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Inter-comparison of statistical downscaling methods for projection of extreme flow indices across Europe

  • The effect of methods of statistical downscaling of daily precipitation on changes in extreme flow indices under a plausible future climate change scenario was investigated in 11 catchments selected from 9 countries in different parts of Europe. The catchments vary from 67 to 6171 km(2) in size and cover different climate zones. 15 regional climate model outputs and 8 different statistical downscaling methods, which are broadly categorized as change factor and bias correction based methods, were used for the comparative analyses. Different hydrological models were implemented in different catchments to simulate daily runoff. A set of flood indices were derived from daily flows and their changes have been evaluated by comparing their values derived from simulations corresponding to the current and future climate. Most of the implemented downscaling methods project an increase in the extreme flow indices in most of the catchments. The catchments where the extremes are expected to increase have a rainfall dominated flood regime. In theseThe effect of methods of statistical downscaling of daily precipitation on changes in extreme flow indices under a plausible future climate change scenario was investigated in 11 catchments selected from 9 countries in different parts of Europe. The catchments vary from 67 to 6171 km(2) in size and cover different climate zones. 15 regional climate model outputs and 8 different statistical downscaling methods, which are broadly categorized as change factor and bias correction based methods, were used for the comparative analyses. Different hydrological models were implemented in different catchments to simulate daily runoff. A set of flood indices were derived from daily flows and their changes have been evaluated by comparing their values derived from simulations corresponding to the current and future climate. Most of the implemented downscaling methods project an increase in the extreme flow indices in most of the catchments. The catchments where the extremes are expected to increase have a rainfall dominated flood regime. In these catchments, the downscaling methods also project an increase in the extreme precipitation in the seasons when the extreme flows occur. In catchments where the flooding is mainly caused by spring/summer snowmelt, the downscaling methods project a decrease in the extreme flows in three of the four catchments considered. A major portion of the variability in the projected changes in the extreme flow indices is attributable to the variability of the climate model ensemble, although the statistical downscaling methods contribute 35-60% of the total variance. (C) 2016 Elsevier B.V. All rights reserved.show moreshow less

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Author details:Yeshewatesfa Hundecha, Maria A. Sunyer, Deborah Lawrence, Henrik Madsen, Patrick Willems, Gerd BürgerORCiDGND, Jurate Kriauciuniene, Athanasios Loukas, Marta Martinkova, Marzena Osuch, Lampros Vasiliades, Birgitte von Christierson, Klaus Josef VormoorORCiDGND, Ismail Yuecel
DOI:https://doi.org/10.1016/j.jhydrol.2016.08.033
ISSN:0022-1694
ISSN:1879-2707
Title of parent work (English):Journal of hydrology
Publisher:Elsevier
Place of publishing:Amsterdam
Publication type:Article
Language:English
Year of first publication:2016
Publication year:2016
Release date:2020/03/22
Tag:Climate change; Europe; Flooding; Regional climate models; Statistical downscaling
Volume:541
Number of pages:14
First page:1273
Last Page:1286
Funding institution:Danish Council for Strategic Research as part of the project RiskChange; Hydraulics Research; Flemish Environment Agency; Helmoltz graduate research school GeoSim; Internal Grant Agency of the Faculty of Environmental Sciences; CULS Prague [00000869/2013]; Austrian Climate and Energy Fund as part of the Austrian Climate Research Programme; TUBITAK [110Y036]; EU FP6 Integrated Project ENSEMBLES [05539]
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
Peer review:Referiert
Institution name at the time of the publication:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften
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