Probabilistic Near-Field Tsunami Source and Tsunami Run-up Distribution Inferred From Tsunami Run-up Records in Northern Chile

被引:3
|
作者
Lee, Jun-Whan [1 ]
Irish, Jennifer L. [1 ,2 ]
Weiss, Robert [2 ,3 ]
机构
[1] Virginia Tech, Dept Civil & Environm Engn, Blacksburg, VA 24061 USA
[2] Virginia Tech, Ctr Coastal Studies, Blacksburg, VA USA
[3] Virginia Tech, Dept Geosci, Blacksburg, VA USA
基金
美国国家科学基金会; 美国海洋和大气管理局;
关键词
near-field tsunami; run-up; inversion; 2014; IQUIQUE; SLIP DISTRIBUTION; HAZARD ASSESSMENT; GREAT EARTHQUAKE; INVERSION; GEOMETRY; DEPOSITS; IMPACT; PLATE; GPS;
D O I
10.1029/2021JC017289
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
Understanding a tsunami source and its impact is vital to assess a tsunami hazard. Thanks to the efforts of the tsunami survey teams, high-quality tsunami run-up data exist for contemporary events. Still, it has not been widely used to infer a tsunami source and its impact mainly due to the computational burden of the tsunami forward model. In this study, we propose a TRRF-INV (Tsunami Run-up Response Function-based INVersion) model that can provide probabilistic estimates of a near-field tsunami source and tsunami run-up distribution from a small number of run-up records. We tested the TRRF-INV model with synthetic tsunami scenarios in northern Chile and applied it to the 2014 Iquique, Chile, tsunami event as a case study. The results demonstrated that the TRRF-INV model can provide a reasonable tsunami source estimate to first order and estimate tsunami run-up distribution well. Moreover, the case-study results agree well with the United States Geological Survey report and the global Centroid Moment Tensor solution. We also analyzed the performance of the TRRF-INV model depending on the number and the uncertainty of run-up records. We believe that the TRRF-INV model has the potential for supporting accurate hazard assessment by (1) providing new insights from tsunami run-up records into the tsunami source and its impact, (2) using the TRRF-INV model as a tool to support existing tsunami inversion models, and (3) estimating a tsunami source and its impact for ancient events where no data other than estimated run-up from sediment deposit data exist.
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页数:17
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