Globally there exist a very large number of contaminated or possibly contaminated sites where a basic preliminary assessment has not been completed. This is largely, among others, due to limited simple methods/models available for estimating key site quantities such as the maximum plume length, further denoted as and the corresponding time , at which the plume reaches its maximum extent . An approach to easily obtain an estimate of in particular is presented in this work. Limited availability of high-quality field data, particularly of , necessitates the use of synthetic data, which constrains the overall model development works. Taking BIOSCREEN-AT (transient 3D model) as a base model, this work proposes second-order polynomial models, with only two parameters, for estimating and . This reformulation of the well established solution significantly reduces data requirement and workload for initial site assessment purposes. A global sensitivity analysis (), using a large number of random synthetic data, identifies the first-order decay rate constants in the plume and at the source as dominantly most influential for . For , the first-order decay rate constant and groundwater velocity are the two important parameters. The sensitivity analysis also identifies that these parameters non-linearly impact or . With this information, the proposed polynomial models (each for and ) were trained to obtain model coefficients, using a large amount of synthetic data. For verification, the developed models were tested using four datasets comprising over 100 sample sets against the results obtained from BIOSCREEN-AT and the developed BIOSCREEN-AT-based steady-state model. Additionally, the developed models were evaluated against two well documented field sites. The proposed models largely simplify estimation, particularly, of , for which only very limited field or literature information is available.

中文翻译：

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一种数据驱动的方法，用于简化污染物羽流达到最大程度的时间估计

全球范围内存在大量受污染或可能受污染的场地，但基本的初步评估尚未完成。除其他外，这主要是由于可用于估计关键地点数量（例如最大羽流长度，进一步表示为羽流达到其最大程度的相应时间）的简单方法/模型有限。这项工作提出了一种轻松获得估计值的方法。高质量现场数据（尤其是 ）的可用性有限，因此需要使用合成数据，这限制了整体模型开发工作。以 BIOSCREEN-AT（瞬态 3D 模型）为基础模型，本文提出了只有两个参数的二阶多项式模型，用于估计 和 。这种对成熟解决方案的重新表述显着减少了初始现场评估目的的数据需求和工作量。使用大量随机合成数据的全局敏感性分析 () 确定了羽流和源头中对 的影响最大的一阶衰减率常数。对于 ，一阶衰减率常数和地下水流速是两个重要参数。敏感性分析还发现这些参数非线性影响 或 。有了这些信息，使用大量的合成数据对所提出的多项式模型（分别为 和 ）进行训练以获得模型系数。为了验证，开发的模型使用包含 100 多个样本集的四个数据集根据 BIOSCREEN-AT 和开发的基于 BIOSCREEN-AT 的稳态模型获得的结果进行了测试。此外，还针对两个有据可查的现场站点对开发的模型进行了评估。所提出的模型极大地简化了估计，特别是 的估计，因为只有非常有限的领域或文献信息可用。