Laboratory observations of solute transport in groundwater basins
Laboratory observations of solute transport in groundwater basins
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DOI：
10.1016/j.jclepro.2023.138832
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发表时间：
2023-09
影响因子：
11.1
通讯作者：
Hong Niu;Jun-Zhi Wang;Shengli Ni;Xing Liang;Hong Du
中科院分区：
文献类型：
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作者：
Hong Niu;Jun-Zhi Wang;Shengli Ni;Xing Liang;Hong Du
介绍了一种利用流动系统沙箱模型物理仪器在实验室进行地下水污染源识别的方法。介绍了简单流系统的单元盆地和分层嵌套流结构的托蒂安盆地作为案例研究。我们在补给区单独或同时添加逐步输入溶质，以获得每个放电区的突破曲线（BTC）。对于Unit盆地来说，其BTC呈现出逐渐上升的趋势，斜率逐渐减小，但有两个更明显的台阶，这与之前的解析和数值解结果有很大不同。这些步骤是由当前物理仪器的设置引起的，因为上部两个排放口没有输入溶质。对于托蒂安盆地，由于中间和区域地下水流系统到达较晚，可能存在内部台阶。尽管Unit盆地和Tóthian盆地都可以在BTC中存在内部台阶，但它们的原因不同。通过联合求解溶质质量平衡方程和水质量平衡方程，计算出各流动系统的循环速率，定量地解释了实验中遇到的现象，凸显了中间和区域流动系统对整个地下水循环的重要贡献。我们通过推导相对于时间的阶跃输入BTC来间接获得脉冲输入BTC，这也是地下水流域的停留时间分布（RTD），从而可以识别地下水污染源。脉冲输入 BTC 的特点是尖峰和斜尾。峰值对应于中间和区域地下水流系统。倾斜的尾部表示溶质被冲出或污染物消失的速率。通过将自来水输入地下水盆净化污染物，进行自净实验。溶质输入曲线和自净化曲线的形状是系统对称的。由于自净实验受外界干扰较小，可以利用自净曲线来表征和识别地下水流系统。本研究提出了一种识别地下水污染源的物理方法，全面了解地下水流域溶质运移规律，可指导流域尺度面源污染的防治。
This paper introduces a method of groundwater pollution source identification obtained from laboratory by a physical instrument of Flow System Sand-Box Model. A Unit basin of a simple flow system and a Tóthian basin of a hierarchically nested flow structure are introduced as case studies. We add step-input solutes at recharge zones, separately or simultaneously, to obtain the breakthrough curves (BTCs) at each discharge zone. For the Unit basin, its BTC shows a gradual upward trend with a decreasing slope but with two more pronounced steps, which differs a lot from previous results of analytical and numerical solutions. These steps are caused by the settings of the current physical instrument as no solutes are input at the upper two discharge ports. For the Tóthian basin, internal steps may exist due to the late-time arrival of intermediate and regional groundwater flow systems. Although the Unit basin and Tóthian basin can both have internal steps in the BTCs, they are due to different reasons. By jointly solving solute mass balance equations with water mass balance equations, the circulation rate for each flow system is calculated, which quantitatively explains the phenomena encountered in the experiment and highlights the important contributions of intermediate and regional flow systems to the entire groundwater circulation. We indirectly obtain the pulse-input BTCs by deriving the step-input BTCs respective to time, which is also the residence time distribution (RTD) of the groundwater basin, that the groundwater pollution sources can be identified. The pulse-input BTC is characterized by peaks and sloping tails. The peaks correspond to the intermediate and regional groundwater flow systems. The sloping tails indicate the rate at which solutes are flushed out or contaminants fade away. By inputting tap water into the groundwater basin to purify the contaminations, we conduct self-purification experiments. The shapes of the solute-input curves and the self-purification curves are systematically symmetrical. As the self-purification experiment has less external interference, it is possible to use the self-purification curves to characterize and identify the groundwater flow system. This study proposes a physical method for identifying sources of groundwater contamination, and achieves a comprehensive understanding of the law of solute transport in groundwater basins, which could guide the prevention of non-point contamination at the basin scale.