Abstract. Time and length scales of beach variability have been quantified using 16 years of beach surveys sampled at the Army Corps of Engineers' Field Research Facility, located on the U.S. Atlantic coast. Between 50% and 90% of the bathymetric variability at this site was explained by alongshore-uniform response over the approximately 1 km alongshore span of the surveys. Although the incident wave height variance was dominated by frequencies at or higher than 1 cycle/yr, more than 80% of the bathymetric variance at all cross-shore locations was explained by frequencies <1 cycle/yr. Interannual cycles consisting of sandbar formation, migration, and decay contributed to the lowfrequency variability. The observed behavior can be explained by a simple, heuristic model. The model assumes that bars migrate toward a wave height dependent equilibrium position. This position was shown to coincide with the wave "breakpoint." Additionally, the rate of bar response is taken to be variable and was empirically determined to be proportional to the wave height cubed. The net effect of a variable response rate is to shift the expected long-term mean sandbar position offshore, toward the equilibrium position associated with the largest waves. The model explained up to 80% of the observed bar position time series variance and up to 70% of the variance of bar crest velocity time series, which were extracted from three different sandbars. Characteristic bar response times (related to the inverse of the response rate) were found to be long relative to the characteristic timescale of the forcing (1 year in our case). As a result, transient response (i.e., bar position far from equilibrium) tended to persist for many cycles of the forcing. Transient bar behavior appears in the observations when bars formed near the shoreline or when outer bars decayed and inner bars faced a changed wave climate. While the present model is able to explain the evolution of these transients, it does not contain a mechanism for their introduction.

Abstract. This paper builds on the now classical discussions by Bowen [1980] and Bailard [1981] on the applicability and implications of Bagnold's [1963] sediment transport model to nearshore profile modeling. We focus on the morphologic implications of both the strengths and weaknesses of Bagnold's model, isolating the transport terms that are well predicted (i.e., mean flow terms) from those that are not well predicted (i.e., transport due to correlations between flow and sediment load). We factor Bagnold's model into a dimensional transport magnitude and a nondimensional term. The nondimensional term describes the relative importance of transport due to undertow, gravity, and correlations between flow and sediment load. The transport magnitude largely determines the response time of nearshore profiles. For typical nearshore environments this response time was estimated to vary as a function of incident rms wave height (Hrms) from ----500 years (Hrm s "• 0.5 m) to 2 years (Hrm s '-" 3 m). The relative importance of competing transport mechanisms is shown to depend strongly on the relative wave height (defined as the ratio of the rms wave height to the local depth). Simplified nearshore transport parameterizations that are a function of this variable were derived and were interrogated for the existence and form of equilibrium profiles. Several differences from previously computed equilibrium profiles were noted. First, because the relative wave height saturates in natural surf zones, equilibrium profiles converge to a relatively flat profile near the shoreline. Second, under some situations a seaward sloping equilibrium profile may not exist. Third, the long response times combined with unknown stability of an equilibrium profile make it difficult to assess the physical connection between theoretical equilibrium profiles and profiles observed in nature. IntroductionAt present, accurate prediction of nearshore bathymetric change at all relevant scales is impossible. Part of the difficulty is that the relevant scales span a very broad range, from millimeters (individual sand grains) to kilometers (the cross-shore width of the surfzone) and tens of kilometers (alongshore extent of littoral cells). The largest spatial scales are particularly important because they contain the majority of the spatial and temporal variability of nearshore bathymetric change [Lippmann and Holman, 1990; Plant et al., 1999]. These are also the spatial and temporal scales that characterize human interactions with the coast. Unfortunately, the difficulty in modeling and prediction is acute at the largest scales, since evolution at this scale requires the integration over all smaller scales [Roelvink and BrOker, 1993].Ideally, the interaction between the large-scale morphology (e.g., surf zone sandbars or the cross-shore profile as a whole) and small-scale processes (e.g., wave-driven hydrodynamics and sediment transport) can be described in terms of param- The advantage of a purely large-scale model is its transparency, which allows di...

This paper describes an application of the XBeach model to investigate the effect of longshore topographic variance on overwash. The model is used to simulate the morphological response of an eight-kilometer section of Santa Rosa Island, Florida, due to Hurricane Ivan (2004). The influence of longshore scales in the bed elevation is investigated by comparing the morphological response of the reference simulation to the morphological response of six sensitivity simulations in which the initial bed elevation was modified to remove longshore topographic variance. It is shown that the morphological response of the foreshore-foredune area to Hurricane Ivan is not influenced strongly by the initial longshore bed variance. The morphological response of the back barrier and the back barrier bay to Hurricane Ivan is influenced by features on the back barrier with longshore length scales of 100-500 meters, which hamper the flow across the island during inundation overwash. It is noted that these results may vary for other overwash regimes.