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

Q. Tian,Zhanling Li,Xueli Sun

Published 2020 in Journal of Water and Climate Change

ABSTRACT

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. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/). doi: 10.2166/wcc.2020.170 om http://iwaponline.com/jwcc/article-pdf/12/3/772/893800/jwc0120772.pdf er 2021 Qingyun Tian Zhanling Li (corresponding author) Xueli Sun School of Water Resources and Environment, China University of Geosciences, Beijing 100083, China and MOE Key Laboratory of Groundwater Circulation and Environmental Evolution, China University of Geosciences (Beijing), Beijing 100083, China E-mail: zhanling.li@cugb.edu.cn

PUBLICATION RECORD

  • Publication year

    2020

  • Venue

    Journal of Water and Climate Change

  • Publication date

    2020-01-28

  • Fields of study

    Environmental Science

  • Identifiers
    DOI 10.2166/wcc.2020.170
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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