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Identifying non-point source critical source areas based on multi-factors at a basin scale with SWAT

机译:利用SWAT在流域尺度上基于多因素识别非点源关键源区

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The identification of critical source areas (CSAs) is a precondition for non-point source (NPS) pollution control at a basin scale, especially in areas with limited resources. Based on the Soil and Water Assessment Tool (SWAT), nutrient loads coupled with population density and water quality requirements are regarded as multi-factors for CSAs identification in Xiangxi river watershed, the first tributary of the Yangtze River. The results based on the calibrated model found that the subbasins heavily and seriously polluted by nutrient loads were different from the subbasins identified as CSAs, demonstrating integrating socio-economic factors like population density and water quality requirements to identify CSAs is of much necessity. The CSAs occupied 19.7% of the total subbasins, and accounted for 53% total nitrogen loads, 54% total phosphorus loads and 36% of the total population. Considering the model calibration and validation will take a long time as well as data deficiency in some subbasins, the influence of uncalibrated SWAT on CSAs identifications was discussed. The comparative results between CSAs identification with calibrated and uncalibrated SWAT model revealed that model calibration had little effect on nutrients distribution and CSAs locations in the study area. Uncalibrated SWAT model may be applied when the research objective is less related to model calibration. The results will be greatly effective for CSAs identification and NPS pollution control at a basin scale. (C) 2015 Elsevier B.V. All rights reserved.
机译:识别关键源区(CSA)是流域范围内非点源(NPS)污染控制的前提,特别是在资源有限的地区。基于土壤和水评估工具(SWAT),营养负荷与人口密度和水质要求相结合,被认为是长江第一支流湘西河流域的CSAs识别的多因素。基于校准模型的结果发现,受营养负荷严重和严重污染的子流域与确定为CSA的子流域不同,这表明需要综合社会经济因素(如人口密度和水质要求)来确定CSA。 CSA占总流域的19.7%,占总氮负荷的53%,总磷负荷的54%和总人口的36%。考虑到模型的校准和验证将需要很长时间以及某些子盆地的数据不足,因此讨论了未校准的SWAT对CSA识别的影响。通过校准和未校准的SWAT模型对CSA进行识别的比较结果表明,模型校准对研究区域的营养成分分布和CSA位置影响很小。当研究目标与模型校准关系不大时,可以应用未校准的SWAT模型。该结果对流域规模的CSA识别和NPS污染控制将非常有效。 (C)2015 Elsevier B.V.保留所有权利。

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