Multi-parameter fingerprinting of sediment sources: Uncertainty estimation and tracer selection

Numerous studies have shown how different physical and chemical properties of sediments may be used as tracers in the identification of sediment contributing source areas. However, the application of fingerprinting techniques is subject to significant uncertainty due to the limited sampling of naturally variable source groups. Previous applications have not accounted for sampling uncertainties in the measurement of the different trace properties in the different source areas and sinks. In this study, a statistical framework is employed to explicitly assess such uncertainties. The developed framework is applied to both real and synthetic case studies. It is subsequently shown that confidence intervals on resultant contributing source areas may be robustly derived. The developed framework therefore provides a method through which typical sampling strategies may be assessed. Additionally, optimal combinations of multiple trace properties may be identified through a sequential analysis of tracer permutations providing insight into appropriate tracer selection.