An approach for detecting groundwater runoff connectivity using cluster analysis
An approach for detecting groundwater runoff connectivity using cluster analysis
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DOI：
10.1109/smc.2017.8122982
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发表时间：
2017-10
期刊：
影响因子：
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通讯作者：
Xiaojun Kang;Xuguang Zhao;Caixia Guo;Junhua Ding
中科院分区：
文献类型：
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作者：
Xiaojun Kang;Xuguang Zhao;Caixia Guo;Junhua Ding
探测地下水径流连通性对矿山开采和环境保护具有重要意义。然而，传统的基于物理和化学实验的方法既不高效也不有效。实验结果表明，在一个孤立的井中的细菌群落含有独特的DNA序列，而在相连的威尔斯井中的细菌群落具有共同的DNA序列，这在两个孤立的群落中是不期望的。本文对一组威尔斯井的地下水细菌数据进行聚类分析，根据DNA序列分析得到威尔斯井间细菌群落的分布。此外，我们进行了一系列的实验，以显示细菌群落的分布可以指示地下水径流的连通性。聚类结果与传统物理化学实验结果一致。研究表明，细菌群落分布的聚类分析是一种检测地下水径流连通性的有效方法。
Detecting the groundwater runoff connectivity is important for mining and environment protection. However, traditional physical and chemical experiments based approaches are neither efficient nor effective. Experimental results have shown the bacterial community in an isolated well contains unique DNA sequences, and the bacterial communities in connected wells have common DNA sequences that are not expected in two isolated communities. In this paper, we applied a variety of clustering methods to the bacterial data of groundwater that were acquired from a group of wells, to obtain the distribution of the bacterial communities among the wells based on DNA sequences. In addition, we conducted a serials of experiments to show the distribution of the bacterial communities can indicate the groundwater runoff connectivity. The clustering results are consistent to the experimental results of the traditional physical and chemical experiments. The research shows the cluster analysis of the distribution of bacterial communities is an efficient and effective approach for detecting the groundwater runoff connectivity.