Attribution of long-term changes in peak river flows in Great Britain

Aoibheann Brady, Julian Faraway, Ilaria Prosdocimi

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

We investigate the evidence for changes in the magnitude of peak river flows in Great Britain. We focus on a set of 117 near-natural “benchmark” catchments to detect trends not driven by land use and other human impacts, and aim to attribute trends in peak river flows to some climate indices such as the North Atlantic Oscillation (NAO) and the East Atlantic (EA) index. We propose modelling all stations together in a Bayesian multilevel framework to be better able to detect any signal that is present in the data by pooling information across several stations. This approach leads to the detection of a clear countrywide time trend. Additionally, in a univariate approach, both the EA and NAO indices appear to have a considerable association with peak river flows. When a multivariate approach is taken to unmask the collinearity between climate indices and time, the association between NAO and peak flows disappears, while the association with EA remains clear. This demonstrates the usefulness of a multivariate and multilevel approach when it comes to accurately attributing trends in peak river flows.
Original languageEnglish
Pages (from-to)1159-1170
Number of pages12
JournalHydrological Sciences Journal
Volume64
Issue number10
Early online date25 Jun 2019
DOIs
Publication statusPublished - 2019

Keywords

  • attribution
  • climate change
  • flooding
  • multilevel models

ASJC Scopus subject areas

  • Water Science and Technology

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