Parameter uncertainty analysis of the non-point source pollution in the Daning River watershed of the Three Gorges Reservoir Region, China.
Parameter uncertainty analysis of the non-point source pollution in the Daning River watershed of the Three Gorges Reservoir Region, China.
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DOI：
10.1016/j.scitotenv.2008.06.009
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发表时间：
2008-11
期刊：
影响因子：
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通讯作者：
Zhenyao Shen;Qian Hong;Hong Yu;Ruimin Liu
中科院分区：
文献类型：
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作者：
Zhenyao Shen;Qian Hong;Hong Yu;Ruimin Liu
非点源污染的产生和形成具有很大的不确定性，这种不确定性给污染的监测和控制带来了很大的困难。了解影响非点源污染不确定性的主要参数是必要的，为规划和设计控制措施提供依据。本研究采用三种方法对土壤水资源评价工具（SWAT）中的参数进行不确定性分析。根据Morris筛选法的参数敏感性分析结果，选取了对径流、泥沙、有机氮、硝态氮和总磷影响最大的10个参数进行不确定性分析。采用一阶误差分析（FOEA）和蒙特卡罗方法（MC）分析了参数不确定性对模型输出的影响。FOEA结果表明，只有少数参数显着影响最终模拟结果的不确定性，和许多参数的影响很小或没有。SCS曲线数是对径流、沉积物、有机氮、硝酸盐和TP影响显著的不确定性参数，表明径流过程是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，忽略模型参数的不确定性会低估非点源污染负荷，模型输入与输出之间存在非线性关系。非点源污染的不确定性呈现出夏季大于冬季的时间模式。径流量的不确定性小于泥沙、有机氮、硝态氮和总磷的不确定性，其不确定性来源主要受径流相关参数的影响。
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.