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郑春阳, 陈孝兵, 袁 越, 熊玉龙, 方向元.洪水前后新安江源区河流氮素时空分布对比研究水资源与水工程学报[J].,2020,31(6):47-53
洪水前后新安江源区河流氮素时空分布对比研究
Temporal and spatial distribution characteristics of Nitrogen in the headwaters of Xin’anjiang Watershed: A comparison study between the pre-flooding and post-flooding seasons
  
DOI:10.11705/j.issn.1672-643X.2020.06.08
中文关键词:  洪水  源区河流  氮素  时空分布  新安江
英文关键词:flood  headwaters  nitrogen  temporal and spatial distribution  Xin’anjiang River
基金项目:国家自然科学基金项目(41771033、41401014);中央高校基本科研业务费专项资金项目(B200202159)
作者单位
郑春阳1, 陈孝兵1, 袁 越2, 熊玉龙1, 方向元1 (1.河海大学 水利水电学院 江苏 南京 210098 2.河海大学 水文水资源学院 江苏 南京 210098) 
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中文摘要:
      针对源区河流氮素时空分布规律,选择位于安徽省休宁县境内上溪口地区新安江源头段作为试验研究对象,通过野外采样、水质监测和统计分析方法,研究试验区域洪水前后各项监测指标的时空分布特征及其影响因素,揭示洪水对新安江源区河流氮素的影响。结果表明:流域水体总氮浓度沿水流路径逐渐增加;洪水后总氮、氨氮和硝氮浓度比洪水前均有所增大,洪水期雨水对流域的氮素进行了“冲刷”;相关性分析表明洪水前硝氮和总氮受植被影响较大,洪水后硝氮与汇水面积相关,总氮浓度受高程、坡度和地质等因素影响;所构建的预测模型能够较好地预测洪水前硝氮和总氮以及洪水后氨氮和硝氮的分布。
英文摘要:
      The headwaters of Xin’anjiang in Shangxikou area, Xiuning County, Anhui Province was selected as the study site to investigate the temporal and spatial distribution of nitrogen in the source area. Through field sampling, water quality monitoring and statistical analysis, the temporal and spatial distribution characteristics of various monitoring indexes and their influencing factors in pre-flooding and post-flooding seasons were studied, and the influence of flood on river nitrogen dynamics in the source area of Xin’anjiang River was revealed. The results show that the total nitrogen concentration increases gradually along the water flow path. Compared with pre-flooding season, the concentration of total nitrogen, ammonia nitrogen and nitrate nitrogen increased in post-flooding season. During the flood period, the rainwater “scoured off” the nitrogen in the watershed. The correlation analysis shows that nitrate and total nitrogen are greatly affected by vegetation in pre-flooding season. The concentration of nitrate nitrogen is related to the watershed area and the total nitrogen concentration is affected by elevation, slope and geology in post-flooding season. The regression models performs well in the prediction of nitrate and total nitrogen concentrations in pre-flooding season and that of ammonia and nitrate nitrogen concentrations in post-flooding season.
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