Quantifying sediment-associated metal dispersal using Pb isotopes: application of binary and multivariate mixing models at the catchment-scale

Abstract

In this study Pb isotope signatures were used to identify the provenance of contaminant metals and establish patterns of downstream sediment dispersal within the River Maritsa catchment, which is impacted by the mining of polymetallic ores. A two-fold modelling approach was undertaken to quantify sediment-associated metal delivery to the Maritsa catchment; employing binary mixing models in tributary systems and a composite fingerprinting and mixing model approach in the wider Maritsa catchment. Composite fingerprints were determined using Pb isotopic and multi-element geochemical data to characterize sediments delivered from tributary catchments. Application of a mixing model allowed a quantification of the percentage contribution of tributary catchments to the sediment load of the River Maritsa. Sediment delivery from tributaries directly affected by mining activity contributes 42-63% to the sediment load of the River Maritsa, with best-fit regression relationships indicating that sediments originating from mining-affected tributaries are being dispersed over 200 km downstream.