Application of bivariate frequency analysis for estimating design rainfalls
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwon, Young moon | - |
dc.contributor.author | Han, Jeong woo | - |
dc.contributor.author | Kim, Tae woong | - |
dc.date.accessioned | 2021-06-23T18:39:55Z | - |
dc.date.available | 2021-06-23T18:39:55Z | - |
dc.date.issued | 2008-00 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/43036 | - |
dc.description.abstract | Univariate frequency analyses are widely used in practical hydrologic design. However, a storm event is characterized by storm amount, peak intensity, and storm duration. To fully understand these characteristics and to use them appropriately in hydrologic design, a multivariate statistical approach is necessary. This study applied Gumbel mixed model to bivatiate storm frequency analysis using hourly rainfall data collected for 34 years at the Jecheon rainfall gauge station in Korea. This study estimated bivariate return periods of a storm such as joint return periods and conditional return periods based on the estimation of joint cumulative distribution functions of storm characteristics. © 2008 ASCE. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | American Society of Civil Engineers | - |
dc.title | Application of bivariate frequency analysis for estimating design rainfalls | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1061/40976(316)616 | - |
dc.identifier.scopusid | 2-s2.0-79251527239 | - |
dc.identifier.bibliographicCitation | World Environmental and Water Resources Congress 2008: Ahupua'a - Proceedings of the World Environmental and Water Resources Congress 2008, v.316 | - |
dc.citation.title | World Environmental and Water Resources Congress 2008: Ahupua'a - Proceedings of the World Environmental and Water Resources Congress 2008 | - |
dc.citation.volume | 316 | - |
dc.type.docType | Conference Paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | other | - |
dc.subject.keywordPlus | Bivariate | - |
dc.subject.keywordPlus | Design rainfalls | - |
dc.subject.keywordPlus | Frequency Analysis | - |
dc.subject.keywordPlus | Gumbel mixed models | - |
dc.subject.keywordPlus | Hydrologic design | - |
dc.subject.keywordPlus | Joint cumulative distribution function | - |
dc.subject.keywordPlus | Joint return period | - |
dc.subject.keywordPlus | Multivariate statistical approaches | - |
dc.subject.keywordPlus | Peak intensity | - |
dc.subject.keywordPlus | Rainfall | - |
dc.subject.keywordPlus | Rainfall data | - |
dc.subject.keywordPlus | Return periods | - |
dc.subject.keywordPlus | Storm events | - |
dc.subject.keywordPlus | Univariate | - |
dc.subject.keywordPlus | Design | - |
dc.subject.keywordPlus | Distribution functions | - |
dc.subject.keywordPlus | Estimation | - |
dc.subject.keywordPlus | Floods | - |
dc.subject.keywordPlus | Frequency estimation | - |
dc.subject.keywordPlus | Hydraulics | - |
dc.subject.keywordPlus | Multivariant analysis | - |
dc.subject.keywordPlus | Rain | - |
dc.subject.keywordPlus | Storms | - |
dc.subject.keywordPlus | Stream flow | - |
dc.subject.keywordPlus | Water resources | - |
dc.subject.keywordAuthor | Estimation | - |
dc.subject.keywordAuthor | Floods | - |
dc.subject.keywordAuthor | Frequency analysis | - |
dc.subject.keywordAuthor | Rainfall | - |
dc.subject.keywordAuthor | Stream flow | - |
dc.identifier.url | https://ascelibrary.org/doi/10.1061/40976%28316%29616 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.