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http://dx.doi.org/10.3741/JKWRA.2008.41.5.517

Regional Rainfall Frequency Analysis by Multivariate Techniques  

Nam, Woo-Sung (Dept. of Civil Engrg., Yonsei University)
Kim, Tae-Soon (School of Civil & Environmental Engrg., Yonsei University)
Shin, Ju-Young (Dept. of Civil Engrg., Yonsei University)
Heo, Jun-Haeng (School of Civil & Environmental Engrg., Yonsei University)
Publication Information
Journal of Korea Water Resources Association / v.41, no.5, 2008 , pp. 517-525 More about this Journal
Abstract
Regional rainfall quantile depends on the identification of hydrologically homogeneous regions. Various variables relevant to precipitation can be used to form regions. Since the type and number of variables may lead to improve the efficiency of partitioning, it is important to select those precipitation related variables, which represent most of the information from all candidate variables. Multivariate analysis techniques can be used for this purpose. Procrustes analysis which can decrease the dimension of variables based on their correlations, are applied in this study. 42 rainfall related variables are decreased into 21 ones by Procrustes analysis. Factor analysis is applied to those selected variables and then 5 factors are extracted. Fuzzy-c means technique classifies 68 stations into 6 regions. As a result, the GEV distributions are fitted to 6 regions while the lognormal and generalized logistic distributions are fitted to 5 regions. For the comparison purpose with previous results, rainfall quantiles based on generalized logistic distribution are estimated by at-site frequency analysis, index flood method, and regional shape estimation method.
Keywords
Procrustes analysis; factor analysis; fuzzy-c means; regional frequency analysis;
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