首页> 中文期刊> 《农业工程学报》 >考虑降水和地形的京津冀水库流域非点源污染负荷估算

考虑降水和地形的京津冀水库流域非点源污染负荷估算

         

摘要

为了研究京津冀地区水库流域非点源污染现状,该文选取京津冀地区17座重要的水源地水库,运用修正的输出系数模型对水库流域非点源总氮(TN,total nitrogen)、总磷(TP,total phosphorus)输出负荷进行估算,结果表明:1)TN与TP负荷量空间分布具有一致性,TN负荷量较大的水库流域,TP负荷量也较大.TN与TP负荷量的平均比值为6.73.2)TN、TP负荷强度具有空间异质性.TN负荷强度为1.04~24.91 t/km2·a,TP负荷强度为0.11~3.89 t/km2·a.唐山、秦皇岛地区水库面临着更大的氮磷污染风险.3)不同污染源对TN负荷贡献率的顺序是土地利用>农村生活>牲畜养殖,对TP负荷贡献率的顺序是农村生活>土地利用>牲畜养殖.4)运用水库营养状态指数(EI,eutrophication index)对模拟结果进行验证.EI指数分别与TN、TP负荷强度呈显著相关关系(r=0.562,P<0.05;r=0.558,P<0.05),表明模拟出的TN、TP负荷与实际情况较符合,模型具有应用潜力.%With the advantages of fewer model parameters, fewer difficulties in obtaining necessary data, and more combinations with geographic information system (GIS), remote sensing (RS) technologies, the export coefficient model (ECM) is an applicable model for estimating non-point source (NPS) pollution loads. Based on the traditional ECM, the model can be improved by considering the impacts of precipitation and topographical factors on NPS pollution. The simulation accuracy of improved ECM (IECM) on NPS pollution is higher and it has been successfully used in China, such as the upper reaches of the Yangtze River basin, the Miyun Reservoir basin, and the Baoxiang River basin in Yunnan Province. Beijing-Tianjin-Hebei region, namely Beijing-Tianjin-Hebei, located in North China, is an economically developed region with a dense population and fast urbanization. There is a serious lack of water resources in this region and the water quality is bad. Seventeen drinking-water reservoirs in Beijing-Tianjin-Hebei region were selected in this study, and the meteorological, topographical, land use, social and economic data of their watersheds in the year of 2010 were collected. The IECM was applied to estimate the loads and intensities of total nitrogen (TN) and total phosphorus (TP) of NPS in the 17 reservoir watersheds, and the sources of TN and TP were also analyzed. The results were as follows: (1) TN and TP load had the same spatial pattern, namely the TN load was large, and the TP load was large too. The average ratio of TN to TP load was 6.73. (2) TN and TP load intensities had obvious spatial heterogeneities. The TN load intensity was 1.04-24.91 t/km2·a, ranging from the minimum value in Yunzhou Reservoir watershed to the maximum value in Taolinkou Reservoir watershed. The TP load intensity was 0.11-3.89 t/km2·a, with the minimum value in Yunzhou Reservoir watershed and the maximum value in Yanghe Reservoir watershed. The TN and TP load intensities were both relatively high in Taolinkou, Yanghe, Daheiting, Qiuzhuang Reservoir watershed, indicating that the reservoirs located in the northeast Beijing-Tianjin-Hebei region (Tangshan City and Qinhuangdao City) had higher risk of nitrogen and phosphorus pollution. (3) Based on the source analysis results, a conclusion could be drawn that the order of the mean contribution to TN load was land use > rural life > livestock, while the order of the mean contribution to TP load was rural life > land use > livestock. Rural life was an important source of both TN and TP load in this region. (4) We used the water eutrophication index (EI) of drinking-water reservoirs which was published by Haihe River Water Conservancy Commission in 2010 to test the modeling results. EI was significantly correlated to TN and TP load intensities. Person correlation analysis was employed and the correlation coefficient between TN load intensity and EI and that between TP load intensity and EI were 0.562 (P<0.05) and 0.558 (P<0.05), respectively. Model test results showed that the IECM has a high application value, and the TN and TP load of NPS can be well estimated by IECM at large watersheds which lack large numbers of measured data of water quality.

著录项

  • 来源
    《农业工程学报》 |2017年第4期|265-272|共8页
  • 作者

    程先; 陈利顶; 孙然好;

  • 作者单位

    中国科学院生态环境研究中心城市与区域生态国家重点实验室,北京 100085;

    中国科学院大学,北京 100049;

    中国科学院生态环境研究中心城市与区域生态国家重点实验室,北京 100085;

    中国科学院生态环境研究中心城市与区域生态国家重点实验室,北京 100085;

  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类 风险评价;
  • 关键词

    水库; 污染; 模型; 非点源; 氮磷; 京津冀地区;

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