A data-driven exploratory study of extreme events based on joint probability analysis
Lead Research Organisation:
Lancaster University
Department Name: Mathematics and Statistics
Abstract
The aim of this project is to examine records of past moderate and extreme flood events, and of associated environmental variables related to the causes of flooding, and to undertake an exploratory data analysis of these. This would avoid relying immediately on the assumptions built into existing methodology and provide an independent check on these. It would also allow the construction of a statistical methodology tailored both to the observed properties of the datasets and to the estimation of the relevant properties of extreme events that need to be extracted from the data. Joint probability analysis would be one of the main statistical approaches being used. As well as providing useful insight into the occurrence of flooding, this has the potential to lead to more statistically efficient estimation of floods. Further insights into flooding problems will be sought by directly considering the seasonality of flood events in all the analyses. The datasets available can realistically be expected to provide good estimates of floods with return periods of 10-20 years, but the statistical models used can be employed to extrapolate to return periods of 50, 100 or even 1000 years. For such extrapolation the uncertainties inherent in this estimation are likely to be large and an important aim of the project will be to provide a useful assessment of this uncertainty. Hourly datasets already held at CEH will be used for the project
Organisations
Publications
Eastoe E
(2012)
Modelling the distribution of the cluster maxima of exceedances of subasymptotic thresholds
in Biometrika
Eastoe E
(2010)
Statistical models for overdispersion in the frequency of peaks over threshold data for a flow series
in Water Resources Research
Grigg O
(2012)
Threshold models for river flow extremes
in Environmetrics
Description | We have found a more accurate method for estimating the likelihood of extreme events. |
Exploitation Route | A full systematic study applying the new method over the UK is required to assess its performance and importance. |
Sectors | Environment |
Description | At Lancaster we developed new methods for accounting for intra-year variation in the numbers of extreme events and for modelling the distribution of the cluster maximum. The impact to date has been at a theoretic level, though these are likely to change practice in the modelling and risk assessment of extreme meteorological and environmental levels. |
First Year Of Impact | 2012 |
Sector | Environment |
Impact Types | Societal |