Joint inversion of different data sets is an increasingly popular strategy because it helps to reduce uncertainties and ambiguities in data analysis and interpretation. In this study, we use a particle swarm optimization (PSO) based inversion strategy to jointly invert crosshole P-wave and GPR traveltime data sets for the detailed characterization of near-surface sediments at a well-constrained test site in Horstwalde, Germany. At this site, the subsurface is characterized by sand- and gravel-dominated glaciofluvial sediments and exhibits a well-defined layering at the scale of our crosshole data, which allows for using a flexible layer-based model parametrization. Our inversion strategy includes the generation and analysis of a representative ensemble of acceptable models, which allows us to appraise uncertainties and non-uniqueness of the inverted velocity models. Analysing the final ensemble and comparing the resulting velocity models with borehole and direct-push (DP) data, demonstrates that the layered structure, which was found by PSO-based inverson, is in reasonable agreement with major variations in the borehole and DP-parameters. I am a PhD student and I would like to be considered for the AGAP-Quality Award.


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