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预测密歇根湖南岸35公里范围内海滩大肠杆菌浓度的沿海策略。

Coastal strategies to predict Escherichia coli concentrations for beaches along a 35 km stretch of Southern Lake Michigan.

作者信息

Nevers Meredith B, Whitman Richard L

机构信息

U.S. Geological Survey, Great Lakes Science Center, 1100 N. Mineral Springs Road, Porter, Indiana 46304, USA.

出版信息

Environ Sci Technol. 2008 Jun 15;42(12):4454-60. doi: 10.1021/es703038c.

Abstract

To understand the fate and movement of Escherichia coli in beach water, numerous modeling studies have been undertaken including mechanistic predictions of currents and plumes and empirical modeling based on hydrometeorological variables. Most approaches are limited in scope by nearshore currents or physical obstacles and data limitations; few examine the issue from a larger spatial scale. Given the similarities between variables typically included in these models, we attempted to take a broader view of E. coli fluctuations by simultaneously examining twelve beaches along 35 km of Indiana's Lake Michigan coastline that includes five point-source outfalls. The beaches had similar E. coli fluctuations, and a best-fit empirical model included two variables: wave height and an interactive term comprised of wind direction and creekturbidity. Individual beach R2 was 0.32--0.50. Data training-set results were comparable to validation results (R2 = 0.48). Amount of variation explained by the model was similar to previous reports for individual beaches. By extending the modeling approach to include more coastline distance, broader-scale spatial and temporal changes in bacteria concentrations and the influencing factors can be characterized.

摘要

为了解大肠杆菌在海滩水体中的归宿和移动情况,已开展了大量建模研究,包括对水流和羽流的机理预测以及基于水文气象变量的经验建模。大多数方法在范围上受到近岸水流、物理障碍物和数据限制的制约;很少有研究从更大的空间尺度审视该问题。鉴于这些模型中通常包含的变量之间存在相似性,我们试图通过同时考察印第安纳州密歇根湖沿岸35公里范围内的12个海滩(包括5个点源排放口),更全面地了解大肠杆菌的波动情况。这些海滩的大肠杆菌波动情况相似,一个最佳拟合经验模型包含两个变量:波高以及由风向和溪流浊度组成的交互项。各个海滩的R2为0.32 - 0.50。数据训练集结果与验证结果相当(R2 = 0.48)。该模型解释的变异量与之前关于单个海滩的报告相似。通过扩展建模方法以纳入更多海岸线距离,可以表征细菌浓度和影响因素在更广泛尺度上的时空变化。

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