REVISION OF REGIONAL FREQUENCY ANALYSIS METHOD FOR EXTREME WAVE HEIGHTS

2011 ◽  
pp. 1711-1719 ◽  
Author(s):  
Y. GODA ◽  
M. KUDAKA ◽  
H. KAWAI
2011 ◽  
Vol 1 (32) ◽  
pp. 62 ◽  
Author(s):  
Yoshimi Goda ◽  
Masanobu Kudaka ◽  
Hiroyasu Kawai

The L-moments of the Weibull distribution are derived and incorporated in the regional frequency analysis of peaksover-threshold significant wave heights at eleven stations along the eastern coast of Japan Sea. The effective duration of wave measurements varies from 18.0 to 37.2 years with the mean rate of 10.4 to 15.1 events per year. The eleven stations are divided into three regions to assure homogeneity of the data. Both the Weibull and Generalized Pareto (GPA) distributions fit well to the observed data. The 100-year wave height varied from 8.2 to 11.2 m by the Weibull and 7.6 to 10.3 m by the GPA. The GPA distribution is not recommended for determination of design waves for these stations because it has an inherent upper limit and a tendency of under-prediction. References Coles, S. 2001. An Introduction to Statistical Modeling of Extreme Values, Springer, 208p. Goda, Y., Konagaya, O., Takeshita, N., Hitomi, H., and T. Nagai. 2000. Population distribution of extreme wave heights estimated through regional analysis, Coastal Engineering 2000 (Proc. 26th ICCE, Sydney), ASCE, Sydney, 1078-1091. Greenwood, J A., J. M. Landwehr, N. C. Matalas, and J. R. Wallis. 1978. Probability weighted moments: Definition and relation to parameters of several distributions expressable in inverse form, Water Resources Res., Vol. 15, No. 5, pp. 1049-1064. http://dx.doi.org/10.1029/WR015i005p01049 Hosking, J. R. M. 1990. L-moments: Analysis and estimation of distributions using linear combinations of order statistics, J. Roy. Statistical Soc., Series B, 52, pp. 105-24. Hosking, J. R. M. and J. R. Wallis. 1997. Regional Frequency Analysis, Cambridge Univ. Press, 224p. http://dx.doi.org/10.1017/CBO9780511529443 Ma, Q.-S., Li, Y.-B., and J. Li .2006. Regional frequency analysis of siginicant wave heights based on L-moments, China Ocean Engineering, 20(1), pp. 85-98. Petruaskas, C. and P. M. Aagaard. 1971. Extrapolation of historical storm data for estimating design wave heights, J. Soc. Petroleum Engrg., 11, pp. 23-27. van Gelder, P. H. A. J. M. 2000. Statistical Methods for the Risk-Based Design of Civil Structures, Ph.D. thesis Delft University of Technology, 249p. van Gelder, P. H. A. J. M., J. De Ronde, N. W. Neykov, and P. Neytchev. 2000. Regional frequency analysis of extreme wave heights: trading space for time, Coastal Engineering 2000


Author(s):  
Cla´udia Lucas ◽  
G. Muraleedharan ◽  
C. Guedes Soares

Regional frequency analysis (RFA) based on L-moments is applied to the HIPOCAS hindcast data using daily maximum significant wave heights offshore Portugal to identify the homogeneous regions and to suggest the appropriate regional frequency distribution and extreme quantiles. Several statistics are computed at the various grid points in the area of study to classify the wave conditions of the regions. The daily maximum significant wave heights of the rough winter month January are used for this case study. The results of the study have shown that there are 3 homogeneous regions in the offshore region under investigation (35°–45°N, −9.5°–−11°W) comprising from 15 equally spaced grid points referring to an area of 0.25°×0.25°. It is interesting to observe that the algorithm is able to identify neighboring grid points as members of different regions. The maximum discrepancy between the at-sites’ extreme quantiles and their respective regional quantiles is 0.82 m for a return period of 100 years.


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