Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-5237-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-5237-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Uncertainties and their interaction in flood hazard assessment with climate change
Hadush Meresa
CORRESPONDING AUTHOR
Irish Climate Analysis and Research UnitS (ICARUS), Department of
Geography, Maynooth University, Maynooth, Ireland
Conor Murphy
Irish Climate Analysis and Research UnitS (ICARUS), Department of
Geography, Maynooth University, Maynooth, Ireland
Rowan Fealy
Irish Climate Analysis and Research UnitS (ICARUS), Department of
Geography, Maynooth University, Maynooth, Ireland
Saeed Golian
Irish Climate Analysis and Research UnitS (ICARUS), Department of
Geography, Maynooth University, Maynooth, Ireland
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Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hydrol. Earth Syst. Sci., 25, 4159–4183, https://doi.org/10.5194/hess-25-4159-2021, https://doi.org/10.5194/hess-25-4159-2021, 2021
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We benchmarked the skill of ensemble streamflow prediction (ESP) for a diverse sample of 46 Irish catchments. We found that ESP is skilful in the majority of catchments up to several months ahead. However, the level of skill was strongly dependent on lead time, initialisation month, and individual catchment location and storage properties. We also conditioned ESP with the winter North Atlantic Oscillation and show that improvements in forecast skill, reliability, and discrimination are possible.
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Weather and water extremes have devastating effects each year. One of the principal challenges for society is understanding how extremes are likely to evolve under the influence of changes in climate, land cover, and other human impacts. This paper provides a review of the methods and challenges associated with the detection, attribution, management, and projection of nonstationary weather and water extremes.
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Short summary
The assessment of future impacts of climate change is associated with a cascade of uncertainty linked to the modelling chain employed in assessing local-scale changes. Understanding and quantifying this cascade is essential for developing effective adaptation actions. We find that not only do the contributions of different sources of uncertainty vary by catchment, but that the dominant sources of uncertainty can be very different on a catchment-by-catchment basis.
The assessment of future impacts of climate change is associated with a cascade of uncertainty...