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Predicting Transverse Mixing Efficiency Downstream of a River Confluence
Water Resources Research ( IF 4.6 ) Pub Date : 2020-07-23 , DOI: 10.1029/2019wr026367
S. Pouchoulin 1, 2 , J. Le Coz 2 , E. Mignot 1 , L. Gond 1, 2, 3 , N. Riviere 1
Affiliation  

Predicting mixing processes, especially transverse mixing, downstream of river confluences, is necessary for assessing and modeling the fate of pollutants transported in river networks, but it is still challenging. Typically, there is a lack of transverse mixing solutions implemented in 1‐D hydrodynamical models widely used in river engineering applications. To investigate the mixing processes developing downstream of a medium‐sized river confluence, three high‐resolution in situ surveys are conducted at the Rhône‐Saône confluence in France, based on geolocated specific conductivity and hydroacoustic measurements. Contrasting mixing situations are observed depending on hydrological conditions. In some cases, the two flows mix slowly due to turbulent shear at their vertical interface. This can be modeled by an analytical solution of the advection‐diffusion equation. In other cases, the waters from one of the two tributaries move under the waters of the other tributary. The induced local circulation enhances transverse mixing but not vertical mixing and the flow remains stratified vertically, which may be missed when surface or satellite images are analyzed qualitatively. Stratification may be predicted by comparing the time scales for shear and density‐driven adjustment. Shear‐dominated transverse mixing of depth‐averaged concentrations can be predicted analytically and implemented in 1‐D hydrodynamical models. However, the initiation of apparently rapid transverse mixing due to density‐driven circulation remains to be better understood and quantified.

中文翻译:

预测河流汇流下游的横向混合效率

预测河流汇合下游的混合过程,尤其是横向混合,对于评估和模拟在河网中运输的污染物的命运是必要的,但这仍然具有挑战性。通常,缺乏在河流工程应用中广泛使用的一维水动力模型中实现的横向混合解决方案。为了研究中型河汇流下游的混合过程,基于地理位置的比电导率和水声测量结果,在法国的罗纳-索恩汇合处进行了三项高分辨率的原位调查。根据水文条件,观察到相反的混合情况。在某些情况下,由于在其垂直界面处的湍流剪切,这两个流缓慢混合。这可以通过对流扩散方程的解析解来建模。在其他情况下,来自两个支流之一的水在另一个支流的水之下移动。诱导的局部循环增强了横向混合,但没有增强垂直混合,并且流保持垂直分层,当定性分析地面或卫星图像时可能会漏掉。可以通过比较剪切和密度驱动调整的时间尺度来预测分层。可以对深度平均浓度的剪切为主的横向混合进行解析预测,并在一维流体动力学模型中进行实施。然而,由于密度驱动的循环而引起的明显快速的横向混合的启动仍有待更好地理解和量化。来自两个支流之一的水流在另一个支流的水域下移动。引起的局部循环增强了横向混合,但没有增强垂直混合,并且流保持垂直分层,当定性分析地面或卫星图像时可能会漏掉。可以通过比较剪切和密度驱动调整的时间尺度来预测分层。可以对深度平均浓度的剪切为主的横向混合进行分析预测,并在一维流体动力学模型中实施。然而,由于密度驱动的循环而引起的明显快速的横向混合的启动仍有待更好地理解和量化。来自两个支流之一的水流在另一个支流的水域下移动。诱导的局部循环增强了横向混合,但没有增强垂直混合,并且流保持垂直分层,当定性分析地面或卫星图像时可能会漏掉。可以通过比较剪切和密度驱动调整的时间尺度来预测分层。可以对深度平均浓度的剪切为主的横向混合进行解析预测,并在一维流体动力学模型中进行实施。然而,由于密度驱动的循环而引起的明显快速的横向混合的启动仍有待更好地理解和量化。定性分析地表或卫星图像时可能会错过这些信息。可以通过比较剪切和密度驱动调整的时间尺度来预测分层。可以对深度平均浓度的剪切为主的横向混合进行解析预测,并在一维流体动力学模型中进行实施。然而,由于密度驱动的循环而引起的明显快速的横向混合的启动仍有待更好地理解和量化。定性分析地表或卫星图像时可能会错过这些信息。可以通过比较剪切和密度驱动调整的时间尺度来预测分层。可以对深度平均浓度的剪切为主的横向混合进行解析预测,并在一维流体动力学模型中进行实施。然而,由于密度驱动的循环而引起的明显快速的横向混合的启动仍有待更好地理解和量化。
更新日期:2020-07-23
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