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Parameter Uncertainty Analysis Of The Non-point Source Pollution In The Daning River Watershed Of The Three Gorges Reservoir Region, China

机译:三峡库区大宁河流域非点源污染的参数不确定度分析。

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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.
机译:面源污染的产生和形成涉及很大的不确定性,并且这种不确定性使得污染的监控非常困难。必须了解影响面源污染不确定性的主要参数,才能为控制措施的规划和设计提供基础。在这项研究中,采用了三种方法通过土壤和水评估工具(SWAT)进行参数不确定性分析。根据Morris筛选方法进行参数敏感性分析的结果,选择了对径流,沉积物,有机氮,硝酸盐和总磷(TP)影响最大的十个参数,以进行进一步的不确定性分析。一阶误差分析(FOEA)和蒙特卡洛方法(MC)用于分析参数不确定性对模型输出的影响。 FOEA结果表明,只有少数几个参数显着影响了最终模拟结果的不确定性,而许多参数几乎没有影响。 SCS曲线数是影响径流,沉积物,有机氮,硝酸盐和总磷的重要不确定性参数,表明径流过程是造成面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面源污染负荷,并且模型输入与输出之间的关系是非线性的。面源污染的不确定性表现出时间格局:夏季大于冬季。与泥沙,有机氮,硝酸盐和总磷相比,径流的不确定性要小,不确定性的来源主要受与径流有关的参数的影响。

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