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Coasts are continually changing and remote sensing from satellites has the potential to both map and monitor coastal change at multiple scales. Unlike optical technology, synthetic aperture radar (SAR) is uninfluenced by darkness, clouds, and rain, potentially offering a higher revision period to map shoreline position and change, but this can only be feasible if we have a better interpretation of what shorelines as extracted from SAR imagery represent on the ground. This study aims to assess the application of shorelines extracted from SAR from publicly available satellite imagery to map and capture intra-annual to inter-annual shoreline variability. This is assessed in three tidally controlled coastal study areas that represent sand and gravel beaches with different backshore environments: low-lying dunes and marsh; steep, rocky cliff; and urban environments. We have found that SAR shorelines consistently corresponded to positions above the high-water mark across all three sites. We further discuss the influence of the scene geometry, meteorological and oceanographic conditions, and backshore environment and provide a conceptual interpretation of SAR-derived shorelines. In a low-lying coastal setting, the annual change rate derived through SAR presents a high degree of alignment with the known reference values. The present study contributes to our understanding of the poorly known aspect of using shorelines derived from publicly available SAR satellite missions. It outlines a quantitative approach to automatically assess their quality with a new automatic detection method that is transferable to shoreline evolution assessments worldwide. [ABSTRACT FROM AUTHOR]

Velocities and sand concentrations measured along 20 transects at the Field Research Facility (FRF) at Duck, North Carolina during October 16-23, 1997 are analyzed to examine the cross-shore and longshore suspended sand transport in the FRF pier depression. The suspended sand volume [V.sub.s] per unit bottom area remains large outside the surf zone in the depression. The depth-integrated offshore and longshore suspended sand transport rates are shown to be estimated as a, [bar.U] [V.sub.s] and [bar.V] [V.sub.s], respectively, where the empirical parameter a is in the range of 0.1-0.4 in the depression, [bar.U] is the cross-shore current and [bar.V] is the longshore current. The offshore suspended sand transport rate at the end of the pier is estimated to be as large as 3.5 [m.sup.3]/h/m at the peak of a storm with an offshore significant wave height of 3.5 m. The sand transported offshore appears to have been supplied by the longshore sand transport toward the pier depression. CE Database subject headings: Littoral currents; Waves; Sand; Suspended sediment; Sediment transport; Beaches; Piers.

The prediction of berm and dune erosion during a storm is essential for storm damage assessment. Simple and transparent formulas for the cross-shore and longshore transport rates of suspended sediment and bed load on beaches are proposed and incorporated into a combined wave and current model to predict the berm and dune erosion under normally and obliquely incident irregular waves. Two small-scale experiments for two different berm profiles were conducted for the calibration of the developed numerical model. The calibrated numerical model is shown to predict the measured berm and dune erosion in these experiments as well as dune erosion measured in three large-scale tests with errors less than a factor of two. The numerical model is used to examine the effects of the wave period and incident wave angle on the berm and dune erosion. These effects are computed to be within a factor of two. DOI: 10.1061/(ASCE)0733-950X(2009)135:1(1) CE Database subject headings: Berms; Dunes; Sand; Erosion; Beaches; Sediment transport; Bed loads; Storms; Surf zone.