Department of Civil Engineering, Birla Institute of Technology and Science Pilani, Pilani, India.
Environ Monit Assess. 2019 Apr 9;191(5):271. doi: 10.1007/s10661-019-7433-0.
The work incorporates the field data collection, assessment, and use of interpolation and extrapolation methods in modeling the existence of pollutant in groundwater, namely nitrate, and future prediction. To view the variation of concentration of pollutants in any form, 3D representation is required. However, not many techniques are available to achieve the objective accurately. Many modeling studies are done but very little is known about the variation of a group of chemical parameters at vertical scale in any of the climatic zone or habitable region. This kind of study is needed to help stakeholders for better planning. Earlier studies do not show the variation of chemical parameters (contaminants) at vertical scale in the climatic zone, and modellings are very objective specific. Present work presents 3D models using Inverse Distance Weighting technique in Matlab. The concentration pattern of nitrate is studied in 3D and presented in lucid manner at regional scale. The 3D block presentation demonstrates its affiliation and dispersion. The relationship from these models between parameter fixation and profundity shows the presence of distinct layers up to desired depth. The relationship plots are developed to extract the information how the groundwater quality is being transmitted beneath the surface. The projection is verified with the real field data, which will help in future resource management actions and minimize the pollution risks to mankind and the environment. The modeling helps in selecting the danger zones for ground water recharge and discharge for natural cause of elevated concentration of nitrate in groundwater. This study opens up the methodology for finding the variation of other contaminants against depth and that of total water quality.
这项工作结合了现场数据收集、评估以及在地下水污染物（即硝酸盐）建模中应用插值和外推方法，以及未来预测。为了观察任何形式的污染物浓度变化，需要进行 3D 表示。然而，目前并没有很多技术可以准确地实现这一目标。虽然已经进行了许多建模研究，但对于在任何气候带或宜居地区的垂直尺度上，一组化学参数的变化情况却知之甚少。这种研究对于利益相关者的更好规划是必要的。早期的研究并没有显示出在气候带的垂直尺度上化学参数（污染物）的变化情况，而且建模非常具体和客观。本研究使用 Matlab 中的逆距离加权技术呈现 3D 模型。对硝酸盐的浓度模式进行了 3D 研究，并以清晰的方式在区域尺度上呈现。3D 块状图展示了其关联性和分散性。这些模型中参数固定和深度之间的关系表明，在所需深度范围内存在明显的分层。通过绘制关系图，可以提取有关地下水质量在地表以下传输情况的信息。该投影与实际现场数据进行了验证，这将有助于未来的资源管理行动，并最大程度地减少人类和环境面临的污染风险。该模型有助于选择地下水补给和排放的危险区域，以应对由于硝酸盐浓度自然升高而导致的地下水问题。这项研究为针对其他污染物随深度的变化以及整体水质变化的研究提供了方法。
