Dependence of ocean wave return levels on water depth and sampling length: A focus on the South Yellow Sea.

A deterministic Extreme Value Analysis method is of particular importance in an engineering-oriented context. In this paper, three extreme value analysis (EVA) methods, in which annual maxima, monthly maxima or the Peaks-Over-Threshold are fitted into Generalized Extreme Value distribution (GEV) function or Generalized Pareto distribution (GP) function, are used to estimate return values of significant wave height. Sensitivity of return levels on water depth and sampling length is vigorously investigated, based on a 40-year long and high-resolution wave hindcast for the South Yellow Sea (SYS). A spatially-and-temporally varied POT sampling method combined with GP function produces most conservative and confident estimates of return levels for a large return period, but produces wider confidence level than the other two EVA approaches based on GEV function for short return period. In the SYS, the return level estimates are significantly reduced with a longer sample length. However, we find that the reduction is closely related to the long-term trend in extreme wave heights, rather than due to the sampling effect. From deep to shallow waters, spatial inhomogeneity of return levels increases, which should be considered in the engineering practice. • A sophisticated investigation was conducted on the dependence of the return level of extreme wave heights in the SYS to the epistemic and intrinsic factors. • GEV distribution model is more confident in short-term return level estimates, whilst GP distribution model is more confident for long-term return level estimates. • The inter-tidal region although is least sensitive to sampling length for the return level estunates, whilst contains the largest spatial inhomogeneity of extreme wave heights. • A temporal negative long-term trend was found in the return levels of extreme wave height in the SYS. [ABSTRACT FROM AUTHOR]