LAUSR

Suspended sediment concentrations (SSC) in rivers are variable in time due to interacting soil erosion and sediment transport processes. While many hydro-meteorological variables are correlated to suspended sediment concentrations, interpretation of these correlations in terms of driving processes requires in-depth knowledge of the catchment. Detailed sediment source information is needed to establish the causal linkages between driving processes and variations in SSC. This study innovatively combined sediment fingerprinting with multivariate statistical analyses of hydro-meteorological data to investigate how differential contributions of sediment sources control SSC in response to hydrometeorological variables during high-flow events in rivers. Applied to the River Aire (UK), five sediment sources were classified: grassland topsoil in three lithological areas (limestone, millstone grit and coal measures), eroding riverbanks, and street dust. A total of 159 suspended sediment samples were collected during 14 high-flow events (2015-2017). Results show substantial variation in sediment sources during high-flow events. Limestone grassland and street dust, the dominant contributors to the suspended sediment, show temporal variations consistent with variations in total SSC, and are correlated with precipitation and discharge shortly prior and during high-flow events (i.e. fast mobilisation to and within river). Contrarily, contributions from millstone and coals grassland appear to be driven by antecedent hydro-meteorological conditions (i.e. lag-time between soil erosion and sediment delivery). Riverbank material is poorly correlated to hydro-meteorological variables, possibly due to weak source discrimination or the infrequent nature of its delivery to the channel. Differences in source-specific drivers and process interactions for sediment transport demonstrate the difficulty in generalising sediment transport patterns and developing targeted suspended sediment management strategies. While more research is essential to address different uncertainties emerging from the approach, the study demonstrates how empirical data on sediment monitoring, fingerprinting, and hydro-meteorology can be combined and analysed to better understand sediment connectivity and the factors controlling SSC.