Open AccessIntegrating a multivariate extreme value method within a system flood risk analysis model
Author(s) -
Wyncoll D.,
Gouldby B.
Publication year - 2015
Publication title -
journal of flood risk management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.049
H-Index - 36
ISSN - 1753-318X
DOI - 10.1111/jfr3.12069
Subject(s) - flood myth , multivariate statistics , flooding (psychology) , extreme value theory , probabilistic logic , representation (politics) , environmental science , risk analysis (engineering) , computer science , multivariate analysis , reliability (semiconductor) , hydrology (agriculture) , statistics , geography , mathematics , engineering , geotechnical engineering , artificial intelligence , machine learning , business , archaeology , psychology , power (physics) , physics , quantum mechanics , politics , political science , law , psychotherapist
Effective management of flooding requires models that are capable of quantifying flood risk. Quantification of flood risk involves both the quantification of probabilities of flooding and the associated consequences. Modern flood risk models account for the probabilities of extreme hydraulic loading events and also include a probabilistic representation of the performance of flood defence infrastructure and its associated reliability. The spatial and temporal variability of flood events makes probabilistic representation of the hydraulic loading conditions on the flood defences complex. In the system method used widely within E ngland and Wales, simplifying assumptions relating to the spatial dependence of flood events are made. Recent research has shown the benefits of using improved multivariate extreme value methods to define the hydraulic loading conditions for flood risk analysis models. This paper describes the development of an improved modelling system that enhances the systems‐based risk analysis model currently applied in practice, through the incorporation of a multivariate extreme value model. The improved system has been presented on a case study site in the N orth W est of E ngland.