| 基于改进输出系数模型的非点源污染评估及关键源区识别:以北运河上游流域为例 |
| 摘要点击 2854 全文点击 807 投稿时间：2022-11-29 修订日期：2023-01-31 |
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| 中文关键词 北运河上游 非点源污染(NSP) 关键源区(CSAs) 输出系数模型(ECM) 累积污染负荷曲线 |
| 英文关键词 upper Beiyun River Basin non-point source pollution(NSP) critical source areas(CSAs) export coefficient model(ECM) cumulative pollution load curve |
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| 中文摘要 |
| 非点源污染对水生态环境威胁极大，定量解析非点源污染空间分布特征和准确识别关键源区是实现其高效精准治理的基础.输出系数模型广泛应用于非点源污染的模拟，但该模型忽略污染物迁移过程中的损失量，需要进一步改进.以北运河上游流域为例，通过对非点源污染物迁移物理过程的模拟，量化产流、产沙和下渗过程中污染物的损失率改进输出系数模型，并分析Johnes、常用和改进输出系数模型的模拟精度，探究3个输出系数模型对非点源污染空间分布特征和关键源区模拟结果的影响.结果表明：①改进输出系数模型模拟误差（-6.79%）明显低于Johnes模型（50.44%）和常用模型（-84.01%），显著提高了非点源污染模拟精度.②不同输出系数模型得到的非点源污染空间分布特征和关键源区存在较大差异，改进的输出系数模型模拟结果更符合流域非点源污染特征.流域非点源污染呈西北部低东南部高的空间特征，城镇用地和耕地是主要污染源.③基于改进输出系数模型确定的流域非点源污染关键源区主要分布在昌平、沙河、史各庄、温泉乡北部和马连洼街道西部等区域，占流域总面积6.71%.研究可为缺资料地区的非点源污染评估和治理提供更有效的工具支撑和科学参考. |
| 英文摘要 |
| Non-point source pollution(NSP) poses a great threat to water ecosystem health. The quantitative estimation of spatial distribution characteristics and accurate identification of critical source areas(CSAs) of NSP are the basis for its efficient and accurate control. The export coefficient model(ECM) has been widely used to assess NSP, but this model should be improved because it ignores pollutant loss in transport processes. In this study, the ECM, which refines the physical transport processes of pollutants through quantifying the loss rate of pollutants in runoff, sediment, and infiltration, was improved to assess NSP and identify CSAs. The simulation accuracy among Johnes ECM, frequent ECM, and improved ECM were analyzed, and the effects of the three models on the simulation results of both spatial distribution characteristics and CSAs were explored. The study showed that:① the simulation error of the improved ECM(-6.79%) was significantly lower than that of the Johnes ECM(50.44%) and the frequent ECM(-84.01%), and this improved ECM increased the simulation accuracy of NSP. ② The spatial distribution characteristics and CSAs of NSP obtained from Johnes, frequent, and improved ECMs were significantly different, and the simulation results of improved ECM were more consistent with the spatial characteristics of NSP in the watershed. The NSP was high in the southeast and low in the northwest of the basin, and the NSP mainly came from urban and cultivated land. ③ Based on the improved ECM, the CSAs of NSP in the basin were mainly distributed in Changping, Shahe, Shigezhuang, the north of Wenquan, and the west of Malianwa Street, accounting for 6.71% of the area. This study can provide an effective tool and scientific reference for the assessment and control of NSP in data-limited regions. |
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