Abstract

Fine sediment availability and channel hydraulics are two of the primary controls on the ingress of fine sediment into gravel river beds. A novel dataset consisting of fine sediment ingress measurements coupled with high-resolution turbidity and discharge time series, was analysed to investigate relations between ingress, discharge and turbidity. Discharge and turbidity demonstrated a weak association with each other, and their relations with fine sediment ingress were relatively weak. An alternative, but widely applied ‘redundancy’ approach was investigated that focused on key metrics, or facets, of the discharge and turbidity time series and their association with fine sediment ingress. Principal component analysis was used to distil the most important facets driving variation in the discharge and turbidity datasets and these were then used as independent variables in regression models with sediment ingress as the dependent variable. These models accounted for a larger amount of the statistical variation in sediment ingress over time than discharge and turbidity time series. Facets of the turbidity time series were found to be the most effective explanatory variables. The results suggest that this approach could be valuable and justify its application and testing across a range of river types in different hydrological and sedimentary settings. Application of this method could improve our generic understanding of what controls ingress at larger spatial and temporal scales and therefore complements process-based approaches, which is vital for the development of fine sediment management strategies.

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