Estimating extreme water level probabilities: A comparison of the direct methods and recommendations for best practise
Estimating extreme water level probabilities: A comparison of the direct methods and recommendations for best practise
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DOI：
10.1016/j.coastaleng.2013.07.003
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发表时间：
2013-11-01
影响因子：
4.4
通讯作者：
Pattiaratchi, C.
中科院分区：
文献类型：
--
作者：
Arns, A.;Wahl, T.;Pattiaratchi, C.
在过去的五十年里，已经发展了几种估计极端静止水位的概率的方法。目前，不仅在跨国范围内，而且在国家范围内采用不同的方法，造成了不同程度的保护。应用不同的统计方法可以得到非常不同的回归水位估计，但即使使用相同的技术也会产生很大的差异，因为在模型建立的几个步骤中都有主观的参数选择。在本文中，我们比较了使用主要的直接方法(即块极大值方法和峰值超过阈值方法)估计的极端静止水位的概率，考虑到创建极值数据集的广泛策略和一系列不同的模型设置。我们主要使用德国海湾的潮汐测量仪记录，但也考虑了英国和澳大利亚各地的数据进行比较。重点是测试以下三个主要因素的影响，这些因素可能会影响极值统计的估计：(1)去除原始数据集的趋势；(2)从原始数据集建立极值样本；(3)原始数据集的记录长度。我们发现，使用不同的去趋势技术会使极值统计的结果产生偏差。因此，我们建议使用高水位的一年移动平均值(或每小时记录，如果有的话)来修正原始数据集的季节性和长期海平面变化。我们的结果强调，峰值超过阈值方法比块最大值方法产生更可靠和更稳定的极端静止水位概率估计(即使用短记录时得到与使用长记录时相同的结果)。在分析各种阈值选择方法时，我们发现使用99.7%的水位可以得到德州湾沿岸最稳定的回归水位估计。这一点也适用于所考虑的国际电台。最后，为了给沿海工程技术人员和操作人员提供指导，我们推荐了峰值过阈值的方法，并定义了建立模型的客观方法。如果这种做法在一个国家普遍适用，将有助于克服由于不同的方法和不同的模式设置而导致的保护水平不同的问题。(C)2013爱思唯尔B.V.保留所有权利。
Over the past five decades, several approaches for estimating probabilities of extreme still water levels have been developed. Currently, different methods are applied not only on transnational, but also on national scales, resulting in a heterogeneous level of protection. Applying different statistical methods can yield significantly different estimates of return water levels, but even the use of the same technique can produce large discrepancies, because there is subjective parameter choice at several steps in the model setup. In this paper, we compare probabilities of extreme still water levels estimated using the main direct methods (i.e. the block maxima method and the peaks over threshold method) considering a wide range of strategies to create extreme value dataset and a range of different model setups. We primarily use tide gauge records from the German Bight but also consider data from sites around the UK and Australia for comparison. The focus is on testing the influence of the following three main factors, which can affect the estimates of extreme value statistics: (1) detrending the original data sets; (2) building samples of extreme values from the original data sets; and (3) the record lengths of the original data sets. We find that using different detrending techniques biases the results from extreme value statistics. Hence, we recommend using a 1-year moving average of high waters (or hourly records if these are available) to correct the original data sets for seasonal and long-term sea level changes. Our results highlight that the peaks over threshold method yields more reliable and more stable (i.e. using short records leads to the same results as when using long records) estimates of probabilities of extreme still water levels than the block maxima method. In analysing a variety of threshold selection methods we find that using the 99.7th percentile water level leads to the most stable return water level estimates along the German Bight. This is also valid for the international stations considered. Finally, to provide guidance for coastal engineers and operators, we recommend the peaks over threshold method and define an objective approach for setting up the model. If this is applied routinely around a country, it will help overcome the problem of heterogeneous levels of protection resulting from different methods and varying model setups. (C) 2013 Elsevier B.V. All rights reserved.