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Constructing rainfall depth-frequency curves considering a linear trend in rainfall observations

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dc.contributor.authorSeo, Lynn-
dc.contributor.authorKim, Tae-Woong-
dc.contributor.authorChoi, Minha-
dc.contributor.authorKwon, Hyun-Han-
dc.date.accessioned2021-06-23T07:53:36Z-
dc.date.available2021-06-23T07:53:36Z-
dc.date.created2021-01-21-
dc.date.issued2012-03-
dc.identifier.issn1436-3240-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/33183-
dc.description.abstractComprehensive flood prevention plans are established in large basins to cope with recent abnormal floods in South Korea. In order to make economically effective plans, appropriate design rainfalls are critically determined from the rainfall depth-frequency curves which take the occurrence of abnormal floods into consideration. Conventional approaches to construct the rainfall depth-frequency curves are based on the stationarity assumption. However, this assumption has a critical weak aspect in that it cannot reflect non-stationarities in rainfall observations. As an alternative, this study suggests the non-stationary Gumbel model (NSGM) which incorporates a linear trend of rainfall observations into rainfall frequency analysis to construct the rainfall depth-frequency curves. A comparison of various schemes employed in the model found that the proposed NSGM permits the estimation of the distribution parameters even when shifted in the future by using linear relationships between rainfall statistics and distribution parameters, and produces more acceptable estimates of design rainfalls in the future than the conventional model. The NSGM was applied at several stations in South Korea and then expected the design rainfalls to increase by up to 15-30% in 2050.-
dc.language영어-
dc.language.isoen-
dc.publisherSpringer Verlag-
dc.titleConstructing rainfall depth-frequency curves considering a linear trend in rainfall observations-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Tae-Woong-
dc.identifier.doi10.1007/s00477-011-0549-6-
dc.identifier.scopusid2-s2.0-84856418527-
dc.identifier.wosid000300016400008-
dc.identifier.bibliographicCitationStochastic Environmental Research and Risk Assessment, v.26, no.3, pp.419 - 427-
dc.relation.isPartOfStochastic Environmental Research and Risk Assessment-
dc.citation.titleStochastic Environmental Research and Risk Assessment-
dc.citation.volume26-
dc.citation.number3-
dc.citation.startPage419-
dc.citation.endPage427-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaEnvironmental Sciences & Ecology-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalResearchAreaWater Resources-
dc.relation.journalWebOfScienceCategoryEngineering, Environmental-
dc.relation.journalWebOfScienceCategoryEngineering, Civil-
dc.relation.journalWebOfScienceCategoryEnvironmental Sciences-
dc.relation.journalWebOfScienceCategoryStatistics & Probability-
dc.relation.journalWebOfScienceCategoryWater Resources-
dc.subject.keywordPlusNONSTATIONARY APPROACH-
dc.subject.keywordPlusMODEL INTEGRATIONS-
dc.subject.keywordPlusREGIONAL CLIMATE-
dc.subject.keywordPlusEXTREME RAINFALL-
dc.subject.keywordPlusFUTURE CHANGES-
dc.subject.keywordAuthorFrequency-
dc.subject.keywordAuthorRainfall-
dc.subject.keywordAuthorTrend-
dc.subject.keywordAuthorGumbel-
dc.identifier.urlhttps://link.springer.com/article/10.1007/s00477-011-0549-6-
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ERICA 공학대학 (DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING)
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