Grabowski, Robert C.Hess, Tim M.Vercruysse, Kim2019-07-152019-07-152017-09http://dspace.lib.cranfield.ac.uk/handle/1826/14345Human activity has disturbed the natural suspended sediment (SS) balance and the associated geomorphological and ecological functioning of many rivers. Yet, predicting and managing SS is challenging because the processes controlling SS transport over multiple timescales are not well understood. The aim of this research is to improve the prediction and management of SS by investigating the hydro-meteorological and catchment processes driving temporal variation in SS transport. The objectives are (i) to assess SS transport over multiple timescales to uncover the scale-specific processes and process interactions that determine temporal variation in SS transport; (ii) to apply and test a sediment fingerprinting approach based on infrared spectrometry to identify dominant SS sources; and (iii) to evaluate the role of variations in sediment sources in controlling SS concentrations in response to hydro-meteorological variables. The research was carried out in the River Aire, UK. The findings show that SS transport in the River Aire is highly event-driven and supply-limited, while also being influenced by long-term changes in land use. Over the studied period, the dominant SS source was grassland, and its contribution was mainly controlled by antecedent moisture conditions. On the contrary, urban street dust, which was also a dominant sediment source, was less hydrologically driven. The research also demonstrated that while infrared-based fingerprinting can be used to estimate SS source contributions with acceptable model errors, sediment apportionment is strongly influenced by the degree of discrimination between source classes. In order to improve methods to quantify SS transport and sources, and to identify sediment management needs, this research underscores the need to (i) recognise different timescales of SS transport to identify the underlying processes; (ii) develop better approaches for source classification and discrimination to accurately represent the sediment in rivers; and (iii) establish further knowledge on sediment sources variations in different contexts and over multiple spatial and temporal scales.en© Cranfield University, 2015. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.Timescalefluvial geomorphologyconnectivityhydro-meteorologysediment fingerprintingprocessesThesis