Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, Delhi 110016, India.
Institute of Groundwater Management, Technische Universität Dresden, Germany; Department of Civil Engineering, Manipal University Jaipur, India.
J Contam Hydrol. 2020 Nov;235:103709. doi: 10.1016/j.jconhyd.2020.103709. Epub 2020 Sep 1.
A large number of potentially contaminated sites reported worldwide require cost- and time-effective assessment of the extent of contamination and the threats posed to the water resources. A significant risk assessment metric for these sites can be the determination of the maximum (i.e., steady-state) contaminant plume length (L). Analytical approaches in the literature provide an option for such an assessment, but they include a certain degree of uncertainty. Often, the causes of such uncertainties are the simplifications in the analytical models, e.g., not considering the influence of hydrogeological stresses such as recharge, which impact the plume development significantly. This may lead to an over- or underestimation of L. This work includes the influence of the recharge for the effective estimation of L. For that, several two-dimensional (2D) numerical simulations have been performed by considering different aquifer thicknesses (1 m- 4 m) and recharge rates (ranging from 0 to 3.6 mm/day). From the numerical results of this work, it has been deduced that 1) the application of the recharge shortens L, and the recharge entering the aquifer top causes the plume to tilt, 2) the reduction percentage in L depends on the recharge rate applied and the aquifer thickness, and 3) the reduction percentage varies in a non-linear manner with respect to the recharge rate for a fixed aquifer thickness. Based on these results, a hybrid analytical-empirical solution has been developed for the estimation of L with the inclusion of the recharge rate. The proposed hybrid analytical-empirical solution superimposes an empirically obtained correction factor onto an analytical solution. Although extensive confirmation steps of the developed model are required for including the effect of the recharge on aquifer hydraulics, the proposed expression improves the estimation of the L significantly. The hybrid analytical-empirical solution has also been confirmed with a selection of limited field contamination sites data. The hybrid model result (L) provides a significant improvement in the estimation, i.e., an order of magnitude lower mean relative error compared to the analytical model.
大量在全球范围内报告的潜在污染场地需要对污染程度和对水资源构成的威胁进行具有成本效益和时间效益的评估。对于这些场地，可以采用确定最大（即稳态）污染物羽流长度（L）作为重要的风险评估指标。文献中的分析方法为这种评估提供了一种选择，但它们包含一定程度的不确定性。通常，这种不确定性的原因是分析模型的简化，例如，不考虑补给等水文地质应力对羽流发展的显著影响。这可能导致对 L 的高估或低估。本工作包括补给对有效估计 L 的影响。为此，考虑了不同含水层厚度（1 米-4 米）和补给率（0 至 3.6 毫米/天），通过进行了几个二维（2D）数值模拟。从本工作的数值结果可以推断出：1）补给的应用缩短了 L，进入含水层顶部的补给会导致羽流倾斜；2）L 的减少百分比取决于应用的补给率和含水层厚度；3）对于固定的含水层厚度，L 的减少百分比与补给率呈非线性变化。基于这些结果，开发了一种包含补给率的 L 估算的混合分析-经验解决方案。所提出的混合分析-经验解决方案将经验获得的校正因子叠加到分析解决方案上。尽管需要进行广泛的模型确认步骤以包括补给对含水层水力学的影响，但所提出的表达式可以大大提高 L 的估计精度。还使用有限的现场污染场地数据对混合模型进行了验证。与分析模型相比，混合模型的结果（L）在估计方面有显著提高，即平均相对误差低一个数量级。
