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A Study on the Estimation Method of Extreme Wave Height Taking Sea State Persistence into Account

考虑海况持续性的极端波高估算方法研究

基本信息

批准号：
07680491
负责人：
HATADA Yoshio
金额：
$ 1.47万
依托单位：
Ehime University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1995
资助国家：
日本
起止时间：
1995 至 1996
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-07680491/
关键词：
high waves and strong winds duration of waves and winds long term wave and wind data peak values of wave height and wind speed annual occurrence rate of duration regression models Monte-Carlo simulation Weibull distribution 長期資料分布継続時間発生

项目摘要

Not only extremes of wave height and wind speed but also persistences of wave height and wind speed above a threshold value are important factors to be considered in design of coastal structures and planning of coastal defense works, but few attempts have been conducted because of lack of long term data with good quality. In this study, detail statistical analyzes have carried out for the long term data of wave height and wind speed gathered at many observation points around the coasts of Japan and the surrounding sea area. Regression models, in which independent variables are the dimensionless variance of the wave height or wind speed data and its dimensionless threshold value, are proposed for the estimation of probability distribution of long term wave height or wind speed and probability distributions of its persistence above a threshold and peak value during the duration period. Return period of high waves or strong winds with duration above a threshold, where these values are prescribed is evaluated with the combination of the above-mentioned three regression models. Next, an investigation has been made to find what kind of fitting method is preferable for the parameter estimation of a probability distribution to obtain a reliable estimate of statistics and how the sampling variability could be evaluated. The study uses 8 kinds of theoretical probability distribution including the Weibull and Gumbel distributions and 4 kinds of parameter estimation methods such as the probability weighted moment method and maximum likelihood method. Based on the statistical analysis with use of 3 or 4 methods for data generated by a Monte-Carlo simulation technique, the optimum method to be used for parameter estimation was determined for each distibution from the view points of minimizing bias and variance of statistics. Also applicability of the jackknife method and information matrix method to the estimation of variance of statistics were verified.

波高和风速的极端值以及波高和风速持续高于阈值都是海岸结构设计和海防工程规划中需要考虑的重要因素，但由于缺乏长期的数据，很少进行尝试。质量好。在本研究中，详细的统计分析了在日本海岸和周边海域的许多观测点收集的波高和风速的长期数据。本文提出了以波高或风速数据的无量纲方差及其无量纲阈值为自变量的回归模型，用于估计长期波高或风速的概率分布以及在持续期内波高或风速在阈值和峰值以上的持续性的概率分布。将上述三个回归模型组合起来，对规定的持续时间超过阈值的高浪或强风重现期进行了评估。其次，研究了概率分布的参数估计应采用何种拟合方法，以获得可靠的统计估计值，以及如何评价抽样变异性。研究中采用了威布尔分布、冈贝尔分布等8种理论概率分布和概率加权矩法、极大似然法等4种参数估计方法。基于使用3或4种方法对蒙特-卡罗模拟技术生成的数据进行的统计分析，从最小化统计偏差和方差的观点出发，确定了用于每个分布的参数估计的最佳方法。验证了刀切法和信息矩阵法对统计量方差估计的适用性。