Multivariate return periods of sea storms for coastal erosion risk assessment
Multivariate return periods of sea storms for coastal erosion risk assessment
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DOI：
10.5194/nhess-12-2699-2012
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发表时间：
2012-01-01
影响因子：
4.6
通讯作者：
Stretch, D. D.
中科院分区：
文献类型：
--
作者：
Corbella, S.;Stretch, D. D.
海滩的侵蚀取决于各种风暴特征。理想情况下，与风暴相关的风险可以用代表侵蚀风险的单一多变量重现期来描述，即一个100年的多变量风暴重现期将导致100年的侵蚀重现期。不幸的是，特定的概率水平可能与风暴特征的多种组合有关。尽管这些组合具有相同的多变量概率，但可能会导致非常不同的侵蚀结果。本文在基于Copula的多变量重现期的背景下，利用南非东海岸德班的一个案例研究来探讨这一歧义问题。模拟被用于将历史事件的多变量重现期与估计的风暴引起的侵蚀量的重现期相关联。此外，还调查了最有可能的设计事件(萨尔瓦多等人，2011年)与海岸侵蚀的关系。研究发现，波高和持续时间的多变量重现期与侵蚀重现期的相关性最高。最有可能的设计事件被发现是目前形式的设计方法不充分。我们探讨了基于波浪事件的物理可实现性的条件的包含，以及使用多元线性回归将风暴参数与基于过程的模型计算的侵蚀相关联。建立风暴统计和侵蚀后果之间的联系可以解决多变量风暴重现期和相关侵蚀重现期之间的模糊问题。
The erosion of a beach depends on various storm characteristics. Ideally, the risk associated with a storm would be described by a single multivariate return period that is also representative of the erosion risk, i.e. a 100 yr multivariate storm return period would cause a 100 yr erosion return period. Unfortunately, a specific probability level may be associated with numerous combinations of storm characteristics. These combinations, despite having the same multivariate probability, may cause very different erosion outcomes. This paper explores this ambiguity problem in the context of copula based multivariate return periods and using a case study at Durban on the east coast of South Africa. Simulations were used to correlate multivariate return periods of historical events to return periods of estimated storm induced erosion volumes. In addition, the relationship of the most-likely design event (Salvadori et al., 2011) to coastal erosion was investigated. It was found that the multivariate return periods for wave height and duration had the highest correlation to erosion return periods. The most-likely design event was found to be an inadequate design method in its current form. We explore the inclusion of conditions based on the physical realizability of wave events and the use of multivariate linear regression to relate storm parameters to erosion computed from a process based model. Establishing a link between storm statistics and erosion consequences can resolve the ambiguity between multivariate storm return periods and associated erosion return periods.