Using particle size distributions to fingerprint suspended sediment sources—Evaluation at laboratory and catchment scales

Abstract

Applications of sediment source fingerprinting studies are growing globally despite the high costs and workloads associated with the analyses of conventional fingerprint properties on target sediment samples collected using traditional methods. To this end, there is a need to test new fingerprint properties that can overcome these challenges. Sediment particle size could potentially contribute here since it is relatively easy to measure but, until now, has rarely been deployed as a fingerprint itself. Instead, particle size has been used to ensure that source and target sediment samples are more directly comparable on the basis of the fingerprints used. Accordingly, this work examined whether particle size distributions (PSDs) could be used as a reliable fingerprint for apportioning sediment sources, in combination with a grain size un-mixing model. Application of PSDs as a fingerprint was tested at two scales: (i) in a laboratory setting where soil samples with known PSDs were used to generate artificial mixtures to evaluate un-mixing model results, and (ii) a catchment setting comparing PSDs in a confluence-based approach to test if downstream target sediment PSDs could be un-mixed into the contributions of sediment coming from an upstream and a tributary sampling site. Laboratory results showed that the known proportions of the two, three and four soil samples in the artificial mixtures were predicted accurately using the AnalySize grain size un-mixing model, giving average absolute errors of 9%, 8% and 6%, respectively. Catchment results showed variable performances when comparing un-mixing results with sediment budget estimations, with the best results obtained at higher discharge values during storm runoff events. Overall, our results suggest the potential of using PSDs for estimating contributions of sediment sources delivering SS with distinct PSDs when sources are located at short distance to the downstream sampling site.

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Identifiers

ORCID for Niels F. Lake: orcid.org/0000-0002-5909-2005

ORCID for Peter J. Shaw: orcid.org/0000-0001-9044-1069

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