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

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 G...

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Autores principales: Steirou, Eva, Gerlitz, Lars, Sun, Xun, Apel, Heiko, Agarwal, Ankit, Totz, Sonja, Merz, Bruno
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357046/
https://www.ncbi.nlm.nih.gov/pubmed/35933510
http://dx.doi.org/10.1038/s41598-022-16633-1
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author Steirou, Eva
Gerlitz, Lars
Sun, Xun
Apel, Heiko
Agarwal, Ankit
Totz, Sonja
Merz, Bruno
author_facet Steirou, Eva
Gerlitz, Lars
Sun, Xun
Apel, Heiko
Agarwal, Ankit
Totz, Sonja
Merz, Bruno
author_sort Steirou, Eva
collection PubMed
description 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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spelling pubmed-93570462022-08-08 Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information Steirou, Eva Gerlitz, Lars Sun, Xun Apel, Heiko Agarwal, Ankit Totz, Sonja Merz, Bruno Sci Rep Article 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. Nature Publishing Group UK 2022-08-06 /pmc/articles/PMC9357046/ /pubmed/35933510 http://dx.doi.org/10.1038/s41598-022-16633-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Steirou, Eva
Gerlitz, Lars
Sun, Xun
Apel, Heiko
Agarwal, Ankit
Totz, Sonja
Merz, Bruno
Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information
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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357046/
https://www.ncbi.nlm.nih.gov/pubmed/35933510
http://dx.doi.org/10.1038/s41598-022-16633-1
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