Published July 21, 2025 | Version v1

Field data, analysis and model software and model inputs for "Measurements and modeling of aeolian sand transport on dynamic cobble berm revetments"

  • 1. EDMO icon Utrecht University, Faculty of Geosciences
  • 2. ROR icon Oregon State University

Description

This repository includes moisture content, wind, sand transport and topography measurements collected in January of 2024 in Westport, WA, USA. It also includes the AeoLiS software (version 3.0.0.rc1, de Vries et al., 2023) including the changes described in Section 3.2 of the paper and the input files which were used for the aeolian sediment transport simulations in this research. The Python code used for the analysis of the measured data and modeling results and the generation of figures as presented in the paper is also preserved in this repository. The AeoLiS software is available under a GPL-3.0 license and is developed openly on Github (https://github.com/openearth/aeolis-python). 

Associated with:

van IJzendoorn, Christa and Wengrove, Meagan E. and Ruggiero, Peter and Bond, Hailey G., Measurements and Modeling of Aeolian Sand Transport on Dynamic Cobble Berm Revetments. Available at SSRN: https://ssrn.com/abstract=5253286 or http://dx.doi.org/10.2139/ssrn.5253286 

Files

Aeolian_DynaRev_Zenodo.zip

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Additional details

Identifiers

Funding

United States Army Corps of Engineers
Fundamental Research to Advance the Understanding and Prediction of Coastal Processes for the US West Coast W912HZ2120045
U.S. National Science Foundation
Cascadia Coastlines and Peoples Hazards Research Hub, NSF Coastlines and People Large-Scale Hub 2103713

Dates

Collected
2024-01-06
field data
Submitted
2025-05-11
manuscript