Barchan swarm dynamics from a Two-Flank Agent-Based Model

Abstract. In this work, we simulate barchan swarms using the Two-Flank Agent-Based Model and investigate how changes to model parameters and environmental drivers lead to different swarm dynamics. In particular, we explore how the parameter qshift, which controls the rate of equilibration between the flanks of an asymmetric dune and thereby the stability of an asymmetric morphology, influences the frequencies of different collision types in the swarm and can be adjusted to produce swarms with dune sizes that are longitudinally homogeneous. Such size stability has been observed in real-world swarms but has not been obtained by previous agent-based models. We also find that, for certain densities of newly added barchans, the dune number density remains constant with downwind distance, something which has also been reported in nature but not in previous agent-based models. We also investigated how boundary condition changes propagate through swarms, something which will become increasingly important in the face of human infrastructure expansion and anthropogenic climate change. Finally, we are able to investigate how asymmetry and spatially patterning in the swarms are influenced by bimodal wind regimes. Since these simulations produce many more realistic phenomena than previous models, this work represents a significant step forward in the our understanding of the interplay between environmental conditions and dune interactions in shaping the dynamics of barchan swarms.

Authors

Institutions

Publication Details

Journal
Earth Surface Dynamics
Published
2024-10-22
DOI
https://doi.org/10.5194/esurf-12-1205-2024
Citations
2
Primary Topic
Aeolian processes and effects
Type
article
Field-Weighted Citation Impact
1.03

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Barchan swarm dynamics from a Two-Flank Agent-Based Model

Dominic T. Robson, Andreas Baas
2 citations
Earth Surface Dynamics
Aeolian processes and effects
1.03
article

Barchan swarm dynamics from a Two-Flank Agent-Based Model

Dominic T. Robson, Andreas Baas
article en
2 citations

Abstract

Abstract. In this work, we simulate barchan swarms using the Two-Flank Agent-Based Model and investigate how changes to model parameters and environmental drivers lead to different swarm dynamics. In particular, we explore how the parameter qshift, which controls the rate of equilibration between the flanks of an asymmetric dune and thereby the stability of an asymmetric morphology, influences the frequencies of different collision types in the swarm and can be adjusted to produce swarms with dune sizes that are longitudinally homogeneous. Such size stability has been observed in real-world swarms but has not been obtained by previous agent-based models. We also find that, for certain densities of newly added barchans, the dune number density remains constant with downwind distance, something which has also been reported in nature but not in previous agent-based models. We also investigated how boundary condition changes propagate through swarms, something which will become increasingly important in the face of human infrastructure expansion and anthropogenic climate change. Finally, we are able to investigate how asymmetry and spatially patterning in the swarms are influenced by bimodal wind regimes. Since these simulations produce many more realistic phenomena than previous models, this work represents a significant step forward in the our understanding of the interplay between environmental conditions and dune interactions in shaping the dynamics of barchan swarms.

Earth Surface DynamicsVol. 12(5)
King's College London (GB), University of Reading (GB)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 25%
Aeolian processes and effects
1.03
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.