River Ecomorphodynamic Models Exhibit Features of Nonlinear Dynamics and Chaos

I. Cunico*, W. Bertoldi, F. Caponi, H. A. Dijkstra, A. Siviglia

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Modeling the nonlinear interactions between flow, sediment, and vegetation is essential for improving our understanding and prediction of river system dynamics. Using simple numerical models, we simulate the key flow-sediment-vegetation interaction where the disturbance is intrinsically generated by the presence of vegetation. In this case, biomass growth modifies the flow field, induces bed scour, and thus potentially causes vegetation uprooting when erosion exceeds root depth. Our results show that this nonlinear feedback produces deterministic chaos under a wide range of conditions, with complex aperiodic dynamics generated by a period-doubling route to chaos. Moreover, our results suggest relatively small values of Lyapunov time, spanning 2–4 growth-flood cycles, which significantly restrict the predictability of riverbed evolution. Although further spatial and temporal processes may add complexity to the system, these results call for the use of ensemble methods and associated uncertainty estimates in ecomorphodynamic models.

Original languageEnglish
Article numbere2023GL107951
JournalGeophysical Research Letters
Volume51
Issue number11
DOIs
Publication statusPublished - 16 Jun 2024

Bibliographical note

Publisher Copyright:
© 2024. The Authors.

Funding

The first, second and last authors acknowledge the Italian Ministry of Education, Universities and Research (MUR), in the framework of the project DICAM-EXC (Departments of Excellence 2023-2027, Grant L232/2016) and the European Union under NextGenerationEU, in the framework of the project Green Rivers, PRIN 2022 PNRR Prot. n. P20229WTX7. We thank Chris Paola and an anonymous referee for their valuable comments and Michele Castelluzzo for conducting preliminary analysis on the computation of the Lyapunov exponent.

FundersFunder number
Italian Ministry of Education, Universities and Research (MUR)DICAM-EXC, 2023-2027, L232/2016
European UnionP20229WTX7

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