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Integration of monthly water balance modeling and nutrient load estimation in an agricultural catchment

机译:农业流域每月水量平衡模型和营养物负荷估算的集成

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Non-point sources pollution has become a serious environmental problem in the aquatic systems throughout the world. The Xitiaoxi catchment is located in the southwest of Taihu Basin, contributing large amounts of runoff and associated nutrients to Taihu Lake. Thus, identifying critical non-point sources pollution in this catchment is urgent and essential to control water pollution, improve the water quality, and reduce the pollutants drained into water bodies. The present study integrated a monthly water balance model with the export coefficient model for total nitrogen and total phosphorus loads estimation in the Xitiaoxi catchment in southeastern China. The simulated monthly runoff are in good agreement with the observed streamflow at both Hengtangcun and Fanj-iancun stations with Nash-Sutcliffe coefficients higher than 0.80. The predictions showed reasonable ranges from 1687 to 2046 t/y (2002-2005) for total nitrogen loads, and from 106 to 157 t/y for total phosphorus loads (1999-2007), respectively, which are consistent with the observed values at Hengtangcun. Overall, the monthly export coefficient model coupling monthly water balance simulation to export coefficient model presented both the seasonal dynamics and magnitude for streamflow andnutrients loads, which generally match well with the observations. These findings demonstrate that the proposed model can provide encouraging results and can be used as an efficient tool to identify the pollution sources for planning and management of large-scale agricultural catchment.
机译:面源污染已成为全世界水生系统中严重的环境问题。西条溪流域位于太湖流域的西南部,为太湖贡献了大量径流和相关养分。因此,在该流域识别关键的非点源污染对于控制水污染,改善水质和减少排入水体的污染物是紧急且必不可少的。本研究将月水平衡模型与出口系数模型相结合,用于估算中国东南部西条溪流域的总氮和总磷负荷。 Nash-Sutcliffe系数大于0.80的横塘村站和Fanj-iancun站的模拟月径流量与观测到的水流高度吻合。预测显示总氮负荷的合理范围为1687至2046 t / y(2002-2005),而总磷负荷的合理范围分别为106至157 t / y(1999-2007),与在横塘村。总体而言,月度出口系数模型将月度水平衡模拟与出口系数模型结合起来,显示了流量和养分负荷的季节动态和幅度,这通常与观测值非常吻合。这些发现表明,所提出的模型可以提供令人鼓舞的结果,并且可以用作识别大型农业流域规划和管理污染源的有效工具。

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