Abstract
Gravel-bed rivers draining mountainous forested headwater regions are critically important for drinking water supply and ecological integrity. These rivers, however, have been increasingly impacted by intensifying anthropogenic and natural (especially climate change exacerbated) landscape disturbances that commonly increase hillslope/channel connectivity and the delivery of cohesive sediment (<63 μm) and associated pollutants. Despite the known deleterious threats of excess cohesive sediments, there is still limited understanding of their transport and intra-gravel storage due to the complexities of such processes. Accordingly, the objectives of this study were to: i) calibrate and validate a semi-empirical cohesive sediment transport model (RIVFLOC) using the observations from flume experiments; ii) estimate the intra-gravel storage capacity for cohesive sediment with the calibrated model based on the field dataset (collected in two field campaigns between 2019 and 2021), and; iii) investigate mechanisms of cohesive sediment transport dynamics in this gravel-bed river, identifying knowledge gaps and areas for future research. Our results showed that despite the increased floc settling velocity, deposition was hindered by turbulent flow fields. The model predicted that ~60 % of upstream cohesive sediment would ingress within the 10 km study reach due to the flow interaction with the gravel-bed. Despite the agreement between flume and field observations on ingress rates and preferential ingress of coarser (~100 μm) flocs, notable differences were observed between modelled and field datasets, highlighting unknowns regarding cohesive sediment exfiltration without framework mobilization. This study uniquely integrates field measurements, flume experiments, and modelling strategies to evaluate the transport and fate of cohesive sediment in a gravel-bed river. Accordingly, our findings advance current knowledge on the mechanistic understanding of cohesive sediment transport and highlight future research directions.
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