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Evaluation of targeting methods for implementation of best management practices in the Saginaw River Watershed

机译:评估萨吉诺河流域最佳管理实践的目标确定方法

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Increasing concerns regarding water quality in the Great Lakes region are mainly due to changes in urban and agricultural landscapes. Both point and non-point sources contribute pollution to Great Lakes surface waters. Best management practices (BMPs) are a common tool used to reduce both point and non-point source pollution and improve water quality. Meanwhile, identification of critical source areas of pollution and placement of BMPs plays an important role in pollution reduction. The goal of this study is to evaluate the performance of different targeting methods in 1) identifying priority areas (high, medium, and low) based on various factors such as pollutant concentration, load, and yield, 2) comparing pollutant (sediment, total nitrogen-TN, and total phosphorus-TP) reduction in priority areas defined by all targeting methods, 3) determine the BMP relative sensitivity index among all targeting methods. Ten BMPs were implemented in the Saginaw River Watershed using the Soil and Water Assessment Tool (SWAT) model following identification of priority areas. Each targeting method selected distinct high priority areas based on the methodology of implementation. The concentration based targeting method was most effective at reduction of TN and TP, likely because it selected the greatest area of high priority for BMP implementation. The subbasin load targeting method was most effective at reducing sediment because it tended to select large, highly agricultural subbasins for BMP implementation. When implementing BMPs, native grass and terraces were generally the most effective, while conservation tillage and residue management had limited effectiveness. The BMP relative sensitivity index revealed that most combinations of targeting methods and priority areas resulted in a proportional decrease in pollutant load from the subbasin level and watershed outlet. However, the concentration and yield methods were more effective at subbasin reduction, while the stream load method was more effective at reducing pollutants at the watershed outlet. The results of this study indicate that emphasis should be placed on selection of the proper targeting method and BMP to meet the needs and goals of a BMP implementation project because different targeting methods produce varying results.
机译:大湖地区对水质的担忧日益增加,主要是由于城市和农业景观的变化。点源和面源都对大湖地表水造成污染。最佳管理实践(BMP)是用于减少点和非点源污染并改善水质的常用工具。同时,确定关键的污染源区域和BMP的位置在减少污染中起着重要的作用。这项研究的目的是在以下方面评估不同目标方法的性能:1)根据污染物浓度,负荷和产量等各种因素确定优先区域(高,中和低),2)比较污染物(沉积物,总量)氮-总氮和总磷-总磷)的降低是由所有靶向方法确定的,3)确定了所有靶向方法中BMP的相对敏感性指数。确定重点地区后,使用土壤和水评估工具(SWAT)模型在萨吉诺河流域实施了十个BMP。每种目标确定方法都根据实施方法选择了不同的高优先领域。基于浓度的靶向方法在减少TN和TP方面最有效,可能是因为它选择了BMP实施的最高优先领域。子流域负荷确定方法最有效地减少了沉积物,因为它倾向于选择大型,高度农业化的子流域来实施BMP。实施BMP时,通常以天然草和梯田最为有效,而保护性耕作和残留物管理的效果有限。 BMP相对敏感度指数显示,靶向方法和优先区域的大多数组合导致了从流域水平和集水区出口的污染物负荷成比例下降。然而,浓度和产量法在减少流域的流域方面更有效,而流负荷法在减少流域出口处的污染物方面更有效。这项研究的结果表明,应强调选择适当的定位方法和BMP,以满足BMP实施项目的需求和目标,因为不同的定位方法会产生不同的结果。

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