Application of bivariate frequency analysis to the derivation of rainfall-frequency curves
- Authors
- Lee, Chang Hwan; Kim, Tae-Woong; Chung, Gunhui; Choi, Minha; Yoo, Chulsang
- Issue Date
- 3월-2010
- Publisher
- SPRINGER
- Keywords
- Bivatiate frequency analysis; Design rainfall; Gumbel mixed model
- Citation
- STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, v.24, no.3, pp.389 - 397
- Indexed
- SCIE
SCOPUS
- Journal Title
- STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
- Volume
- 24
- Number
- 3
- Start Page
- 389
- End Page
- 397
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/116945
- DOI
- 10.1007/s00477-009-0328-9
- ISSN
- 1436-3240
- Abstract
- Bivariate distributions have been recently employed in hydrologic frequency analysis to analyze the joint probabilistic characteristics of multivariate storm events. This study aims to derive practical solutions of application for the bivariate distribution to estimate design rainfalls corresponding to the desired return periods. Using the Gumbel mixed model, this study constructed rainfall-frequency curves at sample stations in Korea which provide joint relationships between amount, duration, and frequency of storm events. Based on comparisons and analyses of the rainfall-frequency curves derived from univariate and bivariate storm frequency analyses, this study found that conditional frequency analysis provides more appropriate estimates of design rainfalls as it more accurately represents the natural relationship between storm properties than the conventional univariate storm frequency analysis.
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Collections - College of Engineering > School of Civil, Environmental and Architectural Engineering > 1. Journal Articles
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