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Numerical Simulation of Unsteady Hyperconcentrated Sediment-Laden Flow in the Yellow River

机译:黄河不稳定高浓度含沙流的数值模拟。

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The major obstacles to simulating flood flow in the Yellow River are its high sediment concentration, complex compound cross section, and rapid change in channel planform. This paper presents an improved one-dimensional numerical model that takes into account the effect of sediment concentration and bed change on mass and momentum conservation of flood flow in the Yellow River. The model is calibrated and then validated by simulating three individual flood events. Results show that an increase in sediment concentration leads to a reduction in flood wave celerity and peak discharge. The generalized likelihood uncertainty estimation (GLUE) method is used to evaluate the uncertainty of modeling results. A sensitivity index, analogous to the Nash-Sutcliffe efficiency factor, is adopted to quantify the sensitivity of calibration parameters. The modeling results are sensitive to the choice of Manning's roughness coefficient and the empirical recovery coefficient for suspended sediment transport at reaches of transitional channel planform.
机译:黄河模拟洪水的主要障碍是其高的泥沙浓度,复杂的复合剖面以及河道平面形式的快速变化。本文提出了一种改进的一维数值模型,该模型考虑了泥沙浓度和河床变化对黄河洪水流量和动量守恒的影响。对该模型进行校准,然后通过模拟三个单独的洪水事件进行验证。结果表明,泥沙浓度的增加导致洪水波速度和峰值流量的减少。广义似然不确定性估计(GLUE)方法用于评估建模结果的不确定性。采用类似于Nash-Sutcliffe效率因子的灵敏度指数来量化校准参数的灵敏度。模拟结果对Manning粗糙度系数的选择和过渡河道平面型河段悬沙输沙经验回收系数的选择很敏感。

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