• 关键词：土壤  农药  淋溶  对流弥散方程  传递函数模型  预报

• 基金项目：国家重点基础研究发展规划项目(G1999045706);国家自然科学基金项目(40271058)

• 任理
• 中国农业大学土壤和水科学系,教育部植物土壤相互作用重点实验室,北京 100094

• 毛萌
• 中国农业大学土壤和水科学系,教育部植物土壤相互作用重点实验室,北京 100094

• 张仁铎
• 美国怀俄明大学再生资源系,Laramie WY82071-3354

• 摘要：基于对流弥散方程(CDE)的解和传递函数模型(TFM)中呈对数正态分布的溶质迁移时间的概率密度函数,构造了稳定流场饱和砂质壤土中仅考虑吸附作用时农药淋溶动态的预报模式.建立该模式的思路首先是利用示踪剂的穿透曲线,由CDE的解析解反求水动力弥散系数;再针对不同的阻滞因子通过求解CDE正问题的数学实验,生成农药穿透曲线的模拟值.接着应用对数正态概率密度函数拟合得到相应于不同阻滞因子的农药迁移时间的均值和方差.结果表明:均值与阻滞因子为乘幂函数的关系,而方差随阻滞因子的变化甚小,且不同流速下农药迁移时间的均值与方差随阻滞因子的变化亦呈现相同的规律.通过农药阿特拉津的淋溶实验对该模式的预报精度进行了检验.

• Abstract：Based on the convection-dispersion equation (CDE) and the transfer function model (TFM) on a lognormal probability density function (pdf) of solute travel time, a new predicting model was developed to describe the leaching dynamics of pesticides undergoing adsorption in a sandy loamy saturated soil during steady flow. To establish the model, (i) we carried out a tracer miscible displacement experiment to obtain the breakthrough curve (BTC), and then applied the code CXTFIT 2.0 to solve an inverse problem for obtaining hydraulic dispersion coefficient, (ii) for the different retardation factors of various pesticides, we constructed a series mathematical experiments to solve the direct problem of CDE, and the simulated BTCs of the pesticides were generated, and (iii) fit the simulated BTCs with lognormal pdfs, and the mean and variance values of the travel times corresponding to the different retardation factors of various pesticides were obtained. We found that, there was a power function relationship between mean and retardation factor, while the fluctuation of variance was small with respect to the retardation factor. Moreover, the same trend was presented in the change of the retardation factors with the mean and variance values of travel times at different averaged pore water velocities. Satisfying results were received in testing the precision of the model prediction by using the leaching experiment of atrazine.

• Key words：soil  pesticide  leaching  convection-dispersion equation  transfer function model  prediction.

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