Background

Total suspended solids (TSS) loads carried by stormwater runoff is a major pollutant source on receiving water bodies. Stormwater ponds are widely used for controlling TSS discharge. However, the trap efficiency is not satisfactory because it is affected by many complex factors, which are not fully understood. Therefore, there is a necessity to gain insight into the sediment process in stormwater ponds for optimization design of stormwater ponds. To address this issue, we propose a novel modeling framework based on discrete phase model (DPM), aiming to fully represent the sediment transport, settling, and resuspension at grain scale under time-dependent conditions.

Results

In the newly proposed method, heterogeneous characteristics of sediments’ loads, varying flows and sediment loads, settling and resuspension effect at grain scale, time-dependent conditions, and turbulent effect are all well considered. The proposed models have been coded with C language and hooked in computational fluid dynamics software Fluent, and the methods were tested with a case of laboratory experimental setup. Different bed boundary conditions are tested and compared with the observation data for optimization parameters’ identification. The simulation results demonstrated that the physically based DPM with the newly developed method can well reproduce the evolution of sediment transport, settling and resuspension behaviors compared with the scale experiment.

Conclusions

The newly proposed method can accurately predict the trap efficiency and temporal–spatial sediment distribution. The decomposition of bed load motion at grain scale is a necessary and valid way to represent the sedimentation process in shallow ponds. The developed model could be a tool to help us gain insight into the sediment transport phenomena at grain scale in shallow tanks since it can provide detailed information which the experiment cannot.

中文翻译：

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人工雨水池中非稳态条件下颗粒运移，沉积和再悬浮的数值研究

背景

雨水径流携带的总悬浮固体（TSS）负荷是接收水体的主要污染物源。雨水塘被广泛用于控制TSS排放。但是，捕集阱的效率不能令人满意，因为它受许多复杂因素的影响，而这些因素尚未得到充分理解。因此，有必要深入了解雨水塘的沉积过程，以优化雨水塘的设计。为了解决这个问题，我们提出了一个基于离散相模型（DPM）的新颖的建模框架，旨在完全代表随时间变化的条件下颗粒尺度上的沉积物迁移，沉降和重悬浮。

结果

在新提出的方法中，充分考虑了沉积物载荷的非均质特性，变化的流量和沉积物载荷，颗粒尺度上的沉降和重悬浮效应，时变条件和湍流效应。所提出的模型已用C语言编码，并与计算流体动力学软件Fluent挂钩，并在实验室实验设置的情况下对这些方法进行了测试。测试了不同的床边界条件，并将其与观测数据进行比较，以识别优化参数。仿真结果表明，与规模实验相比，采用新开发的方法的基于物理的DPM可以很好地再现沉积物的迁移，沉降和再悬浮行为。

结论

新提出的方法可以准确地预测圈闭的效率和时空沉积物的分布。颗粒尺度上床荷运动的分解是表征浅水池沉积过程的必要和有效途径。所开发的模型可以提供深入实验无法获得的详细信息，因此可以帮助我们深入了解浅水箱中颗粒尺度的沉积物迁移现象。