There is a propensity for an extreme value analysis to be conducted as a consequence of a large flooding event. This timing of the analysis introduces bias and poor coverage probabilities into the associated risk assessments and leads subsequently to inefficient flood protection schemes. We explore these problems through studying stochastic stopping criteria and propose new likelihood‐based inferences that mitigate against these difficulties. Our methods are illustrated through the analysis of the river Lune, following its experiencing the UK's largest ever measured flow event in 2015. We show that without accounting for this stopping feature there would be substantial overdesign in response to the event.

中文翻译：

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根据基于阈值的停止规则推断极值

由于大洪水事件的结果，极有可能进行极值分析。分析的时机将偏差和覆盖率差引入相关的风险评估中，并随后导致低效的防洪计划。我们通过研究随机停止准则来探索这些问题，并提出新的基于似然性的推理来减轻这些困难。在对Lune河进行分析之后，我们的方法得到了说明，该河在2015年经历了英国有史以来最大的流量事件。我们表明，如果不考虑这一停车特征，将对该事件做出大量的过度设计。