A New Method To Estimate Wave Height Of Specified Return Period

The selection of appropriate design parameters based on marine conditions is of paramount importance in the fields of offshore engineering, coastal engineering and coastal disaster prevention, in order to estimate return periods of waves and successfully issue early warnings for storms. In the last few decades, the Annual Extreme Value (AEV) method to estimate the wave height of a specified return period has been widely used in marine engineering, hydraulic engineering, the construction of coastal nuclear power plants。Domestic hydraulic researchers prefer the Gumbel,Weibull, and Pearson type Ⅲ distributions because of their successful applications to engineering。However, these have an obvious disadvantage in that when we chose data with the only annual maximum data,which wasted on the data.Besides, the Annual Extreme Value (AEV) method has a similar power function of the form when the random variable is greater than a certain value. So,it is important to build a new model which contains not only the extremes of information, but also the valve cover of information, while their common features response to the new model.This article is based on fractal theory, focusing on the study of self-similarity and scale invariance, using fractal theory to study the self-similarity of wave height time series.Besides,we verify the common distribution function under certain conditions, have fractal characteristics, then propose a new model based on fractal theory.This model which contains not only the extremes of information, but also the valve cover of information, while their common features response to this model. Finally, we test our method using in-situ data recorded along the coast of Chaolian Island from 1963-1989 and compare it with traditional methods. The results show that:(1) Comparing this model with traditional models, we found that the measurements using this model were higher than the Pearson-Ⅲ distribution, lower than the extreme value distribution, which between the extreme value distribution and Pearson-Ⅲ distribution. This suggests that the new model which designed annual extreme wave heights, higher than the Pearson-Ⅲ distribution, from the reflection of the usefulness of the new model.(2)Considering the geographical and seasonal effects on wave heights, such as typhoons, etc., the extreme values recorded from June to September were analyzed and compared with annual extreme values. We found that the design wave heights during the summer were smaller when considering a return period of 100 years, but the difference was less than 8.95%.