基于土壤物理特性扩展技术的土水特征曲线预测方法

土水特征曲线是模拟水和污染物在非饱和土中运移的重要水力特性参数。但是,土水特征曲线的直接量测方法比较困难。Arya和Paris提出了一种通过粒径分布曲线预测土水特征曲线的模型——AP模型。该模型引入一个转换系数α建立土体假想形态与真实形态之间的联系。但是,现有的推导系数α的方法一方面计算过程过于复杂,另一方面没有全面考虑土的物理特性。基于土壤物理特性扩展技术提出一种新的计算参数α的方法。为了验证新方法,从非饱和土水力特性数据库中选出不同类型的土壤样本,采用新方法分别计算出各类型土壤的参数α。然后,将计算出的参数α用于预测其他土样的土水特征曲线,从而验证新方法计算出的参数α的有效性。还将提出的新方法与其他利用AP模型预测土水特征曲线的代表性方法进行对比,结果显示该方法预测结果更加准确。

Prediction of soil water characteristic curve using physically based scaling technique

The soil water characteristic curve (SWCC) is an important hydraulic parameter for modeling water flow and contaminant transport in the unsaturated soil. However, direct measurement of the SWCC is still difficult. The Arya and Paris (AP) model estimates the SWCC from particle-size distribution curve (PSD) based on the shape similarity of the two curves. It introduces an empirical parameter, a, used to scale pore attributes from hypothetical formations to natural structures. Several approaches are used to derive a. However, the calculation procedures of these approaches are either quite complicated or developed without paying much attention to the physical significance of the soil properties. In the present paper the physically based scaling technique (PBS) is employed to derive a for the AP model. Fifty soil samples, representing a range of textures that include sand, sandy loam, loam, silt loam and clay, are selected from UNSODA hydraulic property database for calculating a using the PBS approach. In addition, nineteen soil samples with different textures are used to verify the effectiveness of proposed a values. The results are compared with those of other approaches and show that the PBS technique combining with the AP model is a more useful and easier approach to predict SWCC from PSD.