The evaluation of regional frequency analyses methods for nonstationary data

W. Nam, S. Kim, H. Kim, K. Joo, J. H. Heo

Research output: Contribution to journalConference articlepeer-review

8 Citations (Scopus)


Regional frequency analysis is widely used to estimate more reliable quantiles of extreme hydrometeorological events. The stationarity of data is required for its application. This assumption tends to be violated due to climate change. In this paper, four nonstationary index flood models were used to analyze the nonstationary regional data. Monte Carlo simulation was used to evaluate the performances of these models for the generalized extreme value distribution with linearly time varying location parameter and constant scale and shape parameters. As a results, it was found that the index flood model with time-invariant index flood and time-variant growth curve could yield more statistically efficient quantile when record is long enough to show significant nonstationarity.

Original languageEnglish
Pages (from-to)95-98
Number of pages4
JournalIAHS-AISH Proceedings and Reports
Publication statusPublished - 2015
EventHS02 � Hydrologic Non-Stationarity and Extrapolating Models to Predict the Future in the 2015 IUGG General Assembly - Prague, Czech Republic
Duration: 2015 Jun 222015 Jul 2

Bibliographical note

Publisher Copyright:
© Author(s) 2015.

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)


Dive into the research topics of 'The evaluation of regional frequency analyses methods for nonstationary data'. Together they form a unique fingerprint.

Cite this