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

该项目的目的是检查过去中度和极端洪水事件的记录，以及与洪水成因相关的相关环境变量，并对这些记录进行探索性数据分析。这将避免立即依赖于现有方法中的假设，并提供对这些假设的独立检查。它还将允许建立一种统计方法，既适合于观测到的数据集的特性，也适合于估计需要从数据中提取的极端事件的相关特性。联合概率分析将是正在使用的主要统计方法之一。除了提供对洪水发生的有用见解外，这有可能导致对洪水进行更有效的统计估计。通过在所有分析中直接考虑洪水事件的季节性，将寻求对洪水问题的进一步见解。实际上，现有的数据集可以提供10-20年重现期的洪水的良好估计，但使用的统计模型可以用来推断50年、100年甚至1000年的重现期。对于这种外推，这种估计中固有的不确定性可能很大，项目的一个重要目标将是对这种不确定性提供有用的评估。CEH已经持有的每小时数据集将用于该项目

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