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dc.contributor.author
Moraga, Jorge Sebastián
dc.contributor.author
Peleg, Nadav
dc.contributor.author
Molnar, Peter
dc.contributor.author
Fatichi, Simone
dc.contributor.author
Burlando, Paolo
dc.date.accessioned
2022-10-25T06:22:51Z
dc.date.available
2022-10-22T03:04:40Z
dc.date.available
2022-10-25T06:22:51Z
dc.date.issued
2022-10
dc.identifier.issn
0885-6087
dc.identifier.issn
1099-1085
dc.identifier.other
10.1002/hyp.14695
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/577286
dc.identifier.doi
10.3929/ethz-b-000577286
dc.description.abstract
A major challenge in assessing the impacts of climate change on hydrological processes lies in dealing with large degrees of uncertainty in the future climate projections. Part of the uncertainty is owed to the intrinsic randomness of climate phenomena, which is considered irreducible. Additionally, modelling the response of hydrological processes to the changing climate requires the use of a chain of numerical models, each of which contributes some degree of uncertainty to the final outputs. As a result, hydrological projections, despite the progressive increase in the accuracy of the models along the chain, still display high levels of uncertainty, especially at small temporal and spatial scales. In this work, we present a framework to quantify and partition the uncertainty of hydrological processes emerging from climate models and internal variability, across a broad range of scales. Using the example of two mountainous catchments in Switzerland, we produced high-resolution ensembles of climate and hydrological data using a two-dimensional weather generator (AWE-GEN- 2d) and a distributed hydrological model (TOPKAPI-ETH). We quantified the uncertainty in hydrological projections towards the end of the century through the estimation of the values of signal-to-noise ratios (STNR). We found small STNR absolute values (<1) in the projection of annual streamflow for most sub-catchments in both study sites that are dominated by the large natural variability of precipitation (explains ~70% of total uncertainty). Furthermore, we investigated in detail specific hydrological components that are critical in the model chain. For example, snowmelt and liquid precipitation exhibit robust change signals, which translates into high STNR values for streamflow during warm seasons and at higher elevations, together with a larger contribution of climate model uncertainty. In contrast, projections of extreme high flows show low STNR values due to large internal climate variability across all elevations, which limits the potential for narrowing their estimation uncertainty.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Wiley
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc/4.0/
dc.subject
climate change
en_US
dc.subject
hydrological modelling
en_US
dc.subject
hydrological uncertainty
en_US
dc.subject
uncertainty partition
en_US
dc.subject
weather generator
en_US
dc.title
Uncertainty in high-resolution hydrological projections: Partitioning the influence of climate models and natural climate variability
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution-NonCommercial 4.0 International
dc.date.published
2022-09-12
ethz.journal.title
Hydrological Processes
ethz.journal.volume
36
en_US
ethz.journal.issue
10
en_US
ethz.journal.abbreviated
Hydrol. Process.
ethz.pages.start
e14695
en_US
ethz.size
15 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Chichester
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02608 - Institut für Umweltingenieurwiss. / Institute of Environmental Engineering::03473 - Burlando, Paolo / Burlando, Paolo
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02608 - Institut für Umweltingenieurwiss. / Institute of Environmental Engineering::03473 - Burlando, Paolo / Burlando, Paolo
ethz.date.deposited
2022-10-22T03:04:44Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2022-10-25T06:22:52Z
ethz.rosetta.lastUpdated
2023-02-07T07:19:20Z
ethz.rosetta.versionExported
true
ethz.COinS
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