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Random-walk simulation of non-conservative pollutant transport in shallow water flows

机译:浅水流动中非保守污染物运输的随机步行仿真

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The random-walk method is inherently simple and numerically stable. However, when used in hydro-environmental analyses, most of the existing random-walk methods ignore the influence of the non-uniform water depth and only consider the transport of inert materials, hence the inability of modelling biochemical reactions. In addition, the existing applications mainly focus on instantaneous-release problems, where a fixed number of particles move in the computational domain. This paper first presents examples to showcase the capability of a newly-developed random-walk model in simulating the continuous sources of non-conservative substances. Then, the method is applied to examine the BOD-DO balance along a hypothetical river. The predictions agree well with analytical solutions. Finally, the developed model is used to study the pollutant transport in the Thames Estuary. The current model is illustrated to be able to accurately predict the interaction between multiple pollutants in real-world situations with uneven bathymetry and extensive intertidal floodplains.
机译:随机步行方法本质上是简单且数值稳定的。然而,当在水力环境分析中使用时,大多数现有的随机步行方法忽略了非均匀水深的影响,并且只考虑惰性材料的运输,因此无法建模生化反应。此外,现有应用主要关注瞬时释放问题,其中固定数量的粒子在计算域中移动。本文首先展示了展示了新开发的随机步道模型的能力,在模拟了非保守物质的连续来源。然后,应用该方法以沿着假设河流检查BOD DO平衡。预测与分析解决方案都很好。最后,开发的模型用于研究泰晤士河河口的污染物运输。示出了当前模型,以便能够准确地预测多个污染物在现实世界情况之间的相互作用,其具有不均匀的沐浴术和广泛的跨潮泛源性。

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