scholarly journals Return Wave Heights along the Japan Sea Coast through Regional Frequency Analysis with Modified L-Moments Method

2011 ◽  
Vol 67 (2) ◽  
pp. I_141-I_145
Author(s):  
Yoshimi GODA ◽  
Masanobu KUDAKA ◽  
Hiroyasu KAWAI
Keyword(s):  
Frequency Analysis ◽  
Japan Sea ◽  
Regional Frequency Analysis ◽  
Moments Method ◽  
The Japan Sea ◽  
Wave Heights ◽  
L Moments ◽  
Regional Frequency ◽  
Sea Coast

scholarly journals INCORPORATION OF WEIBULL DISTRIBUTION IN L-MOMENTS METHOD FOR

2011 ◽  
Vol 1 (32) ◽  
pp. 62 ◽  
Author(s):  
Yoshimi Goda ◽  
Masanobu Kudaka ◽  
Hiroyasu Kawai
Keyword(s):  
Weibull Distribution ◽  
Frequency Analysis ◽  
Coastal Engineering ◽  
Regional Frequency Analysis ◽  
Eastern Coast ◽  
Ocean Engineering ◽  
Extreme Wave ◽  
Wave Heights ◽  
L Moments ◽  
Regional Frequency

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

scholarly journals Regional Frequency Analysis of Extremes Precipitation Using L-Moments and Partial L-Moments

2017 ◽  
Vol 2017 ◽  
pp. 1-20 ◽  
Author(s):  
Said Arab Khan ◽  
Ijaz Hussain ◽  
Tajammal Hussain ◽  
Muhammad Faisal ◽  
Yousaf Shad Muhammad ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Extreme Precipitation ◽  
Regional Frequency Analysis ◽  
Monthly Precipitation ◽  
Monte Carlo Simulation Study ◽  
Khyber Pakhtunkhwa ◽  
Northern Areas ◽  
L Moments ◽  
Social Environmental ◽  
Regional Frequency

Extremes precipitation may cause a series of social, environmental, and ecological problems. Estimation of frequency of extreme precipitations and its magnitude is vital for making decisions about hydraulic structures such as dams, spillways, and dikes. In this study, we focus on regional frequency analysis of extreme precipitation based on monthly precipitation records (1999–2012) at 17 stations of Northern areas and Khyber Pakhtunkhwa, Pakistan. We develop regional frequency methods based on L-moment and partial L-moments (L- and PL-moments). The L- and PL-moments are derived for generalized extreme value (GEV), generalized logistic (GLO), generalized normal (GNO), and generalized Pareto (GPA) distributions. The Z-statistics and L- and PL-moments ratio diagrams of GNO, GEV, and GPA distributions were identified to represent the statistical properties of extreme precipitation in Northern areas and Khyber Pakhtunkhwa, Pakistan. We also perform a Monte Carlo simulation study to examine the sampling properties of L- and PL-moments. The results show that PL-moments perform better than L-moments for estimating large return period events.

scholarly journals Hujan rancangan berdasarkan analisis frekuensi regional dengan metode tl-moment

2017 ◽  
Vol 12 (1) ◽  
pp. 1-16
Author(s):  
Segel Ginting ◽  
William M Putuhena
Keyword(s):  
Frequency Analysis ◽  
Probability Distributions ◽  
Large Error ◽  
Extreme Value ◽  
Regional Frequency Analysis ◽  
Generalized Extreme Value ◽  
Generalized Pareto ◽  
Moment Ratio ◽  
Moments Method ◽  
Regional Frequency

The designstorm wereestimated by applying the regional frequency analysis provides benefits to a datasetwith limited amount of data has many advantages. Minimum data used in calculating the amount of design stromhas a very large error for higherreturn period. Therefore, the regional frequency analysis was used based on TL-moments method. There arethree types of probability distributions used in this study, namely the Generalized Extreme Value (GEV), Generalized Pareto (GPA) and the Generalized Logistic (GLO). Two of the three typesprobability distributions are the best choice by the TL-moment ratio diagrams which are Generalized Extreme Value, and Generalized Logistic. Ananother analysis wasconducted by the Z test and the Generalized Extreme Value (GEV) gives the best results. Therefore, the designs strom which was estimated based on the regional frequency analysis in Jakarta watersheds using the Generalized Extreme Value (GEV) has been determined.

REGIONAL FREQUENCY ANALYSIS ON PENINSULAR MALAYSIA USING L-MOMENTS

2018 ◽  
Vol 103 (8) ◽  
pp. 1379-1398
Author(s):  
Sharainie Sahrin ◽  
Norazlina Ismail ◽  
Nor Eliza Alias
Keyword(s):  
Frequency Analysis ◽  
Peninsular Malaysia ◽  
Regional Frequency Analysis ◽  
L Moments ◽  
Regional Frequency
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