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Software . 2026
Data sources: ZENODO
ZENODO
Software . 2026
Data sources: Datacite
ZENODO
Software . 2026
Data sources: Datacite
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AEOLIS Idealised Coastal Dune Blowout Simulation Workflow

Authors: Castelle, Bruno; de Vries, Sierd; Burvingt, Olivier; Nicolae Lerma, Alexandre; Hesp, Patrick;

AEOLIS Idealised Coastal Dune Blowout Simulation Workflow

Abstract

AEOLIS SIMULATION OF BLOWOUTS STARTING FROM IDEALISED ALONGSHORE-UNIFORM DUNES : * Overview: This repository provides a simple workflow to run idealised coastal dunesimulations using the AEOLIS model. It reproduces the modelling approachdescribed in: Castelle, B., de Vries, S., Burvingt, O., Nicolae Lerma, A., Hesp, P.Process-based modelling of coastal dune blowout initiation, developmentand stabilisation (Journal of Geophysical Research – Earth Surface,submitted) The workflow automatically: • Generates an idealised dune morphology •Generates vegetation cover • Builds an AEOLIS input file from a template• Runs AEOLIS • Stores the output * Folder structure Aeolis_Version/ → AEOLIS model installation Example_Run/ → Folder wheresimulations are executed Example_Run contains: - run_single_aeolis.py Main script to prepare andrun simulations - aeolis_template.txt AEOLIS configuration template -wind.txt Wind forcing time series - tide.txt Tide time series - ne.grdNon‑erodible layer - callback.py Vegetation callback used by AEOLIS * How the workflow works 1) Topography generation The script creates an idealised Gaussian dune. Optional features: • Offshore slope • Blowout notch • Random topographic noise Generated files: z.grd → bed elevation x.grd → x coordinates y.grd → ycoordinates 2) Vegetation generation Vegetation density is created from: • Elevation threshold • Initial vegetation density • Optional random noise Vegetation is removed inside the blowout notch. Example output: vge_ZVeg0.5_DVeg0.15.grd 3) Automatic AEOLIS input file The script reads aeolis_template.txt and replaces the vegetation file name. Example output: aeolis_ZVeg0.5_DVeg0.15.txt 4) Running AEOLIS The script launches: aeolis run AEOLIS produces aeolis.nc which is renamed automatically. * Running a simulation 1) Make sure AEOLIS is installed and available: aeolis –help 2) Move to the example folder: cd Example_Run 3) Run the reference simulation: python3 run_single_aeolis.py –Zveg 0.5 –Dveg 0.15 –hv 0.4 –Hd 2.5 –hp 0.0 –Ln 0.0 –Hn 0.0 –zl 1.0 –Xs 150.0 –Ss 0.1 * Main parameters Vegetation Zveg → elevation threshold for vegetation Dveg → initialvegetation density hv → vegetation noise amplitude Morphology Hd → dune height Wd → dune width hp → topographic noise Blowout notch Ln → notch size Hn → notch depth Shoreface Xs → start of nearshore slope Ss → nearshore slope Changing forcing conditions Wind forcing: Edit wind.txt to test different wind climates. Tides: Edit tide.txt. Vegetation behaviour: Modify aeolis_template.txt. Important parametersinclude: V_ver, lateral, germinate, gamma_vegshear, hveg_max. Debug mode (no AEOLIS run) python3 run_single_aeolis.py –Zveg 0.5 –Dveg 0.15 –no-run * Output files z.grd, x.grd, y.grd → grid and bed vge_.grd → vegetation aeolis_.txt →AEOLIS input aeolis_*.nc → simulation output NetCDF output contains: zb, rhoveg, uws, uwn, ustars, ustarn, Cu, qs, qn * Typical workflow • Change CLI parameters → morphology experiments • Edit wind.txt → windclimate experiments • Edit aeolis_template.txt → vegetation experiments This setup provides a straightforward and reproducible way to exploreinteractions between wind, vegetation and dune morphology.

Related Organizations
Keywords

blowouts, AeoLiS, vegetation, aeolian transport, geomorphology, numerical model, Coastal dune

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average