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Journal Article

Climate change impact on regional floods in the Carpathian region

Authors
/persons/resource/didovets

Didovets,  Iulii
Potsdam Institute for Climate Impact Research;

/persons/resource/Valentina.Krysanova

Krysanova,  Valentina
Potsdam Institute for Climate Impact Research;

Bürger,  G.
External Organizations;

Snizhko,  S.
External Organizations;

Balabukh,  V.
External Organizations;

Bronstert,  A.
External Organizations;

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8470oa.pdf
(Publisher version), 7MB

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Citation

Didovets, I., Krysanova, V., Bürger, G., Snizhko, S., Balabukh, V., Bronstert, A. (2019): Climate change impact on regional floods in the Carpathian region. - Journal of Hydrology: Regional Studies, 22, 100590.
https://doi.org/10.1016/j.ejrh.2019.01.002


Cite as: https://publications.pik-potsdam.de/pubman/item/item_23113
Abstract
Study region Tisza and Prut catchments, originating on the slopes of the Carpathian mountains. Study focus The study reported here investigates (i) climate change impacts on flood risk in the region, and (ii) uncertainty related to hydrological modelling, downscaling techniques and climate projections. The climate projections used in the study were derived from five GCMs, downscaled either dynamically with RCMs or with the statistical downscaling model XDS. The resulting climate change scenarios were applied to drive the eco-hydrological model SWIM, which was calibrated and validated for the catchments in advance using observed climate and hydrological data. The changes in the 30-year flood hazards and 98 and 95 percentiles of discharge were evaluated for the far future period (2071–2100) in comparison with the reference period (1981–2010). New hydrological insights for the region The majority of model outputs under RCP 4.5 show a small to strong increase of the 30-year flood level in the Tisza ranging from 4.5% to 62%, and moderate increase in the Prut ranging from 11% to 22%. The impact results under RCP 8.5 are more uncertain with changes in both directions due to high uncertainties in GCM-RCM climate projections, downscaling methods and the low density of available climate stations.