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Technical note: comparison of methods for threshold selection for extreme sea levels
https://orcid.org/0000-0002-8809-9118
https://orcid.org/0000-0003-0415-5897
Extreme value analysis is an important tool for studying coastal flood risk, but requires the estimation of a threshold to define an ‘extreme’, which is traditionally undertaken visually. Such subjective judgement is not accurately reproducible, so recently a number of quantitative approaches have been proposed. This paper therefore reviews existing methods, illustrated with coastal tide‐gauge data and the Generalized Pareto Distribution, and proposes a new automated method that mimics the enduringly popular visual inspection method. In total, five different types of statistical threshold selection and their variants are evaluated by comparison to manually derived thresholds, demonstrating that the new method is a useful, complementary tool.
Technical note: comparison of methods for threshold selection for extreme sea levels
https://orcid.org/0000-0002-8809-9118
https://orcid.org/0000-0003-0415-5897
Extreme value analysis is an important tool for studying coastal flood risk, but requires the estimation of a threshold to define an ‘extreme’, which is traditionally undertaken visually. Such subjective judgement is not accurately reproducible, so recently a number of quantitative approaches have been proposed. This paper therefore reviews existing methods, illustrated with coastal tide‐gauge data and the Generalized Pareto Distribution, and proposes a new automated method that mimics the enduringly popular visual inspection method. In total, five different types of statistical threshold selection and their variants are evaluated by comparison to manually derived thresholds, demonstrating that the new method is a useful, complementary tool.
Technical note: comparison of methods for threshold selection for extreme sea levels
https://orcid.org/0000-0002-8809-9118
https://orcid.org/0000-0003-0415-5897
Extreme value analysis is an important tool for studying coastal flood risk, but requires the estimation of a threshold to define an ‘extreme’, which is traditionally undertaken visually. Such subjective judgement is not accurately reproducible, so recently a number of quantitative approaches have been proposed. This paper therefore reviews existing methods, illustrated with coastal tide‐gauge data and the Generalized Pareto Distribution, and proposes a new automated method that mimics the enduringly popular visual inspection method. In total, five different types of statistical threshold selection and their variants are evaluated by comparison to manually derived thresholds, demonstrating that the new method is a useful, complementary tool.
Technical note: comparison of methods for threshold selection for extreme sea levels
J Flood Risk Management
Caballero‐Megido, C. (author) / Hillier, J. (author) / Wyncoll, D. (author) / Bosher, L. (author) / Gouldby, B. (author)
Journal of Flood Risk Management ; 11 ; 127-140
2018-06-01
Article (Journal)
Electronic Resource
English
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