Staged uncertainty and sensitivity analysis within flood risk analysis
Ben P. Gouldby, Greer B. Kingston
Abstract
Ben P. Gouldby, Greer B. Kingston
Abstract
Modelling flood risk is complex and associated with many sources of uncertainty. Models that are unable to capture the full physical processes that they are intended to represent are widely used and some physical processes, like breach formation, for example, are poorly understood. Furthermore, statistical modelling of extreme events is often based on relatively short periods of observed data and knowledge of basic parameters within the flood system, such as defence crest level or floodplain property, is subject to inaccuracies. Uncertainty analysis is intrinsically linked to flood risk analysis and it is increasingly becoming acknowledged as an important component to explicitly include within the decision making process. Whilst methods for uncertainty analysis have been available for many years, these typically become computationally intensive and impractical when applied to flood system risk analysis.
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Modelling flood risk is complex and associated with many sources of uncertainty. Models that are unable to capture the full physical processes that they are intended to represent are widely used and some physical processes, like breach formation, for example, are poorly understood. Furthermore, statistical modelling of extreme events is often based on relatively short periods of observed data and knowledge of basic parameters within the flood system, such as defence crest level or floodplain property, is subject to inaccuracies. Uncertainty analysis is intrinsically linked to flood risk analysis and it is increasingly becoming acknowledged as an important component to explicitly include within the decision making process. Whilst methods for uncertainty analysis have been available for many years, these typically become computationally intensive and impractical when applied to flood system risk analysis.
Key concepts: Sensitivity (control systems), Flood myth, Uncertainty analysis, Risk analysis (engineering), Environmental science, Geography, Engineering, Statistics