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Chaos in a simple model of a delta network

The flux partitioning in delta networks controls how deltas build land and generate stratigraphy. Here, we study flux-partitioning dynamics in a delta network using a simple numerical model consisting of two orders of bifurcations. Previous work on single bifurcations has shown periodic behavior ari...

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Autores principales: Salter, Gerard, Voller, Vaughan R., Paola, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959556/
https://www.ncbi.nlm.nih.gov/pubmed/33077587
http://dx.doi.org/10.1073/pnas.2010416117
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author Salter, Gerard
Voller, Vaughan R.
Paola, Chris
author_facet Salter, Gerard
Voller, Vaughan R.
Paola, Chris
author_sort Salter, Gerard
collection PubMed
description The flux partitioning in delta networks controls how deltas build land and generate stratigraphy. Here, we study flux-partitioning dynamics in a delta network using a simple numerical model consisting of two orders of bifurcations. Previous work on single bifurcations has shown periodic behavior arising due to the interplay between channel deepening and downstream deposition. We find that coupling between upstream and downstream bifurcations can lead to chaos; despite its simplicity, our model generates surprisingly complex aperiodic yet bounded dynamics. Our model exhibits sensitive dependence on initial conditions, the hallmark signature of chaos, implying long-term unpredictability of delta networks. However, estimates of the predictability horizon suggest substantial room for improvement in delta-network modeling before fundamental limits on predictability are encountered. We also observe periodic windows, implying that a change in forcing (e.g., due to climate change) could cause a delta to switch from predictable to unpredictable or vice versa. We test our model by using it to generate stratigraphy; converting the temporal Lyapunov exponent to vertical distance using the mean sedimentation rate, we observe qualitatively realistic patterns such as upwards fining and scale-dependent compensation statistics, consistent with ancient and experimental systems. We suggest that chaotic behavior may be common in geomorphic systems and that it implies fundamental bounds on their predictability. We conclude that while delta “weather” (precise configuration) is unpredictable in the long-term, delta “climate” (statistical behavior) is predictable.
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spelling pubmed-79595562021-03-23 Chaos in a simple model of a delta network Salter, Gerard Voller, Vaughan R. Paola, Chris Proc Natl Acad Sci U S A Physical Sciences The flux partitioning in delta networks controls how deltas build land and generate stratigraphy. Here, we study flux-partitioning dynamics in a delta network using a simple numerical model consisting of two orders of bifurcations. Previous work on single bifurcations has shown periodic behavior arising due to the interplay between channel deepening and downstream deposition. We find that coupling between upstream and downstream bifurcations can lead to chaos; despite its simplicity, our model generates surprisingly complex aperiodic yet bounded dynamics. Our model exhibits sensitive dependence on initial conditions, the hallmark signature of chaos, implying long-term unpredictability of delta networks. However, estimates of the predictability horizon suggest substantial room for improvement in delta-network modeling before fundamental limits on predictability are encountered. We also observe periodic windows, implying that a change in forcing (e.g., due to climate change) could cause a delta to switch from predictable to unpredictable or vice versa. We test our model by using it to generate stratigraphy; converting the temporal Lyapunov exponent to vertical distance using the mean sedimentation rate, we observe qualitatively realistic patterns such as upwards fining and scale-dependent compensation statistics, consistent with ancient and experimental systems. We suggest that chaotic behavior may be common in geomorphic systems and that it implies fundamental bounds on their predictability. We conclude that while delta “weather” (precise configuration) is unpredictable in the long-term, delta “climate” (statistical behavior) is predictable. National Academy of Sciences 2020-11-03 2020-10-19 /pmc/articles/PMC7959556/ /pubmed/33077587 http://dx.doi.org/10.1073/pnas.2010416117 Text en Copyright © 2020 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Physical Sciences
Salter, Gerard
Voller, Vaughan R.
Paola, Chris
Chaos in a simple model of a delta network
title Chaos in a simple model of a delta network
title_full Chaos in a simple model of a delta network
title_fullStr Chaos in a simple model of a delta network
title_full_unstemmed Chaos in a simple model of a delta network
title_short Chaos in a simple model of a delta network
title_sort chaos in a simple model of a delta network
topic Physical Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959556/
https://www.ncbi.nlm.nih.gov/pubmed/33077587
http://dx.doi.org/10.1073/pnas.2010416117
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