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dc.contributor.supervisorGriffiths, Jim
dc.contributor.authorWhitworth, Michael Robert Zordan
dc.contributor.otherSchool of Geography, Earth and Environmental Sciencesen_US
dc.date.accessioned2017-04-05T09:04:37Z
dc.date.available2017-04-05T09:04:37Z
dc.date.issued2015
dc.identifier352159en_US
dc.identifier.urihttp://hdl.handle.net/10026.1/8803
dc.descriptionFull version unavailable due to 3rd party copyright restrictions.
dc.description.abstract

Recent events such as the New Orleans floods and the Japanese tsunami of 2011 have highlighted the uncertainty in the quantification of the magnitude of natural hazards. The research undertaken here has focussed on the uncertainty in evaluating storm surge magnitudes based on a range of statistical techniques including the Generalised Extreme Value distribution, Joint Probability and Monte Carlo simulations. To support the evaluation of storm surge frequency magnitude relationships a unique hard copy observed sea level data set, recording hourly observations, was acquired and digitised for Devonport, Plymouth, creating a 40 year data set. In conjunction with Devonport data, Newlyn (1915-2012) tide gauge records were analysed, creating a data set of 2 million data points. The different statistical techniques analysed led to an uncertainty range of 0.4 m for a 1 in 250 year storm surge event, and 0.7 m for a 1 in 1000 storm surge event. This compares to a 0.5 m uncertainty range between the low and high prediction for sea level rise by 2100. The Geographical Information system modelling of the uncertainty indicated that for a 1 in 1000 year event the level uncertainty (0.7 m) led to an increase of 100% of buildings and 50% of total land affect. Within the study area of south-west England there are several critical structures including a nuclear licensed site. Incorporating the uncertainty in storm surge and wave height predictions indicated that the site would be potentially affected today with the combination of a 1 in 1000 year storm surge event coincident with a 1 in 1000 wave. In addition to the evaluation of frequency magnitude relations this study has identified several trends in the data set. Over the data period sea level rise is modelled as an exponential growth (0.0001mm/yr2), indicating the modelled sea level rise of 1.9 mm/yr and 2.2 mm/yr for Newlyn and Devonport, will potentially increase over the next century by a minimum of 0.2 m by 2100.The increase in storm frequency identified as part of this analysis has been equated to the rise in sea level, rather than an increase in the severity of storms, with decadal variations in the observed frequency, potentially linked to the North Atlantic Oscillation. The identification as part of this study of a significant uncertainty in the evaluation of storm surge frequency magnitude relationships has global significance in the evaluation of natural hazards. Guidance on the evaluation of external hazards currently does not adequately consider the effect of uncertainty; an uncertainty of 0.7 m identified within this study could potentially affect in the region of 500 million people worldwide living close to the coast.

en_US
dc.language.isoenen_US
dc.publisherPlymouth Universityen_US
dc.subjectExtreme Value Analysisen_US
dc.subjectGeographical Information Systemen_US
dc.subjectHazarden_US
dc.subjectRisken_US
dc.subjectSea-Level Riseen_US
dc.subjectSouth-West Englanden_US
dc.subjectStorm Surgeen_US
dc.subjectTide Gaugeen_US
dc.subject.classificationPhDen_US
dc.titleUTILISING PROBABILISTIC TECHNIQUES IN THE ASSESSMENT OF EXTREME COASTAL FLOODING FREQUENCY- MAGNITUDE RELATIONSHIPS USING A CASE STUDY FROM SOUTH-WEST ENGLANDen_US
dc.typeThesis
plymouth.versionEdited versionen_US
dc.identifier.doihttp://dx.doi.org/10.24382/4846
dc.identifier.doihttp://dx.doi.org/10.24382/4846


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