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Journal article
Lagging behind: Impact of non-native gravel within a coastal dune system
Aeolian research, Vol.72, 100957
03/2025
Web of Science ID: WOS:001391990400001
Abstract
Recent research has increasingly focused on the intricate relationship between wind dynamics and sediment transport in coastal settings, particularly how surface features affect aeolian transport processes. Non-erodible roughness elements such as gravel or shell deposits play a significant role by altering wind flow and raising the wind velocity threshold required to mobilize sediment. Despite advancements in modeling, fully understanding sediment transport dynamics remains challenging due to the complex interactions between surface features and wind dynamics. This study explores the influence of non-erodible lag surfaces on sediment transport in sandy barrier island environments. Fieldwork on Santa Rosa Island, Florida, involved two plots: one with a natural sandy surface and another with a gravel lag surface. Wind and sediment transport were monitored for three months using cup anemometers and Wenglor particle counters. Spline regression models identified a two-knot system at wind speed thresholds of 9 ms−1 and 11 ms−1, representing critical changes in sediment transport dynamics. Our results show that non-erodible surfaces significantly reduce sediment transport at lower wind speeds. At wind speeds below 9 ms−1, sediment transport on the lag surface was 131 percent lower than on the non-lag surface. However, as wind speeds increased, the influence of the lag surface diminished, and no significant difference in transport was observed at wind speeds above 11 ms−1. These findings emphasize the intricate role of non-erodible elements in reducing sediment transport at lower wind speeds while enhancing transport dynamics under stronger wind conditions. These insights inform future models and guide coastal management practices.
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Details
- Title
- Lagging behind
- Publication Details
- Aeolian research, Vol.72, 100957
- Resource Type
- Journal article
- Publisher
- Elsevier B.V; London
- Number of pages
- 9
- Copyright
- © 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
- Identifiers
- WOS:001391990400001; 99380595013106600
- Academic Unit
- Mathematics and Statistics; Earth and Environmental Sciences; Hal Marcus College of Science and Engineering
- Language
- English