基于GBNP模型的新安江上游流域非点源污染模拟

Simulation of non-point source pollution in the upper basin of Xin'anjiang catchment using GBNP model

流域非点源污染的监测十分困难,因此数值模拟是定量研究流域非点源污染的主要方法。本文采用基于地貌特征的分布式流域非点源污染模型GBNP(Geomorphology-Based Nonpoint source Pollution model),模拟了新安江上游流域2001—2010年的径流过程和非点源污染物的迁移过程。模型参数的率定与验证结果显示,月径流的Nash效率系数多在0.8以上,确定性系数R2都大于0.9;渔梁和屯溪两个测站的月泥沙负荷的Nash效率系数在0.7以上,确定性系数在0.9以上;两个测站总氮(TN)和总磷(TP)Nash效率系数都在0.55以上,确定性系数都大于0.8。结果表明,该模型在研究区适用性良好。基于模拟结果,分析了研究区内TN、TP以及土壤侵蚀量的时空分布特征。结果显示,研究区多年平均TN流失量为6 706.92 t/a,TP流失量为828.45 t/a,土壤侵蚀量为166.62万t/a。模拟期内年际变化和年内变化结果显示,在其他条件不变的情况下,非点源污染的产生与降雨量大小密切相关。对各区县氮磷分布特点分析可知,TN的空间分布主要受土地利用类型的影响,TP的空间分布主要受土壤侵蚀量的影响。

It’s very difficult to monitor non-point source pollution in a watershed,thus the numerical simu？lation has become the main method for its quantitative research. In this paper,the authors use GBNP（Geo？morphology-Based Nonpoint source Pollution model）model, which bases on geomorphological features, to simulate the process of runoff and non-point source pollution in the upper basin of the Xin’anjiang catch？ment from the year of 2000 to 2010. Considering the monthly discharge,most of the Nash efficiency coeffi？cients are greater than 0.8 and deterministic coefficient are above 0.9;Nash efficiency coefficient and deter？ministic coefficient of monthly sediment load in Tunxi and Yuliang are above 0.7 and 0.9;as for total nitro？gen （TN） and total phosphorus （TP） in these two gauges, Nash efficiency coefficient is more than 0.55 and deterministic coefficient is greater than 0.8. All of them indicate that the model is suitable in the study area. According to the results, the authors analyze the temporal and spatial distribution of sediment, TN and TP. The results show that the annual mean loading of TN is 6,706.92 t/a, and 828.45 t/a for TP and 1,666.2×10^3 t/a for the amount of soil erosion. According to the results of the interannual and seasonal variations,the generation of nonpoint source pollution is closely related to precipitation in case of other con？ditions unchanged. The spatial distribution of TN is mainly influenced by the land use types, and spatial distribution is mainly affected by soil erosion of TP.