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Estimating Summer Nutrient Concentrations in Northeastern Lakes from SPARROW Load Predictions and Modeled Lake Depth and Volume

机译:根据SPARROW负荷预测和模拟的湖深和水量估算东北湖泊的夏季营养物浓度

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摘要

Global nutrient cycles have been altered by the use of fossil fuels and fertilizers resulting in increases in nutrient loads to aquatic systems. In the United States, excess nutrients have been repeatedly reported as the primary cause of lake water quality impairments. Setting nutrient criteria that are protective of a lakes ecological condition is one common solution; however, the data required to do this are not always easily available. A useful solution for this is to combine available field data (i.e., The United States Environmental Protection Agency (USEPA) National Lake Assessment (NLA)) with average annual nutrient load models (i.e., USGS SPARROW model) to estimate summer concentrations across a large number of lakes. In this paper we use this combined approach and compare the observed total nitrogen (TN) and total phosphorus (TN) concentrations in Northeastern lakes from the 2007 National Lake Assessment to those predicted by the Northeast SPARROW model. We successfully adjusted the SPARROW predictions to the NLA observations with the use of Vollenweider equations, simple input-output models that predict nutrient concentrations in lakes based on nutrient loads and hydraulic residence time. This allows us to better predict summer concentrations of TN and TP in Northeastern lakes and ponds. On average we improved our predicted concentrations of TN and TP with Vollenweider models by 18.7% for nitrogen and 19.0% for phosphorus. These improved predictions are being used in other studies to model ecosystem services (e.g., aesthetics) and dis-services (e.g. cyanobacterial blooms) for ~18,000 lakes in the Northeastern United States.
机译:通过使用化石燃料和肥料改变了全球养分循环,从而导致了水生系统养分负荷的增加。在美国,过多的养分已被反复报告为湖泊水质受损的主要原因。设定保护湖泊生态条件的养分标准是一种常见的解决方案。但是,执行此操作所需的数据并不总是很容易获得。一个有用的解决方案是将可用的现场数据(即美国环境保护局(USEPA)国家湖泊评估(NLA))与年均养分负荷模型(即USGS SPARROW模型)相结合,以估算大范围内的夏季浓度湖泊数量。在本文中,我们使用这种组合方法,将2007年国家湖泊评估与东北SPARROW模型预测的东北湖中观测到的总氮(TN)和总磷(TN)浓度进行了比较。我们使用Vollenweider方程将SPARROW预测成功地调整为NLA观测值,Vollenweider方程是一种简单的输入-输出模型,可根据养分负荷和水力停留时间预测湖泊中的养分浓度。这使我们能够更好地预测东北湖泊和池塘夏季总氮和总磷的浓度。平均而言,我们使用Vollenweider模型将氮和磷的预测浓度提高了18.7%,磷提高了19.0%。这些改进的预测已在其他研究中用于为美国东北部约18,000个湖泊的生态系统服务(例如美学)和服务不足(例如蓝藻水华)建模。

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