Simulation of Wave Time Series with a Vector Autoregressive Method
Simulation of Wave Time Series with a Vector Autoregressive Method
复制标题
DOI：
10.3390/w14030363
复制
发表时间：
2022-01
期刊：
影响因子：
3.4
通讯作者：
Antonios Valsamidis;Yuzhi Cai;D. Reeve
中科院分区：
文献类型：
--
作者：
Antonios Valsamidis;Yuzhi Cai;D. Reeve
波浪高度、周期和方向的联合时间序列是海岸工程中用于模拟海滩历时演变的计算模型的基本输入数据。然而，由于费用的原因，收集大量所需的输入数据通常是不切实际的。基于2003年9月1日至2016年6月30日期间英格兰东南部利特尔汉普顿近海的近岸波浪记录，本文提出了一种统计方法，以获得覆盖十年或更长时间跨度的波高、周期和方向的模拟联合时间序列。该方法是基于向量自回归移动平均算法。模拟的时间序列显示出令人满意的程度的随机协议之间的原始和模拟的时间序列，包括平均值，边际分布，自相关和互相关结构，这是重要的海岸线演变的蒙特卡罗模拟，从而允许合奏预测的海岸线响应一个变量波气候。
Joint time series of wave height, period and direction are essential input data to computational models which are used to simulate diachronic beach evolution in coastal engineering. However, it is often impractical to collect a large amount of the required input data due to the expense. Based on the nearshore wave records offshore of Littlehampton in Southeast England over the period from 1 September 2003 to 30 June 2016, this paper presents a statistical method to obtain simulated joint time series of wave height, period and direction covering an extended time span of a decade or more. The method is based on a vector auto-regressive moving average algorithm. The simulated times series shows a satisfactory degree of stochastic agreement between original and simulated time series, including average value, marginal distribution, autocorrelation and cross-correlation structure, which are important for Monte Carlo modelling of shoreline evolution, thereby allowing ensemble prediction of shoreline response to a variable wave climate.