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Identifying critical source areas of nonpoint source pollution with SWAT and GWLF

机译:利用SWAT和GWLF识别非点源污染的关键源区域

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Identification of critical source areas (CSAs) (areas contributing most of the pollutants in a watershed) is important for cost-effective implementation of best management practices. Identification of such areas is often done through watershed modeling. Various watershed models are available for this purpose, however it is not clear if the choice (and complexity) of a model would lead to differences in locations of CSAs. The objective of this study was to use two models of different complexity for identifying CSAs. The relatively complex Soil and Water Assessment Tool (SWAT) and the simpler Generalized Watershed Loading Function (GWLF) were used to identify CSAs of sediment and nutrients in the Saugahatchee Creek watershed in east central Alabama. Models were calibrated and validated for streamflow, sediment, total nitrogen (TN) and total phosphorus (TP) at a monthly time scale. While both models performed well for streamflow, SWAT performed slightly better than GWLF for sediment, TN and TP. Sub-watersheds dominated by urban land use were among those producing the highest amount of sediment, TN and TP loads, and thus identified as CSAs. Sub-watersheds with some amount of agricultural crops were also identified as CSAs of TP and TN. A few hay/pasture dominated sub-watersheds were identified as CSAs of TN. The identified land use source areas were also supported by field collected water quality data. A combined index was used to identify the sub-watersheds (CSAs) that need to be targeted for overall reduction of sediment, TN and TP. While many CSAs identified by SWAT and GWLF were the same, some CSAs were different. Therefore, this study concludes that model choice will affect the location of some CSAs.
机译:确定关键源区域(CSAs)(在流域中占大多数污染物的区域)对于以成本效益的方式实施最佳管理做法很重要。通常通过分水岭建模来识别这些区域。有多种分水岭模型可用于此目的,但是尚不清楚模型的选择(和复杂性)是否会导致CSA位置的差异。这项研究的目的是使用两种不同复杂度的模型来识别CSA。相对复杂的土壤和水评估工具(SWAT)和较简单的广义流域负荷函数(GWLF)用于识别阿拉巴马州东部中部Saugahatchee Creek流域的沉积物和养分的CSA。对模型进行校准并针对每月时间尺度上的流量,沉积物,总氮(TN)和总磷(TP)进行验证。尽管两种模型在水流方面均表现良好,但在沉积物,总氮和总磷方面,SWAT的性能略好于GWLF。在城市土地利用占主导地位的次流域中,沉积物,总氮和总磷负荷量最高,因此被确定为CSA。具有一定数量农作物的小流域也被确定为TP和TN的CSA。一些以干草/牧草为主的子流域被确定为TN的CSA。实地收集的水质数据也为确定的土地利用来源地区提供了支持。使用综合指数来确定需要针对总体减少沉积物,总氮和总磷的子流域(CSA)。虽然由SWAT和GWLF识别的许多CSA是相同的,但某些CSA是不同的。因此,本研究得出的结论是,模型选择将影响某些CSA的位置。

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