that, while the diffusion of ultrasound can be approximated and parameters can be extracted, those parameters are only damage sensitive to some extent and at stages the specimen already shows damages. The velocity changes calculated with coda wave interferometry show a better response when damages appear and local anomalies give information about the location of damaged and extensively strained areas. A link between strain and velocity change shows that the non-linear relation between both measurements can be approximated with a second order polynomial according to the acousto-elastic effect. The parameters of this polynomial are the classical non-linear parameters and accord with literature values. A combination of all three applied methods shows good potential for the setup of a monitoring framework. IDEA League Joint Master's in Applied Geophysics: Delft University of Technology; ETH Zurich; RWTH Aachen University.