Flow speed estimated by inverse modeling of sandy sediment deposited by the 29 September 2009 tsunami near Satitoa, east Upolu, Samoa
Flow speed estimated by inverse modeling of sandy sediment deposited by the 29 September 2009 tsunami near Satitoa, east Upolu, Samoa
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通过 2009 年 9 月 29 日海啸在萨摩亚乌波卢岛东部萨蒂托亚附近沉积的沙质沉积物的反演模型估算的流速
DOI：
10.1016/j.earscirev.2011.03.009
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发表时间：
2011
影响因子：
12.1
通讯作者：
J. Goff
中科院分区：
文献类型：
--
作者：
B. Jaffe;M. Buckley;B. Richmond;L. Strotz;S. Etienne;K. Clark;S. Watt;G. Gelfenbaum;J. Goff
对 2009 年 9 月 29 日萨摩亚乌波卢岛东海岸海啸产生的沙质沉积物进行了调查，记录其特征，并应用逆沉积物输运模型来估计海啸流速。内陆约 25 至 250 米处形成厚度 6 至 15 厘米的沙质沉积物。沉积物中的沉积层由垂直颗粒尺寸变化和接触定义，被解释为是在两次波浪的陆上上升过程中形成的。 3 个地点（内陆 100、170 和 240 m）的矿床包含两层，主要是正常分级（约 80%），但在其底部包含大量部分（约 15%）和反分级部分（约 5%）。正常分级层段总厚度的约 75% 表现出沉积物在其顶部脱离悬浮状态的特征。这种类型的分级，这里称为悬浮分级，首先在浊流沉积物中被认识到，其特征是整个分布在一层中向上移动，高沉降速度，较粗的材料首先沉积，低沉降速度的较细材料最后沉积。 Jaffe 和 Gelfenbaum (2007) 逆沉积物输运模型应用于表现出悬浮液分级的层内区间，以估计海啸流速，并能够再现所观察到的悬浮液分级的总体趋势。建模中的一个关键未知输入是底部粗糙度。对于底部粗糙度参数化，使用 0.03 的曼宁 n（相当于观察到的 2-3 m 水流深度的 z0~ 0.006 m），计算出 3 个位置 2 层的流速分别为 3.8、3.6 和 3.7 m/s（底层/较早的波）和 4.4、4.4 和 4.1 m/s（顶部）层/晚波）分别位于内陆 100、170 和 240 m。这些估计值与巨石输送计算得出的 ~ 3–8 m/s 海啸流速一致，并且当使用最大测量的水流深度时，弗劳德数约为 0.7–1.0。因为反演模型假设沉积物是由悬浮液中落下的沉积物形成的，所以必须注意仅对表现出悬浮液分级的沉积物区间进行建模。包括由沉积物或悬浮物运输汇聚沉积的间隔会导致更高的、有时不切实际的海啸流速估计。
Sandy deposits from the 29 September 2009 tsunami on the east coast of Upolu, Samoa were investigated to document their characteristics and used to apply an inverse sediment transport model to estimate tsunami flow speed. Sandy deposits 6 to 15 cm thick formed from ~ 25 to ~ 250 m inland. Sedimentary layers in the deposits, that are defined by vertical grain size variation and contacts, are interpreted to have formed during onshore runup of two waves. Deposits at 3 locations (100, 170, and 240 m inland) contained two layers that are predominately normally graded (~ 80%), but contained massive sections (~ 15%) and inversely graded sections (~ 5%) at their bases. About 75% of the total thickness of normally graded intervals exhibits a signature of sediment falling out of suspension at their top. This type of grading, termed suspension grading here, was first recognized in turbidity current deposits and is characterized by the entire distribution shifting finer upwards in a layer as high-settling velocity, coarser material deposits first and low-settling velocity finer material deposits last. The Jaffe and Gelfenbaum (2007) inverse sediment transport model was applied to intervals within layers that exhibited suspension grading to estimate tsunami flow speed and was able to reproduce the general trends of the observed suspension grading. A key unknown input in the modeling is the bottom roughness. For a bottom roughness parameterization using a Manning's n of 0.03 (equivalent to a z0~ 0.006 m for the observed flow depths of 2–3 m) flow speeds calculated for the 2 layers at the 3 locations were 3.8, 3.6, and 3.7 m/s (bottom layer/earlier wave) and 4.4, 4.4, and 4.1 m/s (top layer/later wave) at 100, 170, and 240 m inland, respectively. These estimates are consistent with the ~ 3–8 m/s tsunami flow speed from boulder transport calculations and result in Froude numbers of ~ 0.7–1.0 when maximum measured flow depths are used. Because the inverse model assumes the deposit was formed by sediment falling out of suspension care must be taken to model only intervals of the deposit exhibiting suspension grading. Including intervals deposited by either bedload or suspended load transport convergences result in higher, and sometimes unrealistic, tsunami flow speed estimates.
TsuSedMod 反演模型应用于 2004 年苏门答腊岛和 2006 年爪哇海啸的沉积物以及对估计古海啸流动参数的影响
影响因子：
2.8
作者：
Spiske;Bahlburg;Roskosch;Amijaya
通讯作者：
Amijaya