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首页> 外文期刊>Oceanographic Literature Review >Using soil erosion to locate nonpoint source pollution risks in coastal zones: A case study in the Yellow River Delta,China
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Using soil erosion to locate nonpoint source pollution risks in coastal zones: A case study in the Yellow River Delta,China

机译:利用土壤侵蚀在沿海地区定位非点源污染风险:中国黄河三角洲的案例研究

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Soil erosion contributes greatly to nonpoint source pollution (NSP). We built a coastal NSP risk calculation method (CNSPRI) based on the Revised Universal Soil Loss Equation (RUSLE) and geospatial methods. In studies on the formation and transport of coastal NSP, we analysed the pollution impacts on the sea by dividing subbasins into the sea and monitoring the pollutant flux. In this paper, a case study in the Yellow River Delta showed that the CNSPRI could better predict the total nitrogen (TN) and total phosphorus (TP) NSP risks. The value of the soil erodi-bility factor (K) was 0.0377 t h·MJ~(-1) mm~(-1), indicating higher soil erodibility levels, and presented an increased trend from the west to the east coast. The NSP risk also showed an increased trend from west to east, and the worst status was found near the Guangli River of the south-eastern region. The contributions of the seven influencing factors to CNSPRI presented an order of vegetation cover > rainfall erosivity > soil content > soil erodibility > flow > flow path > slope. The different roles of source and sink landscapes influenced the pollutant outputs on a subbasin scale. Arable land and saline-alkali land were the two land-use types with the greatest NSP risks. Therefore, in coastal zones, to reduce NSP output risks, we should pay more attention to the spatial distribution of vegetation cover, increase its interception effect on soil loss, and prioritize the improvement of saline-alkali land to reduce the amount of bare land.
机译:土壤侵蚀有助于极大的源污染(NSP)。我们基于修订后的通用土壤丢失方程(风格)和地理空间方法建立了一种沿海NSP风险计算方法(CNSPRI)。在关于沿海NSP的形成和运输的研究中,我们通过将亚缺失分析到海中并监测污染物通量来分析对海洋的污染影响。在本文中,在黄河三角洲的案例研究表明,CNSPRI可以更好地预测总氮(TN)和总磷(TP)NSP风险。土壤侵蚀性因子(K)的价值为0.0377 T H·MJ〜(-1)mm〜(-1),表明土壤腐蚀水平较高,并提出了西部到东海岸的趋势。 NSP风险也表现出从西向东增加的趋势,最严重的地位是在东南部地区的广场附近找到。七种影响因素对CNSPRI的贡献提出了植被覆盖的秩序>降雨侵蚀性>土壤含量>土壤易用>流动>流动路径>斜坡。源和水槽景观的不同作用影响了子巴西稳定的污染物产出。耕地和盐水碱土地是两种土地使用类型,最大的NSP风险。因此,在沿海地区,为了减少NSP输出风险,我们应该更加关注植被覆盖的空间分布,提高其对土壤损失的截取影响,并优先于盐碱土地的改善,减少裸陆量。

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    《Oceanographic Literature Review》 |2021年第5期|1090-1090|共1页
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