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Surrogate prediction of the breakthrough curve of solute transport in rivers using its reach length dependence
Journal of Contaminant Hydrology ( IF 3.6 ) Pub Date : 2022-05-14 , DOI: 10.1016/j.jconhyd.2022.104024
Byunguk Kim 1 , Siyoon Kwon 1 , Hyoseob Noh 1 , Il Won Seo 2
Affiliation  

Techniques for predicting the contaminant cloud propagation along a stream are necessary for swift action against contaminant spill accidents in fluvial systems. Due to their low computational cost, one-dimensional solute transport models have conventionally been employed, in which the complex channel characteristics are considered using model parameters. However, the determination of such parameters relies predominantly on optimization techniques based on pre-measured tracer data, which are usually unavailable for unexpected accidents. The present paper suggests an alternative method for predicting a breakthrough curve (BTC) variation along an unmeasured stream reach where no flow information is provided. In this study, we investigated the relationship between directly-measured flow properties and BTC characteristics based on field tracer experiments. Using statistical features of the tracer BTCs, we devised a regressive prediction method for estimating the BTC features as a function of travel distance, and validated the method by comparison with simulations using both a one-dimensional advection–dispersion equation (ADE) and transient storage model (TSM), whose parameters were calibrated at upstream reaches. The proposed regressive predictions were relatively accurate than those from parameter-calibrated models, and this advantage was more apparent for long-distance predictions for the unmeasured river reach.



中文翻译:

利用河段长度依赖性替代预测河流中溶质输运的突破曲线

预测污染物云沿河流传播的技术对于快速应对河流系统中的污染物溢出事故是必要的。由于它们的计算成本低,一维溶质输运通常采用模型,其中使用模型参数来考虑复杂的信道特性。然而,这些参数的确定主要依赖于基于预先测量的示踪数据的优化技术,这些数据通常不适用于意外事故。本文提出了一种替代方法,用于预测沿未提供流量信息的未测量河段的突破曲线 (BTC) 变化。在本研究中,我们基于现场示踪实验研究了直接测量的流动特性与 BTC 特性之间的关系。使用追踪器 BTC 的统计特征,我们设计了一种回归预测方法,用于估计 BTC 特征作为行进距离的函数,并通过与使用一维平流-扩散方程(ADE)和瞬态储存模型(TSM)的模拟进行比较来验证该方法,其参数在上游河段进行了校准。所提出的回归预测比参数校准模型的预测相对准确,并且这种优势对于未测量的河流范围的长距离预测更为明显。

更新日期:2022-05-14
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