State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, P.R. China.
Sci Total Environ. 2010 Mar 15;408(8):1971-8. doi: 10.1016/j.scitotenv.2009.12.007. Epub 2009 Dec 24.
Land use type is one of the most important factors that affect the uncertainty in non-point source (NPS) pollution simulation. In this study, seventeen sensitive parameters were screened from the Soil and Water Assessment Tool (SWAT) model for parameter uncertainty analysis for different land use types in the Daning River Watershed of the Three Gorges Reservoir area, China. First-Order Error Analysis (FOEA) method was adopted to analyze the effect of parameter uncertainty on model outputs under three types of land use, namely, plantation, forest and grassland. The model outputs selected in this study consisted of runoff, sediment yield, organic nitrogen (N), and total phosphorus (TP). The results indicated that the uncertainty conferred by the parameters differed among the three land use types. In forest and grassland, the parameter uncertainty in NPS pollution was primarily associated with runoff processes, but in plantation, the main uncertain parameters were related to runoff process and soil properties. Taken together, the study suggested that adjusting the structure of land use and controlling fertilizer use are helpful methods to control the NPS pollution in the Daning River Watershed.
土地利用类型是影响非点源（NPS）污染模拟不确定性的最重要因素之一。本研究从土壤和水评估工具（SWAT）模型中筛选了 17 个敏感参数，用于分析中国三峡库区大宁河流域不同土地利用类型的参数不确定性。采用一阶误差分析（FOEA）方法分析了三种土地利用类型（人工林、森林和草地）下参数不确定性对模型输出的影响。本研究选择的模型输出包括径流量、泥沙产量、有机氮（N）和总磷（TP）。结果表明，三种土地利用类型下参数的不确定性不同。在森林和草地中，NPS 污染的参数不确定性主要与径流过程有关，但在人工林中，主要的不确定参数与径流过程和土壤特性有关。总的来说，该研究表明，调整土地利用结构和控制肥料使用是控制大宁河流域 NPS 污染的有效方法。
