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Characterisation of spatial variability in water quality in the Great Barrier Reef catchments using multivariate statistical analysis

机译:利用多变量统计分析表征大堡礁流域水质的空间变异性

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Water quality monitoring is important to assess changes in inland and coastal water quality. The focus of this study was to improve understanding of the spatial component of spatial-temporal water quality dynamics, particularly the spatial variability in water quality and the association between this spatial variability and catchment characteristics. A dataset of nine water quality constituents collected from 32 monitoring sites over a 11-year period (2006–2016), across the Great Barrier Reef catchments (Queensland, Australia), were evaluated by multivariate techniques. Two clusters were identified, which were strongly associated with catchment characteristics. A two-step Principal Component Analysis/Factor Analysis revealed four groupings of constituents with similar spatial pattern and allowed the key catchment characteristics affecting water quality to be determined. These findings provide a more nuanced view of spatial variations in water quality compared with previous understanding and an improved basis for water quality management to protect nearshore marine ecosystem.
机译:水质监测对于评估内陆和沿海水质变化非常重要。这项研究的重点是增进对时空水质动力学的空间组成的理解,尤其是水质的空间变异性以及这种空间变异性与集水特征之间的联系。通过多变量技术评估了大堡礁集水区(澳大利亚昆士兰州)在过去11年(2006-2016年)中从32个监测点收集的9种水质成分的数据集。确定了两个集群,它们与流域特征密切相关。两步的主成分分析/因子分析显示了四组具有相似空间格局的组分,并可以确定影响水质的关键集水特征。与以前的理解相比,这些发现为水质的空间变化提供了更为细致入微的观点,并为保护近海海洋生态系统的水质管理提供了改进的基础。

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