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  Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information

Steirou, E.-S., Gerlitz, L., Sun, X., Apel, H., Agarwal, A., Totz, S., Merz, B. (2022): Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information. - Scientific Reports, 12, 13514.
https://doi.org/10.1038/s41598-022-16633-1

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 Creators:
Steirou, Eva-Styliani1, Author              
Gerlitz, Lars1, Author              
Sun, Xun2, Author
Apel, H.1, Author              
Agarwal, Ankit1, Author              
Totz, Sonja2, Author
Merz, B.1, Author              
Affiliations:
14.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146048              
2External Organizations, ou_persistent22              

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Free keywords: DEAL Springer Nature
 Abstract: We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead.

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 Dates: 20222022
 Publication Status: Finally published
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 Identifiers: DOI: 10.1038/s41598-022-16633-1
OATYPE: Hybrid - DEAL Springer Nature
GFZPOF: p4 T5 Future Landscapes
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Title: Scientific Reports
Source Genre: Journal, SCI, Scopus, OA
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Pages: - Volume / Issue: 12 Sequence Number: 13514 Start / End Page: - Identifier: CoNE: https://gfzpublic.gfz-potsdam.de/cone/journals/resource/journals2_395
Publisher: Springer Nature