Articles | Volume 26, issue 4
https://doi.org/10.5194/nhess-26-1727-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-1727-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Apr 2026
Research article |
| 15 Apr 2026
| 15 Apr 2026
Towards global sensitivity analysis of large-scale flood loss models
Francesca Pianosi
CORRESPONDING AUTHOR
School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol, United Kingdom
Cabot Institute, University of Bristol, Bristol, United Kingdom
Georgios Sarailidis
School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol, United Kingdom
JBA Risk Management Limited, Skipton, United Kingdom
Kirsty Styles
JBA Risk Management Limited, Skipton, United Kingdom
Philip Oldham
JBA Risk Management Limited, Skipton, United Kingdom
Stephen Hutchings
JBA Risk Management Limited, Skipton, United Kingdom
JBA Trust, Skipton, United Kingdom
Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom
Thorsten Wagener
Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
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Short summary
Mathematical modelling is essential to support flood risk management. As these models simulate complex interactions between climate, the natural and the built environment, they unavoidably embed a range of simplifying assumptions. In this paper, we propose a more rigorous approach to analyse the impact of uncertain assumptions on modelling results. This is important to improve model transparency and set priorities for improving models.
Mathematical modelling is essential to support flood risk management. As these models simulate...
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