冬小麦生长条件下土壤硝态氮淋洗的传递函数模拟和预报  

Simulation and prediction of nitrate-nitrogen leaching from soils under the growth period of winter wheat using transfer function model

作　　者：任理[1] 袁福生[1] 张福锁[1] 

机构地区：[1]中国农业大学资源与环境学院

出　　处：《生态学报》2004年第10期2281-2288,共8页Acta Ecologica Sinica

基　　金：国家重点基础研究发展规划资助项目 ( G19990 1180 3 ) ;北京市自然科学基金重大资助项目 ( 6980 0 0 1)~~

摘　　要：观测了地中渗透计的土壤在 3种不同施肥量下冬小麦自播种至返青期硝态氮的淋洗动态 ,由试验资料获得了硝态氮在土壤中迁移时间的概率密度函数 ,进而运用传递函数模型对土壤排水出流液中的硝态氮浓度和淋洗量动态进行了数学模拟和预报。The leaching losses of indigenous and applied nitrate-nitrogen were measured for the non-weighing lysimeter in soils under the condition of winter wheat cropping. The transfer function model (TFM) developed by Jury et al. and White was used to simulate nitrate-nitrogen transport through unsaturated heterogeneous soils. The probability density functions (pdfs) of the travel times of the nitrate-nitrogen under the experiment condition were determined from the normalized rates of loss of nitrate-nitrogen mass to the drains. The pdfs for the experimental site conformed to a lognormal distribution. The nitrate-nitrogen concentrations in the output flow at 200cm depth and the accumulative quantities of nitrate-nitrogen leached in soils during the winter wheat cropping were simulated using the equations proposed by White. Good agreements were obtained between the simulated and the measured values both the dynamics of concentration and the quantities of nitrate-nitrogen leached. In addition, using same equation proposed by White with the pdfs of the travel time of the nitrate-nitrogen obtained from different experimental site of the lysimeter, the accumulative quantities of nitrate-nitrogen leached during the winter wheat cropping were also predicted. A reasonable leaching of nitrate-nitrogen results was estimated for three treatments of fertilizer in the field according to the mathematical model. Finally, the effects of the amount of nitrogenous fertilization, crop season on the leaching of nitrate-nitrogen were primarily analyzed.

关 键 词：土壤 地中渗透计 冬小麦 硝态氮 淋洗 传递函数模型 模拟 预报 

分 类 号：S153[农业科学—土壤学]