Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information
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 condition...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-16633-1 |
| _version_ | 1818504952356536320 |
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| author | Eva Steirou Lars Gerlitz Xun Sun Heiko Apel Ankit Agarwal Sonja Totz Bruno Merz |
| author_facet | Eva Steirou Lars Gerlitz Xun Sun Heiko Apel Ankit Agarwal Sonja Totz Bruno Merz |
| author_sort | Eva Steirou |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T21:44:10Z |
| format | Article |
| id | doaj.art-f4e83e6ea8da495b8be805c7cb00d371 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-10T21:44:10Z |
| publishDate | 2022-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-f4e83e6ea8da495b8be805c7cb00d3712022-12-22T01:32:25ZengNature PortfolioScientific Reports2045-23222022-08-0112111010.1038/s41598-022-16633-1Towards seasonal forecasting of flood probabilities in Europe using climate and catchment informationEva Steirou0Lars Gerlitz1Xun Sun2Heiko Apel3Ankit Agarwal4Sonja Totz5Bruno Merz6Section Hydrology, GFZ German Research Center for GeosciencesSection Hydrology, GFZ German Research Center for GeosciencesKey Laboratory of Geographic Information Science (Ministry of Education), East China Normal UniversitySection Hydrology, GFZ German Research Center for GeosciencesSection Hydrology, GFZ German Research Center for GeosciencesDepartment of Civil and Environmental Engineering, MITSection Hydrology, GFZ German Research Center for GeosciencesAbstract 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.https://doi.org/10.1038/s41598-022-16633-1 |
| spellingShingle | Eva Steirou Lars Gerlitz Xun Sun Heiko Apel Ankit Agarwal Sonja Totz Bruno Merz Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information Scientific Reports |
| title | Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information |
| title_full | Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information |
| title_fullStr | Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information |
| title_full_unstemmed | Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information |
| title_short | Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information |
| title_sort | towards seasonal forecasting of flood probabilities in europe using climate and catchment information |
| url | https://doi.org/10.1038/s41598-022-16633-1 |
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