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基于BP神经网络方法计算河网区面源负荷

Study on non-point source load in river network based on the BP neural network method

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【作者】 高翔毛献忠

【Author】 Gao Xiang;Mao Xianzhong;Research Center for Environmental Engineering and Management,Graduate School at Shenzhen,Tsinghua University;

【机构】 清华大学深圳研究生院环境工程与管理研究中心

【摘要】 以常州市河网为例,通过监测河网断面水文、水质数据,计算出新澡港河—大湾浜单一河道(29场)及河网(8场)场次降雨面源负荷。采用BP神经网络方法推算出新澡港河—大湾浜单一河道2013年面源总入河负荷。根据该单一河道和河网面源负荷的相关关系,推算河网2013年面源总负荷,其中2013年总氮、氨氮、总磷和COD面源总负荷分别为47.29t、29.13t、3.18t和516.88t。

【Abstract】 The water quality and hydrological condition of the control sections in Xinzaogang River and Dawanbang River(29 times)and the entire river network(8 times)in Changzhou were monitored.The non-point source load entered the Xinzaogang River,the Dawanbang River and the entire river network for each rainfall was also analyzed.Based on the BP neural network model,we predicted the annual non-point source pollutants for a single river of 2013.By analyzing the relationship of the non-point source pollution between a single river and the entire river network,the annual non-point source pollutant loads of 2013 for TN,NH3-N,TP and COD were approximately 47.29 t,29.13 t,3.18 t and 516.88 t,respectively.

【基金】 国家水体污染控制与治理科技重大专项(2012ZX07301-001)
  • 【文献出处】 给水排水 ,Water & Wastewater Engineering , 编辑部邮箱 ,2017年01期
  • 【分类号】TP183;X52
  • 【被引频次】2
  • 【下载频次】180
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