Seasonal and Non-Seasonal Generalized Pareto Distribution to Estimate Extreme Significant Wave Height in The Banda Sea

3rd International Conference on Tropical and Coastal Region Eco Development 2017

地球科学;生态环境科学

Nursamsiah^1,4 ; Sugianto, Denny Nugroho^2,3 ; Suprijanto, Jusup^1 ; Munasik^1 ; Yulianto, Bambang^1

Faculty of Fisheries and Marine Science, Diponegoro University, Jl. Prof. H. Soedarto, Tembalang, Semarang

50275, Indonesia^1

Center for Coastal Disaster Mitigation and Rehabilitation Studies, Diponegoro University, Jl. Prof. H. Soedarto, Tembalang, Semarang

50275, Indonesia^2

Departement of Oceanography, Fisheries and Marine Science Faculty, Diponegoro University, Jl. Prof. H. Soedarto, SH, Semarang

50275, Indonesia^3

Indonesian Agency for Meteorology, Climatology and Geophysics, Jl. Angkasa I No.2, Kemayoran, Jakarta

10610, Indonesia^4

关键词: Extreme wave heights;    Generalized Pareto distribution;    Generalized Pareto Distributions;    Kolmogorov-Smirnov test;    Recommendation methods;    Seasonal modeling;    Seasonal variation;    Significant wave height;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/116/1/012066/pdf
DOI  :  10.1088/1755-1315/116/1/012066

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The information of extreme wave height return level was required for maritime planning and management. The recommendation methods in analyzing extreme wave were better distributed by Generalized Pareto Distribution (GPD). Seasonal variation was often considered in the extreme wave model. This research aims to identify the best model of GPD by considering a seasonal variation of the extreme wave. By using percentile 95 % as the threshold of extreme significant wave height, the seasonal GPD and non-seasonal GPD fitted. The Kolmogorov-Smirnov test was applied to identify the goodness of fit of the GPD model. The return value from seasonal and non-seasonal GPD was compared with the definition of return value as criteria. The Kolmogorov-Smirnov test result shows that GPD fits data very well both seasonal and non-seasonal model. The seasonal return value gives better information about the wave height characteristics.