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Time behavior of solute transport in heterogeneous media: transition from anomalous to normal transport

机译:溶质运移在非均质介质中的时间行为:从异常运移到正常运移

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We study the time behavior of solute transport in a heterogeneous medium. We consider a spatially biased continuous time random walk (CTRW) governed by ψ(s, t), the joint probability density for an event-displacement s with an event-time t. In this effective transport framework the concentration distribution of a solute is given by a generalized master equation (GME). We present results detailing the time dependence for the resident and flux concentrations, the center of mass velocity and the macroscopic dispersion coefficients of the solute plume. The Laplace transform of the GME is converted to a spatial differential equation resembling the advection dispersion equation (ADE), with Laplace space dependent coefficients though, and can then be solved explicitly in Laplace space. The transport behavior of the solute is then determined by accurate numerical inverse Laplace transforms. The confirmation of the accuracy of our methods is demonstrated by the excellent agreement with efficient random walk simulations based on the same ψ(s, t). The ψ(s, t) is given by the product of a Gaussian distribution for s and a truncated power-law distribution for t. This particular choice allows for a systematic study of the time regimes of anomalous and normal transport behavior and the transition from normal to anomalous behavior. The presented results show new aspects for the modeling of solute transport in heterogeneous media, in particular the effect of the system "memory" on plume patterns at asymptotically long times. In a specific application we solve for the contaminant flux entering a stream from a point injection of tracer in a catchment. The results are discussed as an independent test of a model of fractal stream chemistry in catchments.
机译:我们研究了在异质介质中溶质运输的时间行为。我们考虑由ψ(s,t)控制的空间偏置连续时间随机游走(CTRW),即事件-时间为t的事件位移s的联合概率密度。在这种有效的传输框架中,溶质的浓度分布由广义主方程(GME)给出。我们提供的结果详细说明了驻留和通量浓度,质量中心和溶质羽流的宏观弥散系数的时间依赖性。 GME的拉普拉斯变换被转换为类似于对流弥散方程(ADE)的空间微分方程,但是具有与拉普拉斯空间有关的系数,然后可以在拉普拉斯空间中明确求解。然后,通过精确的数值拉普拉斯逆变换确定溶质的传输行为。通过基于相同ψ(s,t)的高效随机游走模拟的出色一致性证明了我们方法的准确性。 ψ(s,t)由s的高斯分布和t的截断幂律分布的乘积给出。这种特殊的选择允许系统地研究异常和正常运输行为的时间范围以及从正常行为到异常行为的过渡。提出的结果显示了在非均质介质中溶质运移建模的新方面,特别是系统“内存”在渐近长时间内对羽流模式的影响。在特定的应用中,我们解决了从示踪剂在集水区中点注入而进入流中的污染物通量的问题。结果作为流域分形流化学模型的独立测试进行了讨论。

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