Publication:
The role of antecedent conditions in translating precipitation events into extreme floods at the catchment scale and in a large-basin context

cris.virtual.author-orcid0000-0002-6155-837X
cris.virtualsource.author-orcid47ae548f-ed8b-4153-8d41-dcd3f0e73940
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cris.virtualsource.author-orcidwill be referenced::ORCID::0000-0001-6991-0975
datacite.rightsopen.access
dc.contributor.authorStaudinger, Maria
dc.contributor.authorKauzlaric, Martina
dc.contributor.authorMas, Alexandre
dc.contributor.authorEvin, Guillaume
dc.contributor.authorHingray, Benoit
dc.contributor.authorViviroli, Daniel
dc.date.accessioned2025-03-18T11:06:19Z
dc.date.available2025-03-18T11:06:19Z
dc.date.issued2025-01-16
dc.description.abstractIn this study, we analyze how precipitation, antecedent conditions, and their spatial patterns and interactions lead to extreme floods in a large catchment. The analysis is based on 10 000 years of continuous simulations from a hydro-meteorological modelling chain for a large catchment, the Aare River basin, Switzerland. To account for different flood-generating processes, we based our work on simulations with hourly time resolution. The hydro-meteorological modelling chain consisted of a stochastic weather generator (GWEX), a bucket-type hydrological model (HBV), and a routing system (RS MINERVE), providing the hydrological basis for flood protection management in the Aare River basin. From the long continuous simulations of runoff, snow, soil moisture, and dynamic storage, we were able to assess which combinations of antecedent conditions and triggering precipitation lead to extreme floods in the sub-basins of the Aare catchment. We found that only about 18 % to 44 % (depending on the sub-catchment) of annual maximum precipitation (AMP) and simulated annual maximum flood (AMF) events occurred simultaneously, highlighting the importance of antecedent conditions for the generation of large floods. For most sub-catchments in the 200–500 km2 range, after return periods greater than 500 years we found only AMF caused by triggering AMP, which is notably higher than the return periods typically used for design floods. Spatial organization within a larger area is complicated. After routing the simulated runoff, we analyzed the important patterns and drivers of extreme flooding at the outlet of the Aare River basin using a random forest. The different return period classes had distinct key predictors and showed specific spatial patterns of antecedent conditions in the sub-catchments, leading to different degrees of extreme flooding. While precipitation and soil moisture conditions from almost all sub-catchments were important for more frequent floods, for rarer events only the conditions in specific sub-catchments were important. Snow conditions were important only from specific sub-catchments and for more frequent events.
dc.description.sponsorshipInstitute of Geography
dc.description.sponsorshipOeschger Centre for Climate Change Research (OCCR) - MobiLab
dc.description.sponsorshipUniversity of Zurich
dc.description.sponsorshipOeschger Centre for Climate Change Research (OCCR)
dc.description.sponsorshipUniversité Grenoble Alpes
dc.identifier.doi10.48620/86051
dc.identifier.publisherDOI10.5194/nhess-25-247-2025
dc.identifier.urihttps://boris-portal.unibe.ch/handle/20.500.12422/206672
dc.language.isoen
dc.publisherEuropean Geosciences Union
dc.relation.fundingSwiss Federal Office for the Environment
dc.relation.fundingSwiss Federal Office of Energy
dc.relation.grantno19.0104.PJ / 3C01 E3B6F
dc.relation.grantnoSI/502150-01
dc.relation.ispartofNatural Hazards and Earth System Sciences
dc.relation.issn1684-9981
dc.relation.issn1561-8633
dc.relation.producthttps://doi.org/10.5194/nhess-25-247-2025-supplement
dc.subject.ddc500 - Science::550 - Earth sciences & geology
dc.subject.ddc900 - History::910 - Geography & travel
dc.titleThe role of antecedent conditions in translating precipitation events into extreme floods at the catchment scale and in a large-basin context
dc.typearticle
dspace.entity.typePublication
dspace.file.typetext
oaire.citation.endPage265
oaire.citation.issue1
oaire.citation.startPage247
oaire.citation.volume25
oairecerif.author.affiliationUniversity of Zurich
oairecerif.author.affiliationOeschger Centre for Climate Change Research (OCCR)
oairecerif.author.affiliationUniversité Grenoble Alpes
oairecerif.author.affiliationUniversité Grenoble Alpes
oairecerif.author.affiliationUniversité Grenoble Alpes
oairecerif.author.affiliationUniversity of Zurich
oairecerif.author.affiliation2Geographisches Institut (GIUB) - Klimafolgenforschung
oairecerif.author.affiliation3Institute of Geography
oairecerif.author.affiliation4Oeschger Centre for Climate Change Research (OCCR) - MobiLab
unibe.additional.sponsorshipInstitute of Geography
unibe.additional.sponsorshipOeschger Centre for Climate Change Research (OCCR) - MobiLab
unibe.contributor.rolecorresponding author
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unibe.description.ispublishedpub
unibe.refereedtrue
unibe.subtype.articlejournal

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