Pupić Vurilj Mia, Antolínez José A Á, Muis Sanne, Morales Napoles Oswaldo
Department of Hydraulic Engineering, Delft University of Technology, Delft, Netherlands.
Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Nat Hazards (Dordr). 2025;121(12):14147-14175. doi: 10.1007/s11069-025-07351-8. Epub 2025 May 29.
Due to changing climates and rising sea levels, low-lying coastal regions, such as the Netherlands, face increased risks of flooding driven by extreme sea levels. Thus, understanding extreme sea level events and their underlying dynamics is crucial for effective coastal management. This study developed and applied a novel classification framework to investigate historical storm surge events along the Dutch coast and improve the understanding of regional storm surge dynamics. Using 16 sea level records, storm surges were identified with the Peak Over Threshold (POT) method, using the 70th (POT70) and 99th (POT99) percentiles as thresholds. POT70 captured a more comprehensive storm surge activity, including multiple peaks and successive surges that are critical for coastal management. In contrast, POT99 captured surge peaks but missed significant pre- and post-storm surge activities. The POT70-derived surges were classified into 56 event types using clustering methods based on surge values across the whole event time series, and event duration. Event types were then characterised by temporal patterns, peak magnitude, duration, probability of occurrence, yearly frequency, and cumulative surge intensity. Key findings revealed frequent two-peak storm surges and significant variations in storm surge intensity along the coast, with stronger events occurring in northern regions. The results highlight the complexity of storm surge patterns, indicating that while simplified hydrograph models are useful, they may not always capture the full range of surge pattern variations. This novel classification framework offers a more detailed approach to evaluating surge patterns and can be applied to other coastal regions as well.
The online version contains supplementary material available at 10.1007/s11069-025-07351-8.
由于气候变化和海平面上升,像荷兰这样的低海拔沿海地区面临着由极端海平面引发的洪水风险增加的问题。因此,了解极端海平面事件及其潜在动态对于有效的海岸管理至关重要。本研究开发并应用了一种新颖的分类框架,以调查荷兰海岸沿线的历史风暴潮事件,并增进对区域风暴潮动态的理解。利用16个海平面记录,采用阈值超量峰值(POT)方法识别风暴潮,分别使用第70百分位数(POT70)和第99百分位数(POT99)作为阈值。POT方法70捕捉到了更全面的风暴潮活动,包括对海岸管理至关重要的多个峰值和连续涌浪。相比之下,POT99捕捉到了涌浪峰值,但遗漏了风暴前后的重要涌浪活动。基于整个事件时间序列的涌浪值和事件持续时间,使用聚类方法将POT70得出的涌浪分为56种事件类型。然后根据时间模式、峰值大小、持续时间、发生概率、年频率和累积涌浪强度对事件类型进行了特征描述。主要发现揭示了频繁出现的双峰风暴潮以及沿海地区风暴潮强度的显著变化,北部地区发生的事件更强。结果突出了风暴潮模式的复杂性,表明虽然简化的水位图模型很有用,但它们可能并不总是能捕捉到涌浪模式变化的全部范围。这种新颖的分类框架为评估涌浪模式提供了一种更详细的方法,也可应用于其他沿海地区。
在线版本包含可在10.1007/s11069-025-07351-8获取的补充材料。