Although the sequential tsunami scenario detection framework was validated in our previous work, several tasks remain to be resolved from a practical point of view. This study aims to evaluate the performance of the previous tsunami scenario detection framework using a diverse database consisting of complex fault rupture patterns with heterogeneous slip distributions. Specifically, we compare the effectiveness of scenario superposition to that of the previous most likely scenario detection method. Additionally, how the length of the observation time window influences the accuracy of both methods is analyzed. We utilize an existing database comprising 1771 tsunami scenarios targeting the city Westport (WA, U.S.), which includes synthetic wave height records and inundation distributions as the result of fault rupture in the Cascadia subduction zone. The heterogeneous patterns of slips used in the database increase the diversity of the scenarios and thus make it a proper database for evaluating the performance of scenario superposition. To assess the performance, we consider various observation time windows shorter than 15 minutes and divide the database into five testing and learning sets. The evaluation accuracy of the maximum offshore wave, inundation depth, and its distribution is analyzed to examine the advantages of the scenario superposition method over the previous method. We introduce the dynamic time warping (DTW) method as an additional benchmark and compare its results to that of the Bayesian scenario detection method.

翻译：尽管序贯海啸情景检测框架在我们先前的工作中已得到验证，但从实用角度出发，仍有若干问题有待解决。本研究旨在利用包含具有非均匀滑动分布的复杂断层破裂模式的多样化数据库，评估先前海啸情景检测框架的性能。具体而言，我们比较了情景叠加方法与先前最可能情景检测方法的有效性。此外，分析了观测时间窗口长度对两种方法准确性的影响。我们采用了一个包含1771个针对美国华盛顿州韦斯特波特市的海啸情景的现有数据库，该数据库包含由卡斯卡迪亚俯冲带断层破裂产生的合成波高记录和淹没分布。数据库中使用的非均匀滑动模式增加了情景的多样性，从而使其成为评估情景叠加方法性能的合适数据库。为评估性能，我们考虑了短于15分钟的各种观测时间窗口，并将数据库划分为五个测试集与学习集。通过分析最大离岸波高、淹没深度及其分布的评价准确性，检验了情景叠加方法相较于先前方法的优势。我们引入动态时间规整（DTW）方法作为附加基准，并将其结果与贝叶斯情景检测方法的结果进行了比较。