Modeling granulometric, mineralogical, and geochemical composition of sediments: A quantitative tool for predicting sediment composition and reconstructing sediment provenance

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Numerical modeling has become a powerful tool in several fields of geosciences, but a comprehensive model to describe the composition of clastic sediments is still lacking. This study aims at developing a numerical-statistical model that allows for describing quantitatively the petrographic, chemical, and granulometric changes related to the overall transfer of material from the original source rock to the sediment at the final site of deposition. These relative changes of sediment composition (as compared to the initial source) are largely controlled by tectonics, physiography, climate, and transport energy. The model will be suited for both inductive and deductive approaches. Potential applications of the model are, for example, the prediction of sediment composition under well-known geologic conditions and the reconstruction of sediment provenance based on final composition. To achieve this general goal, it needs the successful execution of two subgoals: (1) the broadening of our theoretical understanding of so-called multi-way compositions (e.g., data sets reporting grain size, chemistry, and mineralogy of sediment samples) and (2) modeling of multi-way compositional change in several case studies comprising both literature data as well as new datasets obtained within the frame of this project.