ABSTRACT

Figueiredo, S.A.; Cowell, P.J., 2016. Sensitivity of shoreline-recession forecasts to sediment-budget uncertainties. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 947–951. Coconut Creek (Florida), ISSN 0749-0208.

Intrinsic uncertainty associated with the stochastic nature of coastal processes and how they affect sediment budget estimates under present conditions already make predicting coastal change difficult. The possibility that under climate change conditions alteration of wave climate will have direct implications for alongshore transport in future, may complicate even more future forecasts of coastal change in response to sea-level rise. This study exploits the variability in sediment budgets along the Rio Grande do Sul coastal plain, in southern Brazil, to provide an experimental framework to evaluate the significance of such uncertainties in coastal response under the rising sea levels rates predicted for the next century. The analysis involved quantifying the variation in coastal recession sensitivity between different sectors along the coast (coastal cells), through the application of RanSTM (Random Shoreface Translation Model) using two different scenarios for the sediment-budget parameter. Sediment budget parameter was estimated based on historical shoreline changes and Holocene barrier stratigraphic data. The results show that forecasts for lower-magnitude coastal recession associated with more likely impacts (e.g. 90% risk) are more susceptible to uncertainties in littoral sediment budgets than high-magnitude less likely impacts (e.g. 10% risk). This is especially the case for coastal cells with low dune dimensions because in general such dunes have less capacity to buffer coastal-erosion effects. The reduced effect on high-end forecasts with respect to sediment budget uncertainties therefore favors better confidence in the forecasts.

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