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Application of a roughness-length representation to parameterize energy-loss in 3D numerical simulations of large rivers

机译:粗糙度长度表示法在大型河流的3D数值模拟中对能量损失进行参数化的应用

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摘要

Recent technological advances in remote sensing have enabled investigation of the morphodynamics and hydrodynamics of large rivers. However, measuring topography and flow in these very large rivers is time consuming, and so often constrains the spatial resolution and reach-length scales that can be monitored. Similar constraints exist for Computational Fluid Dynamics (CFD) requiring maximization of mesh- or grid-cell dimensions and implying a reduction in the representation of bedform-roughness elements that are the order of a cell’s dimensions or less, even if they are represented in available topographic data. These ‘subgrid’ elements require parameterizing, and here we aim to apply and consider the impact of roughness-length treatments that include the effect of bed roughness due to ‘unmeasured’ topography. CFD predictions were found to be sensitive to roughness-length specification. Upscaling roughness length was not found to be a particularly effective means of optimizing the agreement between model predictions and field data, because the effects of large bedforms were not well parameterized in roughness-length treatments. Changes in roughness length were shown to have a major impact upon flow routing at the channel-scale, and this was linked to the impacts of roughness length 37 upon channel-scale secondary-flow structures. These results show a poor equivalence between the roughness lengths needed in 2D models and those required for 3D models, especially in deeper areas of the river. Improved shear stress estimation was obtained with a two-layer model. However, this introduces additional parameters that are difficult to estimate a priori.
机译:遥感技术的最新进展使人们能够研究大型河流的形态动力学和水动力学。但是,在这些非常大的河流中测量地形和流量非常耗时,因此常常会限制可监视的空间分辨率和到达长度尺度。对于计算流体动力学(CFD),存在类似的约束条件,要求最大化网格或网格单元的尺寸,这意味着减小床形粗糙度元素的表示形式,即单元尺寸或更少的数量级,即使它们可用地形数据。这些“子网格”元素需要进行参数化,这里我们的目的是应用和考虑粗糙度长度处理的影响,其中包括由于“未测”地形引起的床面粗糙度的影响。发现CFD预测对粗糙度长度规格敏感。由于在粗糙长度处理中不能很好地参数化大型床形的影响,因此未发现增加粗糙长度是优化模型预测与现场数据之间一致性的特别有效手段。粗糙度长度的变化显示出对通道规模的流动路径有重大影响,这与粗糙度长度37对通道尺度的二次流结构的影响有关。这些结果表明,在2D模型中所需的粗糙度长度与3D模型中所需的粗糙度长度之间的等效性很差,尤其是在河流深处。使用两层模型获得了改进的剪切应力估计。然而,这引入了难以估计先验的其他参数。

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