首页> 外文期刊>Journal of Hydrology >Uncertainty assessment in baseflow nonpoint source pollution prediction: The impacts of hydrographic separation methods, data sources and baseflow period assumptions
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Uncertainty assessment in baseflow nonpoint source pollution prediction: The impacts of hydrographic separation methods, data sources and baseflow period assumptions

机译:基础流非点源污染预测中的不确定性评估:水文分离方法,数据源和基流期假设的影响

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Effective management of nonpoint source (NPS) pollutants requires an understanding of their potential surface runoff and baseflow pathways. In this study, an integrated method was developed for separating baseflow and surface NPS pollutants at the watershed scale. Then, the uncertainty of the prediction of baseflow NPS pollutants was explored by comparing four hydrographic separation methods (the United Kingdom Institute of Hydrology (UKIH), the Lyne-Hollick (LH) method, the Eckhardt (ECK) method and the Soil and Water Assessment Tool (SWAT)), three data sources (monitoring data, SWAT and the LOADEST model) and two baseflow period assumptions. A real case study was performed in a typical catchment, the Three Gorges Reservoir Area, China. The results showed that the baseflow annually contributed 30.1% and 23.0% of the total nitrogen (TN) and phosphorus (TP) load, respectively, indicating that baseflow was identified as the key means of transport of NPS pollutants, especially for NPS-N during the dry season. The water quality data source represents the largest uncertainty source in baseflow NPS pollutant estimation, and the simulated baseflow loads of TN and TP were the largest when LOADEST and SWAT were used as water quality data sources, respectively. The baseflow NPS estimations were more uncertain for TN during the non-dry season and TP during the dry season. The results of this study could provide implications for the prediction and management of NPS pollutants at the watershed scale, especially for groundwater-polluted catchments.
机译:有效管理非点源(NPS)污染物需要了解其潜在的表面径流和基流途径。在该研究中,开发了一种综合方法,用于在流域尺度处分离碱流和表面NPS污染物。然后,通过比较四水文分离方法(United Kingdom水文学研究所(Ukih),Lyne-Hollick(LH)方法,Eckhardt(ECK)方法和土壤和水,探讨了基础流动NPS污染物预测的不确定性。评估工具(SWAT)),三个数据源(监控数据,SWAT和最负载最多)和两个基流时期假设。在中国三峡库区的典型集水区进行了一个真正的案例研究。结果表明,碱基流量分别每次占总氮(TN)和磷(TP)载荷的30.1%和23.0%,表明基流被鉴定为NPS污染物的转运关键手段,特别是对于NPS-N旱季。水质数据源代表了BaseFlow NPS污染物估计中的最大不确定性源,并且当最大的SWAT和SWAT分别用作水质数据源时,TN和TP的模拟基流量最大。在干燥季节期间,在非干燥季节和TP期间,基流NPS估计对TN更不确定。本研究的结果可以为流域规模的NPS污染物的预测和管理提供影响,特别是对于地下水污染的集水区。

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