Shen Zhenyao, Hong Qian, Yu Hong, Liu Ruimin
State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, PR China.
Sci Total Environ. 2008 Nov 1;405(1-3):195-205. doi: 10.1016/j.scitotenv.2008.06.009. Epub 2008 Jul 18.
The generation and formation of non-point source pollution involves great uncertainty, and this uncertainty makes monitoring and controlling pollution very difficult. Understanding the main parameters that affect non-point source pollution uncertainty is necessary to provide the basis for the planning and design of control measures. In this study, three methods were adopted to do the parameter uncertainty analysis with the Soil and Water Assessment Tool (SWAT). Based on the results of parameter sensitivity analysis by the Morris screening method, the ten parameters that most affect runoff, sediment, organic N, nitrate, and total phosphorous (TP) were chosen for further uncertainty analysis. First-order error analysis (FOEA) and the Monte Carlo method (MC) were used to analyze the effect of parameter uncertainty on model outputs. FOEA results showed that only a few parameters had significantly affected the uncertainty of the final simulation results, and many parameters had little or no effect. The SCS curve number was the parameter with significant uncertainty impact on runoff, sediment, organic N, nitrate and TP, and it showed that the runoff process was mainly responsible for the uncertainty of non-point source pollution load. The uncertainty of sediment was the biggest among the five model output results described above. MC results indicated that neglecting the parameter uncertainty of the model would underestimate the non-point source pollution load, and that the relationship between model input and output was non-linear. The uncertainty of non-point source pollution exhibited a temporal pattern: It was greater in summer than in winter. The uncertainty of runoff was smaller compared to that of sediment, organic N, nitrate, and TP, and the source of uncertainty was mainly affected by parameters associated with runoff.
非点源污染的产生和形成具有很大的不确定性，这种不确定性使得污染监测和控制非常困难。了解影响非点源污染不确定性的主要参数对于为控制措施的规划和设计提供依据是必要的。在本研究中，采用了三种方法利用土壤和水资源评估工具（SWAT）进行参数不确定性分析。基于Morris筛选法的参数敏感性分析结果，选择了对径流、泥沙、有机氮、硝酸盐和总磷（TP）影响最大的10个参数进行进一步的不确定性分析。采用一阶误差分析（FOEA）和蒙特卡罗方法（MC）分析参数不确定性对模型输出的影响。FOEA结果表明，只有少数参数对最终模拟结果的不确定性有显著影响，许多参数影响很小或没有影响。SCS曲线数是对径流、泥沙、有机氮、硝酸盐和TP的不确定性影响显著的参数，这表明径流过程是造成非点源污染负荷不确定性的主要原因。在上述五个模型输出结果中，泥沙的不确定性最大。MC结果表明，忽略模型的参数不确定性会低估非点源污染负荷，且模型输入与输出之间的关系是非线性的。非点源污染的不确定性呈现出时间模式：夏季大于冬季。与泥沙、有机氮、硝酸盐和TP相比，径流的不确定性较小，其不确定性来源主要受与径流相关的参数影响。
