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Using a Scenario‐Neutral Framework to Avoid Potential Maladaptation to Future Flood Risk

This study develops a coherent framework to detect those catchment types associated with a high risk of maladaptation to future flood risk. Using the “scenario‐neutral” approach to impact assessment the sensitivity of Irish catchments to fluvial flooding is examined in the context of national climat...

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Autores principales: Broderick, Ciaran, Murphy, Conor, Wilby, Robert L., Matthews, Tom, Prudhomme, Christel, Adamson, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6472323/
https://www.ncbi.nlm.nih.gov/pubmed/31007298
http://dx.doi.org/10.1029/2018WR023623
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author Broderick, Ciaran
Murphy, Conor
Wilby, Robert L.
Matthews, Tom
Prudhomme, Christel
Adamson, Mark
author_facet Broderick, Ciaran
Murphy, Conor
Wilby, Robert L.
Matthews, Tom
Prudhomme, Christel
Adamson, Mark
author_sort Broderick, Ciaran
collection PubMed
description This study develops a coherent framework to detect those catchment types associated with a high risk of maladaptation to future flood risk. Using the “scenario‐neutral” approach to impact assessment the sensitivity of Irish catchments to fluvial flooding is examined in the context of national climate change allowances. A predefined sensitivity domain is used to quantify flood responses to +2 °C mean annual temperature with incremental changes in the seasonality and mean of the annual precipitation cycle. The magnitude of the 20‐year flood is simulated at each increment using two rainfall‐runoff models (GR4J, NAM), then concatenated as response surfaces for 35 sample catchments. A typology of catchment sensitivity is developed using clustering and discriminant analysis of physical attributes. The same attributes are used to classify 215 ungauged/data‐sparse catchments. To address possible redundancies, the exposure of different catchment types to projected climate is established using an objectively selected subset of the Coupled Model Intercomparison Project Phase 5 ensemble. Hydrological model uncertainty is shown to significantly influence sensitivity and have a greater effect than ensemble bias. A national flood risk allowance of 20%, considering all 215 catchments is shown to afford protection against ~48% to 98% of the uncertainty in the Coupled Model Intercomparison Project Phase 5 subset (Representative Concentration Pathway 8.5; 2070–2099), irrespective of hydrological model and catchment type. However, results indicate that assuming a standard national or regional allowance could lead to local over/under adaptation. Herein, catchments with relatively less storage are sensitive to seasonal amplification in the annual cycle of precipitation and warrant special attention.
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spelling pubmed-64723232019-04-19 Using a Scenario‐Neutral Framework to Avoid Potential Maladaptation to Future Flood Risk Broderick, Ciaran Murphy, Conor Wilby, Robert L. Matthews, Tom Prudhomme, Christel Adamson, Mark Water Resour Res Research Articles This study develops a coherent framework to detect those catchment types associated with a high risk of maladaptation to future flood risk. Using the “scenario‐neutral” approach to impact assessment the sensitivity of Irish catchments to fluvial flooding is examined in the context of national climate change allowances. A predefined sensitivity domain is used to quantify flood responses to +2 °C mean annual temperature with incremental changes in the seasonality and mean of the annual precipitation cycle. The magnitude of the 20‐year flood is simulated at each increment using two rainfall‐runoff models (GR4J, NAM), then concatenated as response surfaces for 35 sample catchments. A typology of catchment sensitivity is developed using clustering and discriminant analysis of physical attributes. The same attributes are used to classify 215 ungauged/data‐sparse catchments. To address possible redundancies, the exposure of different catchment types to projected climate is established using an objectively selected subset of the Coupled Model Intercomparison Project Phase 5 ensemble. Hydrological model uncertainty is shown to significantly influence sensitivity and have a greater effect than ensemble bias. A national flood risk allowance of 20%, considering all 215 catchments is shown to afford protection against ~48% to 98% of the uncertainty in the Coupled Model Intercomparison Project Phase 5 subset (Representative Concentration Pathway 8.5; 2070–2099), irrespective of hydrological model and catchment type. However, results indicate that assuming a standard national or regional allowance could lead to local over/under adaptation. Herein, catchments with relatively less storage are sensitive to seasonal amplification in the annual cycle of precipitation and warrant special attention. John Wiley and Sons Inc. 2019-02-07 2019-02 /pmc/articles/PMC6472323/ /pubmed/31007298 http://dx.doi.org/10.1029/2018WR023623 Text en ©2019. The Authors. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Broderick, Ciaran
Murphy, Conor
Wilby, Robert L.
Matthews, Tom
Prudhomme, Christel
Adamson, Mark
Using a Scenario‐Neutral Framework to Avoid Potential Maladaptation to Future Flood Risk
title Using a Scenario‐Neutral Framework to Avoid Potential Maladaptation to Future Flood Risk
title_full Using a Scenario‐Neutral Framework to Avoid Potential Maladaptation to Future Flood Risk
title_fullStr Using a Scenario‐Neutral Framework to Avoid Potential Maladaptation to Future Flood Risk
title_full_unstemmed Using a Scenario‐Neutral Framework to Avoid Potential Maladaptation to Future Flood Risk
title_short Using a Scenario‐Neutral Framework to Avoid Potential Maladaptation to Future Flood Risk
title_sort using a scenario‐neutral framework to avoid potential maladaptation to future flood risk
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6472323/
https://www.ncbi.nlm.nih.gov/pubmed/31007298
http://dx.doi.org/10.1029/2018WR023623
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