Using wind run to predict sand drift |
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| Authors: | Andreas CW Baas Derek WT Jackson Irene Delgado-Fernandez Kevin Lynch J Andrew G Cooper |
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| Institution: | 1. Department of Geography, King's College London, London, UK;2. Centre for Coastal and Marine Research, School of Environmental Sciences, University of Ulster, Coleraine, UK;3. Department of Geography, Edge Hill University, Ormskirk, UK;4. School of Geography and Archaeology, National University of Ireland, Galway, Ireland |
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| Abstract: | Conventional aeolian sand transport models relate mass transport rate to wind speed or shear velocity, usually expressed and empirically tested on a 1-s time scale. Projections of total sand delivery over long time scales based on these models are highly sensitive to any small bias arising from statistical fitting on empirical data. We analysed time series of wind speed and sand transport rate collected at 14 independent measurement stations on a beach during a prior field experiment. The results show that relating total sand drift to cumulative above-threshold wind run yields models which are more statistically robust when fitted on empirical data, generating smaller prediction errors when projected to longer time scales. Testing of different power exponents indicates that a linear relationship between sand drift and above-threshold wind run yields the best results. These findings inspire a speculative novel phenomenological model relating the mass flow of air in the boundary layer to the mass transport of sand over the surface. © 2020 John Wiley & Sons, Ltd. |
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| Keywords: | aeolian sand transport regression prediction statistical analysis phenomenological model |
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