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Modeling lithospheric rheology from modern measurements of Bonneville shoreline deformation.

机译:从现代Bonneville海岸线变形的测量中模拟岩石圈流变学。

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摘要

Here I develop a cross-correlation approach to estimating heights of shoreline features, and apply the new method to paleo-shorelines of Pleistocene Lake Bonneville. I calculaTe 1st-derivative (slope) and 2nd-derivative (curvature) profiles from Digital Elevation Model (DEM) or Global Positioning SysTem Real-Time Kinematic (GPS-RTK) measurements of elevation. I then cross-correla Te pairs of profiles that have been shifT ed by various "lags," or shifts in elevation. The correlation coefficient (a normalized dot-product measure of similarity) is calcula Ted as a function of lag within small (~40 m) windows cenTered at various elevations. The elevation and lag with the greaTest correlation coefficient indicaTes the shoreline elevation at the reference profile and the change in shoreline height for the profile pair. I evalua Te several different algorithms for deriving slope and curvature by examining closure of elevation lags across profile triples.;I then model isostatic response to Lake Bonneville loading and unloading. I first model lakeshore uplift response to lake load removal assuming an elastic layer over an inviscid half-space. I obtain a best-fit comparison of predic Ted to observed shoreline heights for the Bonneville level with an elastic layer thickness, Te, of 25±2 km (at 95% confidence) when using only previously published shoreline elevation estimaTes. The best-fit for the Bonneville level when using these estimaTes plus 44 new estima Tes suggests a Te of 26±2 km. The best-fit model for the Provo level suggests Te of 17±3 km. For the Gilbert level, the response is insensitive to the assumed Te. I next model isostatic response to Bonneville loading and unloading assuming an elastic layer over a viscoelastic halfspace. This approach assumes constant parameTers for the entire loading history, and yields a best-fit model with Te =70±5 km and viscosity ŋ=~2x1018 Pa s with 95% confidence ranging from ~1x1018 to ~5x10 19 Pa s when only the previously published data are used. With the newer data added, the best-fit model has Te =58±2 km and ŋ ranging from ~1x1018 to ~1x1019 Pa s with 95% confidence. The 12-15 m weighTed root-mean-square misfit to the best-fitting model is dominaT ed by Tectonic signals rela Ted to Basin-and-Range Tectonics particularly seismic offsets of the Wasatch fault, and closely mimics the geological timescale patTe m of basin-subsidence and range-uplift.
机译:在这里,我开发了一种用于估计海岸线特征高度的互相关方法,并将新方法应用于更新世博纳维尔湖的古海岸线。我从数字高程模型(DEM)或全球定位系统实时运动学(GPS-RTK)测量高程中计算出一阶导数(斜率)和二阶导数(曲率)轮廓。然后,我将因各种“滞后”或高程偏移而被校正的轮廓对相互关联。相关系数(相似性的标准化点积度量)是在不同高度以小(〜40 m)窗口内滞后的函数Ted计算的。高程和滞后以及greaTest相关系数指示参考轮廓处的海岸线高程以及轮廓对的海岸线高度变化。通过检查跨剖面三重面的高程滞后的闭合性,我评估了几种不同的算法来得出坡度和曲率。然后,我对邦纳维尔湖的装卸等静响应进行了建模。我首先模拟了在不粘稠的半空间上有一个弹性层的情况下,对湖面卸荷的湖岸隆升响应。当仅使用以前发布的海岸线高程估算值时,我得到了泰德断言与Bonneville水平面观测到的海岸线高度的最佳拟合,弹性层厚度Te为25±2 km(置信度为95%)。使用这些估算值加上44个新估算值时,最适合邦纳维尔水准的参数表明Te值为26±2 km。 Provo级的最佳拟合模型建议Te为17±3 km。对于吉尔伯特水平,响应对假设的Te不敏感。接下来,我假设粘弹性半空间上有一个弹性层,从而对Bonneville装卸的等静压响应进行建模。该方法在整个加载历史中均假设参数恒定,并生成最佳拟合模型,其Te = 70±5 km,粘度ŋ =〜2x1018 Pa s,95%置信度从〜1x1018到〜5x10 19 Pa s。使用以前发布的数据。添加了更新的数据后,最佳拟合模型的Te = 58±2 km,ŋ范围为〜1x1018至〜1x1019 Pa s,置信度为95%。最佳拟合模型的12-15 m权重均方根失配主要由与盆地和范围构造有关的构造信号(特别是Wasatch断层的地震偏移)所主导,并且紧密地模仿了盆地下沉和范围隆升。

著录项

  • 作者

    Beard, Eric P.;

  • 作者单位

    Utah State University.;

  • 授予单位 Utah State University.;
  • 学科 Geology.;Geomorphology.;Geophysics.
  • 学位 M.S.
  • 年度 2012
  • 页码 94 p.
  • 总页数 94
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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