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| Titel |
Multivariate analysis of nonlinearity in sandbar behavior |
| VerfasserIn |
L. Pape, B. G. Ruessink |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 15, no. 1 ; Nr. 15, no. 1 (2008-02-18), S.145-158 |
| Datensatznummer |
250012561
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| Publikation (Nr.) |
 copernicus.org/npg-15-145-2008.pdf |
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| Zusammenfassung |
| Alongshore sandbars are often present in the nearshore zones of storm-dominated micro- to mesotidal coasts. Sandbar
migration is the result of a large number of small-scale physical processes that are generated by the incoming waves
and the interaction between the wave-generated processes and the morphology. The presence of nonlinearity in a sandbar
system is an important factor determining its predictability. However, not all nonlinearities in the underlying system
are equally expressed in the time-series of sandbar observations. Detecting the presence of nonlinearity in sandbar
data is complicated by the dependence of sandbar migration on the external wave forcings. Here, a method for detecting
nonlinearity in multivariate time-series data is introduced that can reveal the nonlinear nature of the dependencies between
system state and forcing variables. First, this method is applied to four synthetic datasets to demonstrate its ability to
qualify nonlinearity for all possible combinations of linear and nonlinear relations between two variables. Next, the method
is applied to three sandbar datasets consisting of daily-observed cross-shore sandbar positions and hydrodynamic forcings,
spanning between 5 and 9 years. Our analysis reveals the presence of nonlinearity in the time-series of sandbar and
wave data, and the relative importance of nonlinearity for each variable. The relation between the results of each sandbar
case and patterns in bar behavior are discussed, together with the effects of noise. The small effect of nonlinearity implies
that long-term prediction of sandbar positions based on wave forcings might not require sophisticated nonlinear models. |
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