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Hydrodynamic Simulation of an Irregularly Meandering Gravel-Bed River: Comparison of MIKE 21 FM and Delft3D Flow models

机译:不规则蜿蜒的砾石床的流体动力学模拟:Mike 21 FM和Delft3D流模型的比较

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摘要

This study aims at hydrodynamic modelling of Bow River, which passes through the City of Calgary, Canada. Bow River has a mobile gravel bed. Erosion and deposition processes were exacerbated by a catastrophic flood in 2013. Channel banks were eroded at various locations, and large gravel bars formed, which could lead to water level changes and accordingly more flooding. This study investigates the performance of Delft3D-Flow and MIKE 21 FM to simulate the hydrodynamics of the river during the 2013 flood. MIKE 21FM employs unstructured triangular mesh while Delft3D-Flow model uses curvilinear structured grids. Performance of each model was evaluated by the available historical water levels. The results of this study demonstrated that, with approximately the same averaged grid resolution, MIKE 21 FM resulted in more accurate results with a higher computational cost compared to the Delft3DFlow model. It was shown that Delft3D-Flow model may require higher grid cell resolution to result in comparably same depth-averaged velocities throughout the study area. However, considering the balance between the computational cost and the accuracy of the results, both models were capable to adequately replicate the hydrodynamics of the river during the 2013 flood. Results of statistical KS and ANOVA test analysis showed that the model predictions were sensitive to the horizontal eddy viscosity and the Manning roughness. This confirms the necessity of an appropriate calibration of the generated numerical models. The findings of this study shed light on the Bow River flood modelling, which can guide flood management.
机译:本研究旨在朝向加拿大卡尔加里市的流体动力学建模。弓河有一个移动砾石床。 2013年灾难性洪水加剧了侵蚀和沉积过程。渠道银行在各个地点被侵蚀,形成了大型砾石条,这可能导致水位变化,因此更大的洪水。本研究调查了Delft3D-Flow和Mike 21 FM的性能,以模拟2013年洪水中河流的流体动力学。迈克21FM采用非结构化三角网格,而Delft3D-Flow型号使用曲线结构栅格。每个模型的性能由可用的历史水平评估。该研究的结果证明,具有大致相同的平均网格分辨率,迈克21 FM与Delft3DFlow模型相比,使用更高的计算成本更准确地产生更准确的结果。结果表明,Delft3D-Flow模型可能需要较高的网格单元分辨率,以导致整个研究区域中相同相同的深度平均速度。然而,考虑到计算成本与结果的准确性之间的平衡,两种模型都能够在2013年洪水期间充分复制河流的流体动力学。统计KS和ANOVA测试分析结果表明,模型预测对水平涡粘度和曼宁粗糙度敏感。这证实了所生成的数值模型的适当校准的必要性。这项研究的调查结果揭示了弓河洪水建模,可以引导洪水管理。

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