Data_Sheet_1_Estimation of Return Levels for Extreme Skew Surge Coastal Flooding Events in the Delaware and Chesapeake Bays for 1980–2019.pdf

Extreme storm surges can overwhelm many coastal flooding protection measures in place and cause severe damages to private communities, public infrastructure, and natural ecosystems. In the US Mid-Atlantic, a highly developed and commercially active region, coastal flooding is one of the most significant natural hazards and a year-round threat from both tropical and extra-tropical cyclones. Mean sea levels and high-tide flood frequency has increased significantly in recent years, and major storms are projected to increase into the foreseeable future. We estimate extreme surges using hourly water level data and harmonic analysis for 1980–2019 at 12 NOAA tide gauges in and around the Delaware and Chesapeake Bays. Return levels (RLs) are computed for 1.1, 3, 5, 10, 25, 50, and 100-year return periods using stationary extreme value analysis on detrended skew surges. Two traditional approaches are investigated, Block Maxima fit to General Extreme Value distribution and Points-Over-Threshold fit to Generalized Pareto distribution, although with two important enhancements. First, the GEV r-largest order statistics distribution is used; a modified version of the GEV distribution that allows for multiple maximum values per year. Second, a systematic procedure is used to select the optimum value for r (for the BM/GEVr approach) and the threshold (for the POT/GP approach) at each tide gauge separately. RLs have similar magnitudes and spatial patterns from both methods, with BM/GEVr resulting in generally larger 100-year and smaller 1.1-year RLs. Maximum values are found at the Lewes (Delaware Bay) and Sewells Point (Chesapeake Bay) tide gauges, both located in the southwest region of their respective bays. Minimum values are found toward the central bay regions. In the Delaware Bay, the POT/GP approach is consistent and results in narrower uncertainty bands whereas the results are mixed for the Chesapeake. Results from this study aim to increase reliability of projections of extreme water levels due to extreme storms and ultimately help in long-term planning of mitigation and implementation of adaptation measures.

极端风暴潮可能超越许多现有的沿海防洪措施，并对私人社区、公共基础设施和自然生态系统造成严重损害。在美国中大西洋地区，这一高度发达且商业活动频繁的区域，沿海洪水是最大的自然灾害之一，同时也是热带和副热带气旋全年存在的威胁。近年来，平均海平面和高潮洪水频率显著增加，预计未来可预见的时期内主要风暴还将增加。我们利用1980年至2019年在特拉华湾和切萨皮克湾周边12个美国海洋和大气管理局（NOAA）潮汐站的每小时水位数据和调和分析，对极端潮汐进行了估算。通过去趋势偏斜潮汐的平稳极值分析，计算了1.1年、3年、5年、10年、25年、50年和100年一遇的回报水平（RLs）。研究了两种传统方法，即最大值法拟合广义极值分布和超越阈值法拟合广义帕累托分布，尽管进行了两项重要改进。首先，采用GEV r最大顺序统计量分布；这是GEV分布的一种修改版本，允许每年有多个最大值。其次，采用系统程序分别在每个潮汐站选择r（对于BM/GEVr方法）和阈值（对于POT/GP方法）的最优值。两种方法的RLs在数值和空间模式上相似，其中BM/GEVr方法得到的100年一遇RLs普遍较大，而1.1年一遇RLs较小。最大值出现在位于各自海湾西南区域的劳斯（特拉华湾）和塞维尔点（切萨皮克湾）潮汐站。最小值出现在中部海湾区域。在特拉华湾，POT/GP方法结果一致，导致不确定性带较窄，而切萨皮克湾的结果则混合。本研究的结果旨在提高极端风暴引起的极端水位预测的可靠性，最终有助于长期规划和实施缓解及适应措施。