任何复杂系统都具有不同层次的时空结构特征，而所有不同的时空结构均具有尺度属性。不同尺度下土壤氮磷养分迁移过程也具有显著不同的时空结构特征（如养分迁移的途径、驱动力和影响因素等）和属性分异（如养分迁移的速率、状态及源汇分布等），导致不同尺度下土壤养分迁移规律的不一致和对养分迁移模拟结果的“同构异果”现象。本项目以十多年流域水质定点监测并经LOADEST模型率定得到的每日河流养分变化资料为基础，结合农田尺度上养分监测网络所取得的序列资料，通过小波变换分析，把流域尺度上河流养分变化母函数分解为若干个子函数，探索能与农田尺度上土壤养分平衡变化过程相匹配的子函数，深入揭示养分迁移过程在两种尺度下关键因子的时空组合方式；利用地统计学方法重构流域尺度和农田尺度之间养分运移的定量关系；以此为基础，建立流域尺度河流水质变化与农田尺度养分输出过程的联合模拟模型，实现两种尺度下的监测和试验资料更有效耦合与转化。

Any complex system has the spatial and temporal structure characteristics within different levels, and all the spatial and temporal structures at a different level have their own scale features. The transports of soil nitrogen and phosphorus nutrients under a different scale are also significantly different from their spatial and temporal structure (such as the moving ways and moving channels, the driving forces and their influencing factors ) and different properties (such as the rate and state parameters of nutrient migration and their influencing factors), which may lead to inconsistency for soil nutrient migration regular pattern and a phenomenon of "different result under a isomorphism " for the nutrient transport simulation. This project, based on the data of the daily river water nutrient variation obtained from the in-situ monitoring and calibration by LOADEST model for more than ten years, the wavelet transform and geostatistical methods were used to decompose the generating function of river water nutrient variation on watershed scale into several sub-functions; then, combine with the geographical and ecological pattern analysis for each farmland to reveal the nutrient migration structure characteristics and properties under watershed and farmland scales; lastly, try to reconstruct nutrient transfer process of the key factors in two different scales. On the basis of this, a joint simulation model would be constructed to directly simulate both the water quality changes in a watershed scale and the nutrient output process in a farmland scale. Through the study of the scaling effects of nutrient migration in watershed and farmland scales, we try to realize a more effective coupling and transforming each other for the two scales of monitoring data.