A data-driven exploratory study of extreme events based on joint probability analysis

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.