Following the eruption of Mount Anak Krakatau, a considerable landslide occurred on the southwestern part of the volcano and, upon entering the sea, generated a large tsunami within the Sunda Strait, Indonesia, on December 22, 2018. This tsunami traveled ~ 5 km across the strait basin and inundated the shorelines of Sumatra and Java with a vertical runup reaching 13 m. Following the event, observed field data, GPS measurements of the inundation, and multibeam echo soundings of the bathymetry within the strait were collected and publicly provided. Using this dataset, numerical modeling of the tsunami was conducted using the two-layer (soil and water) TUNAMI-N2 model based on a combination of landslide sources and bathymetry data. The two-layer model was implemented to nest the grid system using the finest grid size of 20 m. To constrain the unknown landslide parameters, the differential evolution (DE) global optimization algorithm was applied, which resulted in a parameter set that minimized the deviation from the measured bathymetry after the event. The DE global optimization procedure was effective at determining the landslide parameters for the model with the minimum deviation from the measured seafloor. The lowest deviation from the measured bathymetry was obtained for the best-fitting parameters: a maximum landslide thickness of 301.2 m and a landslide time of 10.8 min. The landslide volume of 0.182 km3 estimated by the best-fitting parameters shows that the tsunami flow depth could have reached 3–10 m along the shore with a K value of 0.89, although the simulated flow depths were underestimated in comparison with the observation data. According to the waveforms, the general wave pattern was well reproduced at tide gauges during the event. A large number of objective function evaluations were necessary to locate the minimum with the DE procedure to fix the grid cell size to 20 m; this limited the accuracy of the obtained parameter values for the two-layer model. Moreover, considering the generalizations in the modeling of landslide movements, the impact landslide time and thickness must be carefully calculated to obtain a suitable accuracy.

中文翻译：

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使用观测数据对数值两层模型进行全局优化：以2018年Sun他海峡海啸为例

在Anak Krakatau火山喷发之后，火山西南部发生了相当大的滑坡，并在入海后于2018年12月22日在印度尼西亚的Sunda海峡内引发了一场海啸。该海啸横越了约5公里海峡盆地和苏门答腊岛和爪哇岛的海岸线被淹没，垂直延伸量达13 m。事件发生后，收集并公开提供了海峡内海域测得的实地数据，GPS测量值以及测深仪的多波束回波测深。使用该数据集，基于滑坡源和测深数据的组合，使用两层（土壤和水）TUNAMI-N2模型对海啸进行了数值建模。实施了两层模型以使用20 m的最佳网格尺寸嵌套网格系统。为了约束未知的滑坡参数，应用了差分演化（DE）全局优化算法，该算法产生了一个参数集，该参数集使事件发生后与测深的偏差最小。DE全局优化程序可有效确定模型的滑坡参数，且与被测海床的偏差最小。对于最合适的参数，与测得的测深曲线的偏差最小：最大滑坡厚度为301.2 m，滑坡时间为10.8 min。通过最佳拟合参数估算的滑坡量为0.182 km3，表明海啸沿岸的水深可能达到3-10 m，K值为0.89，尽管与观测数据相比，模拟的水深被低估了。根据波形，事件期间潮汐仪很好地再现了一般的波形。要使用DE程序确定最小值以将网格像元大小固定为20 m，必须进行大量的目标函数评估。这限制了所获得的两层模型参数值的准确性。此外，考虑到滑坡运动建模中的一般性，必须仔细计算冲击滑坡的时间和厚度，以获得合适的精度。