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基于SWAT模型的流域河道硝酸盐δ15N和δ18O模拟
摘要点击 358  全文点击 106  投稿时间:2017-06-05  修订日期:2017-07-17
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中文关键词  流域  硝酸盐  SWAT模型  同位素  过程模拟
英文关键词  basin  nitrate  SWAT model  isotopic  process simulation
作者单位E-mail
王康 武汉大学水资源与水电工程科学国家重点实验室,武汉 430072 wwangkang@163.com 
冉宁 武汉大学水资源与水电工程科学国家重点实验室,武汉 430072  
林忠兵 武汉大学水资源与水电工程科学国家重点实验室,武汉 430072  
周祖昊 中国水利水电科学研究院水资源研究所,北京 100038  
中文摘要
      为提升流域地表水硝酸盐溯源方法的可靠性,于2013~2015年在釜溪河流域,对流域水文和水质过程进行了连续监测,同步测定了流域内主要污染源和干支流河道硝酸盐δ15N和δ18O.基于SWAT(soil and water assessment tool)模型模拟了陆面水文和河道水文过程中的氨氮(NH4+)和硝酸盐(NO3-)迁移转化过程,在此基础上,耦合河道中硝酸盐15N和18 O掺混、转化和分馏机制,发展了流域河道硝酸盐δ15N和δ18O模拟方法.结果表明,河道中硝酸盐δ15N和δ18O主要受流域内污染源以及不同水文期径流条件变化的影响,不同污染源同位素掺混过程对于同位素丰度变化的贡献率为82.74%,氮素转化过程中同位素分馏的贡献率为16.26%,SWAT模拟NH4+和NO3-浓度偏差对δ15N和δ18O模拟误差的影响为10.44%.由于降雨中硝酸盐δ18O的变化范围显著地超过δ15N的变化范围,以及河道硝酸盐18 O来源复杂性,δ18O模拟误差平均较δ15N偏大18.72%.所提出的方法模拟河道硝酸盐的δ15N和δ18O结果的系统误差和偏差小于10%和15%.所提出的流域河道硝酸盐δ15N和δ18O模拟方法具有明确的物理意义,为河道氮素正向溯源提供了方法支撑.
英文摘要
      To improve the reliability of methods to trace surface water pollutants in river basins, hydrological and water quality processes in the Fuxi River Basin were continuously monitored from 2013 to 2015, and the main pollution sources in the watershed and δ15N as well as δ18O in the rivers were measured simultaneously. The Soil and Water Assessment Tool (SWAT) model was used to simulate the NH4+ and NO3- migration processes in the hydrological processes of the land surface and rivers. On this basis, the processes of mixing, transformation, and fractionation of δ15N and δ18O in NO3- were coupled, and the simulation methods of δ15N and δ18O in the rivers were developed. The results showed that δ15N and δ18O in the rivers were mainly affected by the pollution sources in the river basin and the variation in runoff conditions during different hydrological periods. The contribution of the mixing process of different isotopes to the isotope abundance was 82.74%. The contribution of isotope fractionation in the process of nitrogen conversion was 16.26%. The influence of NH4+ and NO3- concentration deviation from the SWAT simulation on the simulation errors of δ15N and δ18O was 10.44%. The δ18O simulation errors were 18.72% larger than those of δ15N because of the higher variation range of δ18O in rainfall and the complexity of δ18O. The systematic errors and deviations of the simulated δ15N and δ18O results using the proposed method were less than 10% and 15%, respectively. The simulation method of δ15N and δ18O in the river basin has a clear physical meaning, which provides a useful approach for tracing nitrogen sources in rivers.

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