Uncertainty assessment in suspended sediment fingerprinting based on tracer mixing models: a case study from Luxembourg

Abstract

The primary purpose of this paper is to explore the various sources of uncertainty associated with the use of the fingerprinting approach, based on multivariate mixing models, to establish suspended sediment sources. Model uncertainty has been investigated using a Monte Carlo simulation technique. A key aim of the study is to assess the relative importance to the uncertainty of the output of: (1) the number and type of tracers included in the mixing model, and (2) the spatial variability of the tracer signatures of individual sources. The results obtained showed that the main source of uncertainty was the number of tracers included in the model, and the spatial variability of the tracer signatures associated with an individual source, whereas the types of tracers included were shown to be of lesser importance. The various assessments of the uncertainty associated with sediment fingerprinting were, however, conditioned by the assumptions made. This study demonstrates that the precision and coherence of source ascription partitioning can be improved by: (I) incorporating tracer weightings to reflect the spatial variability of source signatures, and (2) constraining the mixing model to reflect current process understanding. Despite the uncertainties involved, the proposed methodology provides a formalized procedure by which sediment source contributions can be readily established using tracer mixing models.