Abstract
An algorithm has been developed that allows the processing of experimental data that are included in the external monitoring database of the Tunguska groundwater deposit. The problem of groundwater quality deterioration due to river filtration is exacerbated during severe floods. In the work, the selection of mathematical methods for solving the problems of simulation modeling is performed. The possibility of applying the methods of k-means cluster analysis, tree clustering and principal component analysis to extract similar objects from experimental data is shown. Mathematical methods are used to identify patterns and assess the impact of floods on the Amur river on the quality of groundwater in the Tunguska field, from the standpoint of multivariate analysis. The results of using the algorithm are presented on the example of a sample from the database on the content of aromatic compounds in groundwater samples from wells and the Penzenskaya Protoka. It was established that the Penzenskaya Protoka is isolated by indicators of the content of organic compounds, and the wells are grouped by the year of sampling, which indicates significant differences in the content of aromatic compounds in groundwater in the river filtration zone. The hypothesis of a significant impact of the 2013 flood on the Amur river was indirectly confirmed on the quality of groundwater.
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