Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain
Floods are the most common and widely distributed natural risk, causing over £1 billion of damage per year in the UK as a result of recent events. Climatic projections predict an increase in flood risk; it becomes urgent to assess climate change impact on extreme flows, and evaluate uncertainties ...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-02-01
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| Series: | Water |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2073-4441/9/2/103 |
| _version_ | 1811310733246332928 |
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| author | Lila Collet Lindsay Beevers Christel Prudhomme |
| author_facet | Lila Collet Lindsay Beevers Christel Prudhomme |
| author_sort | Lila Collet |
| collection | DOAJ |
| description | Floods are the most common and widely distributed natural risk, causing over £1 billion of damage per year in the UK as a result of recent events. Climatic projections predict an increase in flood risk; it becomes urgent to assess climate change impact on extreme flows, and evaluate uncertainties related to these projections. This paper aims to assess the changes in extreme runoff for the 1:100 year return period across Great Britain as a result of climate change using the Future Flows Hydrology database. The Generalised Extreme Value (GEV) and Generalised Pareto (GP) models are automatically fitted for 11‐member ensemble flow series available for the baseline and the 2080s. The analysis evaluates the uncertainty related to the Extreme Value (EV) and climate model parameters. Results suggest that GP and GEV give similar runoff estimates and uncertainties. From the baseline to the 2080s, increasing estimate and uncertainties is evident in east England. With the GEV the uncertainty attributed to the climate model parameters is greater than for the GP (around 60% and 40% of the total uncertainty, respectively). This shows that when fitting both EV models, the uncertainty related to their parameters has to be accounted for to assess extreme runoffs. |
| first_indexed | 2024-04-13T10:04:09Z |
| format | Article |
| id | doaj.art-577686b19ea54e0fbeadc81503e498d3 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-04-13T10:04:09Z |
| publishDate | 2017-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-577686b19ea54e0fbeadc81503e498d32022-12-22T02:51:08ZengMDPI AGWater2073-44412017-02-019210310.3390/w9020103w9020103Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great BritainLila Collet0Lindsay Beevers1Christel Prudhomme2Water Academy, School of Energy, Geoscience, Infrastructure and Society, Heriot‐Watt University, Edinburgh Campus, Edinburgh EH14 4AS, UKWater Academy, School of Energy, Geoscience, Infrastructure and Society, Heriot‐Watt University, Edinburgh Campus, Edinburgh EH14 4AS, UKCentre for Ecology and Hydrology, MacLean Bldg, Benson Ln, Crowmarsh Gifford, Wallingford OX10 8BB, UKFloods are the most common and widely distributed natural risk, causing over £1 billion of damage per year in the UK as a result of recent events. Climatic projections predict an increase in flood risk; it becomes urgent to assess climate change impact on extreme flows, and evaluate uncertainties related to these projections. This paper aims to assess the changes in extreme runoff for the 1:100 year return period across Great Britain as a result of climate change using the Future Flows Hydrology database. The Generalised Extreme Value (GEV) and Generalised Pareto (GP) models are automatically fitted for 11‐member ensemble flow series available for the baseline and the 2080s. The analysis evaluates the uncertainty related to the Extreme Value (EV) and climate model parameters. Results suggest that GP and GEV give similar runoff estimates and uncertainties. From the baseline to the 2080s, increasing estimate and uncertainties is evident in east England. With the GEV the uncertainty attributed to the climate model parameters is greater than for the GP (around 60% and 40% of the total uncertainty, respectively). This shows that when fitting both EV models, the uncertainty related to their parameters has to be accounted for to assess extreme runoffs.http://www.mdpi.com/2073-4441/9/2/103future flow hydrology generalised extreme value generalised Pareto cascaded uncertainty perturbed physics model ensemble |
| spellingShingle | Lila Collet Lindsay Beevers Christel Prudhomme Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain Water future flow hydrology generalised extreme value generalised Pareto cascaded uncertainty perturbed physics model ensemble |
| title | Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain |
| title_full | Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain |
| title_fullStr | Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain |
| title_full_unstemmed | Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain |
| title_short | Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain |
| title_sort | assessing the impact of climate change and extreme value uncertainty to extreme flows across great britain |
| topic | future flow hydrology generalised extreme value generalised Pareto cascaded uncertainty perturbed physics model ensemble |
| url | http://www.mdpi.com/2073-4441/9/2/103 |
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