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Uncertainty in runup predictions on natural beaches using XBeach nonhydrostatic

机译:使用xbeach非水滴的自然海滩上的运行预测的不确定性

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The wave time series that forces phase-resolving models is a source of model uncertainty that can propagate into wave runup predictions when the wave phase information is unknown. The effect of beach morphology on the propagation of this intrinsic uncertainty related to wave randomness (Ui) is largely unexplored. Here, we quantify the importance of uncertainty in wave runup at a dissipative (TS), intermediate (DU) and reflective (DE) beach using the phase-resolving model XBeach nonhydrostatic. Intrinsic uncertainty is evaluated with respect to the effect of free model parameters and of an evolving bed. Uncertainty contributions due to model equations and numerical methods are not assessed. The model is forced at each beach with 100 different wave time series corresponding to the same storm condition. Computed uncertainty metrics reveal that Ui is most important at TS, where extreme runup (R2%) of a single simulation can deviate up to 31% from the 100-simulation ensemble average. Intrasite differences in R2% can be attributed to the predominance of low-frequency swash (SLF), which is more sensitive to Ui than high-frequency swash and setup. Additional simulations using the suggested range of breaking and bed friction coefficients demonstrate that Ui produces more variability in SLF than the two most important model parameters, whereas the parametric range is more important for high-frequency wave height. Furthermore, morphodynamic simulations show that Ui produces a larger variability in R2% and SLF than an evolving bed under a 7-hr storm. Not surprisingly, Ui causes larger variability in morphologic than hydrodynamic predictions due to morphologic feedback. Trends can reverse from swash zone accretion to erosion (TS) by using a wave time series with differently distributed phase. Ensemble simulations are recommended for forecasts based on wave time series with randomly distributed phase.
机译:强制锁相模型的波时间序列是模型不确定性的源,当波相信息未知时,可以传播到波浪运行预测中。海滩形态对与波动随机性(UI)相关的这种内在不确定性传播的影响在很大程度上是未开发的。在这里,我们使用相位解析模型Xbeach非水rotogation量化在耗散(TS),中间(DU)和反射性(DE)海滩的波浪螺射中的不确定性的重要性。基于自由模型参数和演化床的效果来评估内在不确定性。没有评估由于模型方程和数值方法引起的不确定性贡献。该模型被迫在每个海滩上,100种不同的波时间序列对应于同样的风暴条件。计算的不确定度量显示UI在TS中最重要,其中单个仿真的极端运行(R2%)可以偏离100型仿真集合平均值的31%。 R2%的intrasite差异可归因于低频旋转速率(SLF)的优势,这对UI更敏感而不是高频旋转速率和设置。使用建议的断裂和床摩擦系数的额外模拟表明UI在SLF中产生比两个最重要的模型参数更大,而参数范围对于高频波高度更为重要。此外,形态学模拟表明,UI在7-HR风暴下产生的R2%和SLF的变异性较大。毫不奇怪,UI由于形态学反馈而与流体动力学预测导致形态的变异性更大。通过使用具有不同分布阶段的波浪时间序列,趋势可以从旋转区域积累到腐蚀(TS)反转。建议基于随机分布阶段的波浪时间序列预测集合模拟。

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