Willis, T, Wright, N and Sleigh, A orcid.org/0000-0001-9218-5660 (2019) Systematic analysis of uncertainty in 2D flood inundation models. Environmental Modelling & Software, 122. 104520. ISSN 1364-8152
Abstract
Assessing uncertainty is a critical part of understanding and developing flood inundation models for use in risk assessment. Typically, uncertainties are investigated by comparing the effects of an ensemble of key model inputs, such as friction values and hydrographic uncertainties, on model outputs. In this study, an approach is adopted that also consider the uncertainty associated with the computational models. Using the LISFLOOD-FP code, which contains multiple methods for solving floodplain flow, two test cases with different hydraulic characteristics are used in a systematic uncertainty analysis. An ensemble of inputs including cell size, hydrological uncertainty, and representation of buildings are assessed for impact on modelling results. Results show the numerical complexity is a significant source of uncertainty in complex flow regimes, but this reduces in typical fluvial flood events. The method of assessing the modelling output is also found to be important in determining the overall influence of parameters.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Crown Copyright © 2019 Published by Elsevier Ltd. All rights reserved. This is an author produced version of an article published in Environmental Modelling and Software. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Flood inundation modelling; Uncertainty analysis; Numerical modelling; Hydraulics |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > River Basin Processes & Management (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Dec 2019 13:35 |
Last Modified: | 26 Sep 2020 00:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.envsoft.2019.104520 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:154250 |