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Water Quality of Inflows to the Everglades National Park over Three Decades (1985–2014) Analyzed by Multivariate Statistical Methods

机译:多元统计方法分析三个十年(1985-2014年)大沼泽国家公园的入水水质

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摘要

The Everglades, a vast subtropical wetland, dominates the landscape of south Florida and is widely recognized as an ecosystem of great ecological importance. Data from seven inflow sites to the Everglades National Park (ENP) were analyzed over three decades (1985–2014) for temporal trends by the STL (integrated seasonal-trend decomposition using LOESS) method. A cluster analysis (CA) and principal component analysis (PCA) were applied for the evaluation of spatial variation. The results indicate that the water quality change trend is closely associated with rainfall. Increasing rainfall results in increasing flow and thus, decreasing concentrations of nitrogen and phosphorus. Based on 10 variables, the seven sampling stations were classified by CA into four distinct clusters: A, B, C, and D. The PCA analysis indicated that total nitrogen (TN) and total phosphorus (TP) are the main pollution factors, especially TN. The results suggest that non-point sources are the main pollution sources and best management practices (BMPs) effectively reduce organic nitrogen. However, TN and TP control is still the focus of future work in this area. Increasing the transfer water quantity can improve the water quality temporarily and planting submersed macrophytes can absorb nitrogen and phosphorus and increase the dissolved oxygen (DO) concentration in water, continuously improving the water quality.
机译:大沼泽地是广阔的亚热带湿地,在佛罗里达州南部占主导地位,被广泛认为是具有重要生态意义的生态系统。通过STL(使用LOESS的综合季节性趋势分解)方法,分析了三个十年(1985-2014年)从七个流入大沼泽国家公园的流量数据的时间趋势。应用聚类分析(CA)和主成分分析(PCA)评估空间变化。结果表明,水质变化趋势与降雨密切相关。降雨增加导致流量增加,因此氮和磷的浓度降低。根据CA的七个变量,将七个采样站分为四个不同的集群:A,B,C和D。PCA分析表明,总氮(TN)和总磷(TP)是主要污染因子,尤其是TN。结果表明,面源污染是主要的污染源,最佳管理实践(BMP)可有效减少有机氮。但是,TN和TP控制仍然是该领域未来工作的重点。增加输水量可以暂时改善水质,种植沉水植物可以吸收氮和磷并增加水中的溶解氧(DO)浓度,从而不断改善水质。

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