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Increasing complexity in human-environment interactions at multiple watershed scales presents major challenges to sediment source apportionment data acquisition and analysis. Herein, we present a step-change in the application of Bayesian mixing models: Deconvolutional-MixSIAR (D-MIXSIAR) to underpin sustainable management of soil and sediment. This new mixing model approach allows users to directly account for the ‘structural hierarchy’ of a river basin in terms of sub-watershed distribution. It works by deconvoluting apportionment data derived for multiple nodes along the stream-river network where sources are stratified by sub-watershed. Source and mixture samples were collected from two watersheds that represented (i) a longitudinal mixed agricultural watershed in the south west of England which had a distinct upper and lower zone related to topography and (ii) a distributed mixed agricultural and forested watershed in the mid-hills of Nepal with two distinct sub-watersheds. In the former, geochemical fingerprints were based upon weathering profiles and anthropogenic soil amendments. In the latter compound-specific stable isotope markers based on soil vegetation cover were applied. Mixing model posterior distributions of proportional sediment source contributions differed when sources were pooled across the watersheds (pooled-MixSIAR) compared to those where source terms were stratified by sub-watershed and the outputs deconvoluted (D-MixSIAR). In the first example, the stratified source data and the deconvolutional approach provided greater distinction between pasture and cultivated topsoil source signatures resulting in a different posterior distribution to non-deconvolutional model (conventional approaches over-estimated the contribution of cultivated land to downstream sediment by 2 to 5 times). In the second example, the deconvolutional model elucidated a large input of sediment delivered from a small tributary resulting in differences in the reported contr

Fine-grained sediment is perhaps the most widespread and pervasive contaminant in aquatic systems reflecting its role in influencing the quality of the water (e.g., turbidity, vector of chemicals and other pollutants) and its detrimental effect on infrastructure (e.g., dams, turbines) and aquatic habitats (e.g., salmonid spawning grounds) through sedimentation. Determining the sources of fine-grained sediment thus represents an important requirement for watershed and coastal management, as well as for understanding the evolution of landscapes and ocean basins. Sediment source fingerprinting utilizes the diagnostic physical, chemical and biological properties (i.e., tracers) of source materials to enable samples of collected sediment to be apportioned to these sources. This review examines the development of the technique within the earth and ocean sciences, focusing mainly on agricultural landscapes. However, the development of new tracers, such as compound-specific stable isotopes, has allowed the technique to be applied in a growing number of environmental settings including forested (including wildfire-impacted forests), urban and estuarine/coastal settings. This review also describes other applications of the fingerprinting approach such as geoarchaeological (e.g., archaeological site formation), forensic (e.g., identifying the sources of soil/sediment particles in criminal investigations) and human health (e.g., identifying the sources of airborne particulate matter, PM2.5) applications. Identifying commonalities in methods and approaches between environments and disciplines should foster collaboration and the exchange of ideas. Furthermore, refinement of the sediment source fingerprinting technique requires that several methodological issues be addressed. These methodological issues range from the initial sampling design to the interpretation of the final apportionment results. This review also identifies and assesses these methodological concerns.

Mining represents a major source of metal contamination for fluvial systems worldwide. Monitoring and understanding the effects on downstream water and sediment quality is essential for effective management of active and abandoned mine sites. This study aims to determine the downstream effects of the abandoned, small-scale hydraulic Black Creek gold mine on the geochemistry of fine (