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Quantitative assessment of groundwater pollution intensity on typical contaminated sites in China using grey relational analysis and numerical simulation

机译:基于灰色关联分析和数值模拟的中国典型污染场地地下水污染强度定量评价。

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摘要

Groundwater vulnerability assessment is an important method for groundwater pollution risk assessment. However, vulnerability assessment results rarely consider groundwater pollution concentration. Few quantitative studies consider groundwater pollutant concentration in different hydrogeological conditions. HYDRUS-1D software can simulate different concentrations of pollutants reaching the shallow aquifer under some vadose zone conditions. However, HYDRUS-1D simulation parameter settings are complicated; thus, it is difficult to simulate groundwater pollution intensity (GPI) on the site with limited information. In this study, the issue of site data constraints for model predictions is solved. Ammonia-nitrogen is selected as an indicator, and a method for quantitative groundwater pollution assessment based on grey relational analysis (GRA) is proposed. According to two factors (inherent, extrinsic) of groundwater vulnerability assessment, and on the basis of the information from 18 contaminated sites, primary GPI control factors, including emission concentration, hydraulic conductivity, soil density and diffusion coefficient, are filtered using GRA. These four factors are utilized as variables to establish a multiple linear regression (MLR) equation, which is used to predict the GPI of polluted sites. Compared with a HYDRUS-1D simulation, the proposed GPI prediction method can effectively predict GPI with simpler input conditions. The established MLR equation satisfies a significance test and small error analysis. Comparative results between simulation values and regression values on the established case show that the regression values are closer to the measured value. Hence, the MLR equation is practical and can be applied for sensible groundwater source management and land use planning.
机译:地下水脆弱性评估是评估地下水污染风险的重要方法。但是,脆弱性评估结果很少考虑地下水污染浓度。很少有定量研究考虑不同水文地质条件下的地下水污染物浓度。 HYDRUS-1D软件可以模拟在某些渗流带条件下到达浅层含水层的不同污染物浓度。但是,HYDRUS-1D模拟参数设置很复杂。因此,很难用有限的信息模拟现场的地下水污染强度(GPI)。在这项研究中,解决了用于模型预测的站点数据约束问题。以氨氮为指标,提出了一种基于灰色关联分析的定量地下水污染评价方法。根据地下水脆弱性评估的两个因素(固有的,外部的),并基于来自18个受污染地点的信息,使用GRA过滤了主要的GPI控制因素,包括排放浓度,水力传导率,土壤密度和扩散系数。这四个因素被用作变量以建立多元线性回归(MLR)方程,该方程用于预测污染站点的GPI。与HYDRUS-1D仿真相比,该GPI预测方法可以在更简单的输入条件下有效地预测GPI。建立的MLR方程满足显着性检验和小误差分析。在确定的情况下,模拟值和回归值之间的比较结果表明,回归值更接近于测量值。因此,MLR方程很实用,可以用于合理的地下水源管理和土地利用规划。

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