Network‐Scale Dynamics of Alluvial Cover in a Mixed Bedrock‐Alluvial River
Year: 2025
Type: article
Abstract: Limited understanding of how sediment cover varies spatially in mixed bedrock‐alluvial river networks inhibits our comprehension of erosion processes in these systems. This study investigates the complex interactions between channel and sediment properties that control the extent, spatial distribution, and connectivity of alluvial cover in mixed bedrock‐alluvial river networks. Employing a combination of field data, sediment transport modeling, and connectivity analysis, this study aims to understand the key drivers influencing sediment cover patterns at the network scale. Sediment transport simulations using the NetworkSedimentTransporter model explored how varying initial fluvial and channel parameters affect the steady‐state alluvial cover across the River Carron network in the Scottish Highlands. The results demonstrate that increased initial sediment cover, increased sediment supply, and larger grains increased the extent and connectivity of alluvial sections, whereas deeper flow reduced them. In supply‐limited conditions, the spatial distribution of alluvial cover is most sensitive to slope, while in transport‐limited conditions, sediment supply and grain size become more critical. Even at high sediment supply rates, not all reaches achieved full alluviation, suggesting inherent limitations in sediment distribution. Additionally, channel slope was the most significant factor controlling the directional growth of alluvial sections. These findings contribute to the limited research on the controls of alluvial cover at the network scale, thereby improving our understanding of landscape evolution, river management, and habitat conservation of mixed bedrock‐alluvial rivers.
DOI: 10.1029/2024jf007968
Institution: Durham University
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,070
Funder: Horizon 2020 Framework Programme
Award: G6715980057
OpenAlex ID: W4408337203
