Mapping the shoreface of coastal sediment compartments to improve shoreline change forecasts in New South Wales, Australia

The potential response of shoreface depositional environments to sea level rise over the present century and beyond remains poorly understood. The shoreface is shaped by wave action across a sedimentary seabed and may aggrade or deflate depending on the balance between time-averaged wave energy and the availability and character of sediment, within the context of the inherited geological control. For embayed and accommodation-dominated coastal settings, where shoreline change is particularly sensitive to cross-shore sediment transport, whether the shoreface is a source or sink for coastal sediment during rising sea level may be a crucial determinant of future shoreline change. While simple equilibrium-based models (e.g. the Bruun Rule) are widely used in coastal risk planning practice to predict shoreline change due to sea level rise, the relevance of fundamental model assumptions to the shoreface depositional setting is often overlooked due to limited knowledge about the geomorphology of the nearshore seabed. We present high-resolution mapping of the shoreface-inner shelf in southeastern Australia from airborne lidar and vessel-based multibeam echosounder surveys, which reveals a more complex seabed than was previously known. The mapping data are used to interpret the extent, depositional character and morphodynamic state of the shoreface, by comparing the observed geomorphology to theoretical predictions from wave-driven sediment transport theory. The benefits of high-resolution seabed mapping for improving shoreline change predictions in practice are explored by comparing idealised shoreline change modelling based on our understanding of shoreface geomorphology and morphodynamics before and after the mapping exercise

Wave Runup Distributions On Natural Beaches

Runup distributions were measured on a wide spectrum of sandy beaches on the coast of New South Wales, Australia. The data indicates that the Rayleigh distribution is a reasonable statistical model for the maximum level reached by individual waves. The vertical scale of the best-fit distribution is proportional to the wave height times the surf similarity parameter for the steeper beaches in accordance with Hunt's formula for runup of regular waves on structures. For flat beaches, however, the vertical scale of the distribution is independent of the beach slope. The base level for the best-fit distribution (i.e. the highest level transgressed by all incoming wave crests) is indistinguishable from the still water level on the steep beaches but significantly lower on flat beaches. The demarcation between "steep" and "flat" beaches in these respects is at a beach face slope of approximately 0.10. The level of the shoreline relative to the runup distribution is a decreasing function of the beach slope

A more rigorous approach to calibrating and assessing the uncertainty of coastal numerical models

There has been widespread effort to develop sophisticated numerical models to predict coastal change at a variety of time and spatial scales. All these models contain free parameters that require calibration to the available field data and little guidance (beyond the adoption of the default values provided) is presently available to inform the selection of best-fit parameter values. In practice, the means of optimising these parameters often lacks a sufficiently rigorous assessment of the impacts of parameter interdependence and parameter-induced model uncertainty is rarely quantified. The Generalised Likelihood Uncertainty Estimation (GLUE) method has been employed extensively in the field of hydrology and has proven to be a conceptually simple and efficient method to evaluate model sensitivities to parameter values and identify any inherent model structural errors. The GLUE method approaches the problem of ‘equifinality’ (i.e. the likely existence of multiple ‘optimum’ parameter sets) using Monte Carlo simulation applied to create many different combinations of possible model parameters. The outcomes of the Monte Carlo analysis are parameter posterior distributions, which can then be used by the modeller to determine parameter values most likely to produce model predictions with the highest skill. This paper describes the new application of the GLUE method to the XBeach storm erosion model, using data from a site in Italy where the XBeach model has been previously applied without such a rigorous evaluation of parameter sensitivity. The results presented demonstrate the more generic effectiveness and applicability of GLUE in the field of coastal engineering. The sensitivity of XBeach to each trialled free parameter is determined in a rigorous and transparent manner, and uncertainty bounds are obtained. This enables the modeller to better understand and quantify model skill in predicting observed and potential future erosion

Extreme coastal erosion enhanced by anomalous extratropical storm wave direction

Extratropical cyclones (ETCs) are the primary driver of large-scale episodic beach erosion along coastlines in temperate regions. However, key drivers of the magnitude and regional variability in rapid morphological changes caused by ETCs at the coast remain poorly understood. Here we analyze an unprecedented dataset of high-resolution regional-scale morphological response to an ETC that impacted southeast Australia, and evaluate the new observations within the context of an existing long-term coastal monitoring program. This ETC was characterized by moderate intensity (for this regional setting) deepwater wave heights, but an anomalous wave direction approximately 45 degrees more counter-clockwise than average. The magnitude of measured beach volume change was the largest in four decades at the long-term monitoring site and, at the regional scale, commensurate with that observed due to extreme North Atlantic hurricanes. Spatial variability in morphological response across the study region was predominantly controlled by alongshore gradients in storm wave energy flux and local coastline alignment relative to storm wave direction. We attribute the severity of coastal erosion observed due to this ETC primarily to its anomalous wave direction, and call for greater research on the impacts of changing storm wave directionality in addition to projected future changes in wave heights