Abstract
Groundwater flow into the mine by coal mining, which threatens the safety of coal mine. Therefore, it is necessary to identify the source of the water flowing into the coal mine. Taking binhuang mining area in Shaanxi Province as the research background, the discrimination models of six water inrush sources had been studied. The composition of 256 water samples was determined and the water quality characteristics of 6 water sources were analyzed. Fisher linear discriminant function model was established by selecting 9 indexes of water quality components. By testing the discriminant effect, it is considered that the probability of K1L aquifer misjudging as Q aquifer and surface water is high, and the misjudgment rate is 30.4%. Combined with the analysis of geological conditions, it is considered that K1L aquifer has a good hydraulic connection with Q aquifer and surface water. Aiming at the problem of misjudgment, the neural network analysis model is used, and the misjudgment rate is reduced to 0%.
Highlights
The hydrogeological conditions of coalfields in China are very complex and often threatened by water disasters[1,2,3]
The Binhuang mining area of Huanglong Jurassic Coalfield is located in the southern margin of Ordos Basin and the southwest of Loess Plateau in Northern Shaanxi, which belongs to the Yellow River system
The K1l aquifer misjudged the Quaternary aquifer and surface water, the discrimination rate is as high as 30.4%
Summary
The hydrogeological conditions of coalfields in China are very complex and often threatened by water disasters[1,2,3]. Water disaster affects production and even damages people due to well flooding. Scholars have carried out a large number of research on the discrimination of water inrush sources in coal mines. There are different statistical methods to identify water inrush sources: for example, the distance discrimination method is used to identify water inrush sources, and the fuzzy comprehensive evaluation method is used to identify water inrush sources. A large number of research results have solved the technical problem to a great extent, due to the great difference of groundwater environment in different regions and the different application scope of different methods and data sources, it is necessary to compare different statistical methods and data sources to study the water inrush source discrimination model suitable for the study area
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