<i>HESS Opinions</i> "More efforts and scientific rigour are needed to attribute trends in flood time series"

The question whether the magnitude and frequency of floods have changed due to climate change or other drivers of change is of high interest. The number of flood trend studies is rapidly rising. When changes are detected, many studies link the identified change to the underlying causes, i.e. they at...

Full description

Bibliographic Details
Main Authors: Y. Hundecha, J. Delgado, S. Uhlemann, S. Vorogushyn, B. Merz
Format: Article
Language:English
Published: Copernicus Publications 2012-05-01
Series:Hydrology and Earth System Sciences
Online Access:http://www.hydrol-earth-syst-sci.net/16/1379/2012/hess-16-1379-2012.pdf
id doaj-02886276ec6840bc88de86710e64fdff
record_format Article
spelling doaj-02886276ec6840bc88de86710e64fdff2020-11-24T22:32:03ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382012-05-011651379138710.5194/hess-16-1379-2012<i>HESS Opinions</i> "More efforts and scientific rigour are needed to attribute trends in flood time series"Y. HundechaJ. DelgadoS. UhlemannS. VorogushynB. MerzThe question whether the magnitude and frequency of floods have changed due to climate change or other drivers of change is of high interest. The number of flood trend studies is rapidly rising. When changes are detected, many studies link the identified change to the underlying causes, i.e. they attribute the changes in flood behaviour to certain drivers of change. We propose a hypothesis testing framework for trend attribution which consists of essential ingredients for a sound attribution: evidence of consistency, evidence of inconsistency, and provision of confidence statement. Further, we evaluate the current state-of-the-art of flood trend attribution. We assess how selected recent studies approach the attribution problem, and to which extent their attribution statements seem defendable. In our opinion, the current state of flood trend attribution is poor. Attribution statements are mostly based on qualitative reasoning or even speculation. Typically, the focus of flood trend studies is the detection of change, i.e. the statistical analysis of time series, and attribution is regarded as an appendix: (1) flood time series are analysed by means of trend tests, (2) if a significant change is detected, a hypothesis on the cause of change is given, and (3) explanations or published studies are sought which support the hypothesis. We believe that we need a change in perspective and more scientific rigour: detection should be seen as an integral part of the more challenging attribution problem, and detection and attribution should be placed in a sound hypothesis testing framework.http://www.hydrol-earth-syst-sci.net/16/1379/2012/hess-16-1379-2012.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Y. Hundecha
J. Delgado
S. Uhlemann
S. Vorogushyn
B. Merz
spellingShingle Y. Hundecha
J. Delgado
S. Uhlemann
S. Vorogushyn
B. Merz
<i>HESS Opinions</i> "More efforts and scientific rigour are needed to attribute trends in flood time series"
Hydrology and Earth System Sciences
author_facet Y. Hundecha
J. Delgado
S. Uhlemann
S. Vorogushyn
B. Merz
author_sort Y. Hundecha
title <i>HESS Opinions</i> "More efforts and scientific rigour are needed to attribute trends in flood time series"
title_short <i>HESS Opinions</i> "More efforts and scientific rigour are needed to attribute trends in flood time series"
title_full <i>HESS Opinions</i> "More efforts and scientific rigour are needed to attribute trends in flood time series"
title_fullStr <i>HESS Opinions</i> "More efforts and scientific rigour are needed to attribute trends in flood time series"
title_full_unstemmed <i>HESS Opinions</i> "More efforts and scientific rigour are needed to attribute trends in flood time series"
title_sort <i>hess opinions</i> "more efforts and scientific rigour are needed to attribute trends in flood time series"
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2012-05-01
description The question whether the magnitude and frequency of floods have changed due to climate change or other drivers of change is of high interest. The number of flood trend studies is rapidly rising. When changes are detected, many studies link the identified change to the underlying causes, i.e. they attribute the changes in flood behaviour to certain drivers of change. We propose a hypothesis testing framework for trend attribution which consists of essential ingredients for a sound attribution: evidence of consistency, evidence of inconsistency, and provision of confidence statement. Further, we evaluate the current state-of-the-art of flood trend attribution. We assess how selected recent studies approach the attribution problem, and to which extent their attribution statements seem defendable. In our opinion, the current state of flood trend attribution is poor. Attribution statements are mostly based on qualitative reasoning or even speculation. Typically, the focus of flood trend studies is the detection of change, i.e. the statistical analysis of time series, and attribution is regarded as an appendix: (1) flood time series are analysed by means of trend tests, (2) if a significant change is detected, a hypothesis on the cause of change is given, and (3) explanations or published studies are sought which support the hypothesis. We believe that we need a change in perspective and more scientific rigour: detection should be seen as an integral part of the more challenging attribution problem, and detection and attribution should be placed in a sound hypothesis testing framework.
url http://www.hydrol-earth-syst-sci.net/16/1379/2012/hess-16-1379-2012.pdf
work_keys_str_mv AT yhundecha ihessopinionsimoreeffortsandscientificrigourareneededtoattributetrendsinfloodtimeseries
AT jdelgado ihessopinionsimoreeffortsandscientificrigourareneededtoattributetrendsinfloodtimeseries
AT suhlemann ihessopinionsimoreeffortsandscientificrigourareneededtoattributetrendsinfloodtimeseries
AT svorogushyn ihessopinionsimoreeffortsandscientificrigourareneededtoattributetrendsinfloodtimeseries
AT bmerz ihessopinionsimoreeffortsandscientificrigourareneededtoattributetrendsinfloodtimeseries
_version_ 1725735374151483392