文章摘要
任智慧,赵春发,王青青,徐蕴韵,郭加汛,王腊春.复杂流域氮磷污染物输出特征及模拟——以南京市云台山河流域为例[J].农业环境科学学报,2021,40(1):174-184.
复杂流域氮磷污染物输出特征及模拟——以南京市云台山河流域为例
Characteristics and simulation of nitrogen and phosphorus in complex watersheds:A case study in the Yuntaishan River Basin in Nanjing City, China
投稿时间:2020-07-22  
DOI:10.11654/jaes.2020-0853
中文关键词: 复杂流域  氮磷污染  时空分布  污染负荷模拟  输出特征
英文关键词: complex watershed  nitrogen and phosphorus pollution  temporal and spatial distribution  non-point source pollution load simulation  output characteristics
基金项目:南京市水务科技项目(201806)
作者单位E-mail
任智慧 南京大学地理与海洋科学学院, 南京 210023  
赵春发 南京市江宁区水务局, 南京 211100  
王青青 南京大学地理与海洋科学学院, 南京 210023  
徐蕴韵 南京大学地理与海洋科学学院, 南京 210023  
郭加汛 南京大学地理与海洋科学学院, 南京 210023  
王腊春 南京大学地理与海洋科学学院, 南京 210023 wang6312@263.net.cn 
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中文摘要:
      为定量分析复杂流域下垫面氮磷面源污染对流域水环境的影响,研究以南京市云台山河流域为研究对象,结合原位观测,并构建降雨-径流水文模型以及面源污染负荷模型,对云台山河总氮(TN)、总磷(TP)浓度的时空变化特征以及流域不同下垫面TN面源污染产生及入河特征进行分析。水质监测结果表明:云台山河TN平均浓度为5.1 mg·L-1,各河段TN均超Ⅳ类水质标准。TP平均浓度为0.14 mg·L-1,仅阳山河支流超Ⅳ类水质标准。TN浓度整体表现为下游高于上游,旱季高于雨季。TP浓度空间变化不明显,年内变化缓慢,表现为逐渐下降的趋势。水文模型及面源污染负荷模型对TN的模拟效果较好,模拟结果表明云台山河流域TN年产生量为581.1 t,主要来自农田径流与农村生活源,胜利河片区和主干流片区是TN污染物的主要来源区域。流域TN年入河量为187.8 t,占面源产生量的32%。受土地利用方式及城镇化程度影响,不同片区TN面源污染入河量呈现明显的空间差异性。为达到目标水质,流域TN需削减量为137.3 t·a-1,其中农田径流与农村生活污染需削减量分别为55.5 t·a-1和39.7 t·a-1。研究表明在流域水文资料较缺乏的情况下,结合原位观测与模型构建,可实现流域面源污染物负荷的定量估算。
英文摘要:
      To quantitatively evaluate the impact of nitrogen and phosphorus from non-point source pollution on the water environment of a complex watershed, the Yuntaishan River Basin in Nanjing City was considered a case study. A rainfall-runoff hydrological model and nonpoint source pollution load model was constructed in combination with in-situ observations. The temporal and spatial characteristics of the total nitrogen(TN)and total phosphorus(TP)concentration in Yuntaishan River were analyzed, as well as the inflow characteristics of TN non-point source pollution on different underlying surfaces of the basin. The monitoring results showed that the average concentration of TN was 5.1 mg·L-1, exceeding the Grade Ⅳ water quality standards. The average concentration of TP was 0.14 mg·L-1, and only the tributary of Yangshan River exceeded the Grade Ⅳ water quality standard. The overall TN concentration in the downstream region was higher than that in the upstream region, and higher in the dry season than in the rainy season. The spatial change in TP concentration was not obvious, with a slow downward trend throughout the year. The hydrological model and non-point source pollution load model had a good simulation effect on TN. The simulation results showed that the annual TN output in the basin was 581.1 t, mainly from farmland runoff and rural living pollution sources. Shengli River and the main stream areas were the key sources of TN pollutants. The annual amount of TN pollutant in the Yuntaishan River basin was 187.8 t, accounting for 32% of non-point source production. Land use and urbanization affected the amount of nitrogen pollutant in the rivers in different areas, showing significant spatial differences. To achieve the target water quality, TN needs to be reduced by 137.3 t·a-1 in the watershed, and farmland runoff/rural pollution needs to be controlled. This study showed that in the absence of hydrological data, the combination of in-situ observations and model construction could achieve the quantitative estimation of non-point source pollutant load in a watershed.
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