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Hydrodynamic dispersion coefficient of ammonium in undisturbed soil columns

机译:未受干扰的土柱中铵的流体动力分散系数

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Determination of solute transport parameters is fundamental in numerical modelling and estimation of contaminant movement in the soil. Usually the transport parameters are obtained in the laboratory by columns tests in disturbed samples. However, disturbed samples may not accurately reflect real situations that are subjected to the presence of natural imperfections, influencing the transport parameters values, mainly the hydrodynamic dispersion coefficients (D_h). In this paper we determined D_h values of ammonium (NH_4~+) in undisturbed soil columns and observed the possible effects of the natural imperfections on these values. Column tests in undisturbed samples were performed to obtain the average linear velocity, Darcy velocity and hydraulic conductivity. Later, three solutions of (NH_4)_2HPO_4 were percolated through the columns. The NH_4~+ breakthrough curves were plotted and the D_h values were determined by the methods proposed by Singh (1998) and Bear (1961). We found that both the soil chemical characteristics and macroporosity strongly influenced D_h values. Our overall conclusion was that soils with intact structure are subjected to the presence of natural variations that may powerfully affect D_h values. Moreover, we concluded that a method that uses directly the velocity values in the D_h calculation, cannot be appropriate when there are macropores in the column. Finally, these values obtained from undisturbed columns can result in more reliable data and greater accuracy in prediction of contaminant movement.
机译:溶质转运参数的测定是土壤中污染物运动的数值模拟和估算的基础。通常通过扰动样品中的柱测试在实验室中获得运输参数。然而,受干扰的样本可能无法准确反映经受自然缺陷的存在的实际情况,影响运输参数值,主要是流体动力分散系数(D_h)。在本文中,我们确定了不受干扰的土柱中铵(NH_4〜+)的D_H值,并观察到自然缺陷对这些值的可能影响。进行不受干扰的样品中的柱测试以获得平均线性速度,达西速度和液压导率。后来,通过柱渗滤(NH_4)_2HPO_4的三种溶液。绘制NH_4〜+突破曲线,D_H值由SINGH(1998)和BEAR(1961)提出的方法确定。我们发现土壤化学特性和宏观度都强烈影响了D_h值。我们的整体结论是,具有完整结构的土壤受到可能有力影响D_H值的自然变化的存在。此外,我们得出的结论是,在列中存在Macropores时,使用直接使用D_H计算中的速度值的方法。最后,从未受干扰的柱获得的这些值可以导致更可靠的数据和更高的污染物运动预测的准确性。

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