The influence of seasonal to interannual nearshore profile variability on extreme water levels: Modeling wave runup on dissipative beaches

摘要

Wave runup, an important contributor to storm-induced extreme water levels, is commonly predicted via empirical formulations that parameterize coastal morphology using simple metrics such as the foreshore beach slope. However, spatially and temporally complex nearshore morphology, such as subtidal sandbars, have the potential to alter surf zone wave dissipation patterns and therefore influence setup, swash, and runup levels observed at the shoreline. In this study, a suite of numerical experiments using XBeach demonstrate reasonable skill in reproducing wave runup observations in dissipative settings, explore the relative influence of seasonal to interannual variability in nearshore morphology on runup and its constitutive components, and illustrate differences between empirical and numerically modeled estimates of runup. The numerical model results show that interannual variability in sandbar configuration, associated with net offshore sandbar migration, has a larger influence on wave runup than does seasonal sandbar variability. Although the particular configuration of sandbars was estimated to influence runup by as much as 0.18 m during storm conditions, natural variability in subaerial beach topography has a stronger influence on runup than subtidal morphology. XBeach demonstrates that both wave setup and infragravity swash have morphologic controls. In experiments simulating storm conditions in which both nearshore and beach morphology was varied, natural interannual variability in beach topography explained about 80% of the variance in runup and its constituents. While XBeach predictions of setup, swash, and runup compare favorably with empirical predictors for low wave conditions, the numerical model predicts higher runup levels for storm-conditions on dissipative beaches raising potential concerns about coastal hazards assessments that use these empirical models to estimate extreme total water levels. (C) 2016 Elsevier B.V. All rights reserved.