The evaluation of regional frequency analyses methods for nonstationary data
| Autor: | W. Nam, S. Kim, H. Kim, K. Joo, J.-H. Heo |
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| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: | |
| Zdroj: | Proceedings of the International Association of Hydrological Sciences, Vol 371, Pp 95-98 (2015) |
| Druh dokumentu: | article |
| ISSN: | 2199-8981 2199-899X |
| DOI: | 10.5194/piahs-371-95-2015 |
| Popis: | Regional frequency analysis is widely used to estimate more reliable quantiles of extreme hydro-meteorological 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. |
| Databáze: | Directory of Open Access Journals |
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