Frequency analysis of precipitation extremes under a changing climate: a case study in Heihe River basin, China

The stationary assumption for the traditional frequency analysis of precipitation extremes has been challenged due to natural climate variability or human intervention. To overcome this challenge, this paper, taking Heihe River basin as the case study, performed the frequency analysis by developing...

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Autores principales:	Qingyun Tian, Zhanling Li, Xueli Sun
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	confidence interval gev nonstationary precipitation extremes Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/ca95d6b4fa304f1aa00ae0608a9b0b42
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spelling	oai:doaj.org-article:ca95d6b4fa304f1aa00ae0608a9b0b422021-11-05T18:48:08ZFrequency analysis of precipitation extremes under a changing climate: a case study in Heihe River basin, China2040-22442408-935410.2166/wcc.2020.170https://doaj.org/article/ca95d6b4fa304f1aa00ae0608a9b0b422021-05-01T00:00:00Zhttp://jwcc.iwaponline.com/content/12/3/772https://doaj.org/toc/2040-2244https://doaj.org/toc/2408-9354The stationary assumption for the traditional frequency analysis of precipitation extremes has been challenged due to natural climate variability or human intervention. To overcome this challenge, this paper, taking Heihe River basin as the case study, performed the frequency analysis by developing a nonstationary GEV model for those seasonal maximum daily precipitation (SMP) time series with nonstationary characteristics by employing the GEV conditional density estimation network. In addition, the confidence intervals (CIs) of estimated return levels were also investigated by using the residual bootstrap technique. Results showed that, 7 of 12 SMP series were nonstationary. The parameters in the nonstationary model were specified as functions of time varying or correlated climate indices varying covariates. The frequency analysis showed that the return levels varied linearly or nonlinearly with covariates. Precipitation extremes with the same magnitude in the study area were found to be occurring more frequently in the future. The CIs of such return levels increased with time passing, especially those from the more complex GEV11 model, embedding a nonlinear increasing trend in model scale parameters. It implied that the increase of model complexity is likely to result in the increase of uncertainty in estimates.Qingyun TianZhanling LiXueli SunIWA Publishingarticleconfidence intervalgevnonstationaryprecipitation extremesEnvironmental technology. Sanitary engineeringTD1-1066Environmental sciencesGE1-350ENJournal of Water and Climate Change, Vol 12, Iss 3, Pp 772-786 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	confidence interval gev nonstationary precipitation extremes Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350
spellingShingle	confidence interval gev nonstationary precipitation extremes Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Qingyun Tian Zhanling Li Xueli Sun Frequency analysis of precipitation extremes under a changing climate: a case study in Heihe River basin, China
description	The stationary assumption for the traditional frequency analysis of precipitation extremes has been challenged due to natural climate variability or human intervention. To overcome this challenge, this paper, taking Heihe River basin as the case study, performed the frequency analysis by developing a nonstationary GEV model for those seasonal maximum daily precipitation (SMP) time series with nonstationary characteristics by employing the GEV conditional density estimation network. In addition, the confidence intervals (CIs) of estimated return levels were also investigated by using the residual bootstrap technique. Results showed that, 7 of 12 SMP series were nonstationary. The parameters in the nonstationary model were specified as functions of time varying or correlated climate indices varying covariates. The frequency analysis showed that the return levels varied linearly or nonlinearly with covariates. Precipitation extremes with the same magnitude in the study area were found to be occurring more frequently in the future. The CIs of such return levels increased with time passing, especially those from the more complex GEV11 model, embedding a nonlinear increasing trend in model scale parameters. It implied that the increase of model complexity is likely to result in the increase of uncertainty in estimates.
format	article
author	Qingyun Tian Zhanling Li Xueli Sun
author_facet	Qingyun Tian Zhanling Li Xueli Sun
author_sort	Qingyun Tian
title	Frequency analysis of precipitation extremes under a changing climate: a case study in Heihe River basin, China
title_short	Frequency analysis of precipitation extremes under a changing climate: a case study in Heihe River basin, China
title_full	Frequency analysis of precipitation extremes under a changing climate: a case study in Heihe River basin, China
title_fullStr	Frequency analysis of precipitation extremes under a changing climate: a case study in Heihe River basin, China
title_full_unstemmed	Frequency analysis of precipitation extremes under a changing climate: a case study in Heihe River basin, China
title_sort	frequency analysis of precipitation extremes under a changing climate: a case study in heihe river basin, china
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/ca95d6b4fa304f1aa00ae0608a9b0b42
work_keys_str_mv	AT qingyuntian frequencyanalysisofprecipitationextremesunderachangingclimateacasestudyinheiheriverbasinchina AT zhanlingli frequencyanalysisofprecipitationextremesunderachangingclimateacasestudyinheiheriverbasinchina AT xuelisun frequencyanalysisofprecipitationextremesunderachangingclimateacasestudyinheiheriverbasinchina
_version_	1718444126508154880

Frequency analysis of precipitation extremes under a changing climate: a case study in Heihe River basin, China

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