No abstract

Abstract. Natural geophysical timeseries bear the signature of a number of complex, possibly inseparable, and generally unknown combination of linear, stable non-linear and chaotic processes. Quantifying the relative contribution of, in particular, the non-linear components will allow improved modelling and prediction of natural systems, or at least define some limitations on predictability. However, difficulties arise; for example, in cases where the series are naturally cyclic (e.g. water waves), it is most unclear how this cyclic behaviour impacts on the techniques commonly used to detect the nonlinear behaviour in other fields. Here a non-linear autoregressive forecasting technique which has had success in demonstrating nonlinearity in non-cyclical geophysical timeseries, is applied to a timeseries generated by videoing the waterline on a natural beach (run-up), which has some irregular oscillatory behaviour that is in part induced by the incoming wave field. In such cases, the deterministic shape of each run-up cycle has a strong influence on forecasting results, causing questionable results at small (within a cycle) prediction distances. However, the technique can clearly differentiate between random surrogate series and natural timeseries at larger prediction distances (greater than one cycle). Therefore it was possible to clearly identify nonlinearity in the relationship between observed run-up cycles in that a local autoregressive model was more adept at predicting run-up cycles than a global one. Results suggest that despite forcing from waves impacting on the beach, each run-up cycle evolves somewhat independently, depending on a non-linear interaction with previous run-up cycles. More generally, a key outcome of the study is that oscillatory data provide a similar challenge to differentiating chaotic signals from correlated noise in that the deterministic shape causes an additional source of autocorrelation which in turn influences the predictability at small forecasting distances.

No abstract

Water flows through submerged and emergent vegetation control the transport and deposition of sediment in coastal wetlands. Many past studies into the hydrodynamics of vegetation fields have used idealized vegetation mimics, mostly rigid dowels of uniform height. In this study, a canopy of real mangrove pneumatophores was reconstructed in a flume to quantify flow and turbulence within and above this canopy. At a constant flow forcing, an increase in pneumatophore density, from 71 m -2 to 268 m -2 , was found to cause a reduction of the within-canopy flow velocities, whereas the over-canopy flows increased. Within-canopy velocities reduced to 46% and 27% of the free-stream velocities for the lowest and highest pneumatophore densities, respectively, resulting in stronger vertical shear and hence greater turbulence production around the top of the denser pneumatophore canopies. The maximum Reynolds stress was observed at 1.5 times the average pneumatophore height, in contrast to uniform-height canopies, in which the maximum occurs at approximately the height of the vegetation. The ratios of the within-canopy velocity to the free-stream velocity for the pneumatophores were found to be similar to previous observations with uniform-height vegetation mimics for the same vegetation densities. However, maxima of the scaled friction velocity were two times smaller over the real pneumatophore canopies than for idealized dowel canopies, due to the reduced velocity gradients over the variable-height pneumatophores compared to uniform-height dowels. These findings imply that results from previous studies with idealized and uniform vegetation mimics may have limited application when considering sediment transport and deposition in real vegetation, as the observed turbulence characteristics in nonuniform canopies deviate significantly from those in dowel canopies.

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