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Mining-induced Environmental Engineering Geological Pattern Zoning In Yushen Coal Mining Area,Northern Shaanxi

Posted on:2018-06-04Degree:MasterType:Thesis
Country:ChinaCandidate:Y L WuFull Text:PDF
GTID:2310330539975265Subject:Geological Engineering
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With the depletion of coal resources in the mining area of eastern China,the contradiction between the central resources and environmental constraints is intensifying.The focus of coal resources development in China is quickly transferred to the western which are arid and semi-arid areas and the ecological environment is fragile.The northwest region of China is rich in coal resources,but it has shallow burial depths and thick coal seams.Large-scale development of coal resources is more sensitive and violent to the surface of ecological environment,and easily leads to aquifer damage,shallow surface water loss,surface vegetation death and a series of ecological environment problems,triggering deterioration of engineering geological environment.Therefore,the study on the environmental engineering geological model and its division of water-preserved mining has important theoretical and practical significance to the protection of water resources and the green development of coal in the ecological fragile area,western China.In this paper,the Yushen mining area in northern Shaanxi was selected as a case,the data of production area,exploration data,field data and field observation data,meteorological hydrology and so on,were collected and organized.On this basis,the theoretical analysis was carried out to systematically analyze the geological and hydrogeological condition.To obtain permeability coefficient of clay layer after mining,the in situ permeability test was implemented;According to the influence of coal mining on groundwater and ecological environment,the environmental engineering geological pattern of water-preserved mining was divided into four types: environmental catastrophe,environmental gradual deterioration,environmental gradual recovery and environment friendly,and put forward the preliminary theory and method to determine the threshold value method.Through the collection and statistics of 528 drilling data in the study area,the main influencing factors of engineering geological environment were drawn by using GIS software,and the relationship between the main factors affecting water resources caused by coal mining and engineering geological environment was analyzed.Eight main influencing factors of engineering geological environment and its quantitative indicators were comprehensive identified as follows: The depth of water level,the thickness of the sandstone layer,the thickness of the loess,the thickness of the bedrock,the thickness of the coal seam,the distance between water and coal seam,and the precipitation.BP artificial neural network(ANN)method was used to establish multivariate information comprehensive evaluation model of engineering geological environment.The environmental engineering geological pattern of the study area was mapping and predicted.What's more,the correctness of the modeling of the evaluation model was verified by modeling samples,and the accuracy of the model application was verified by verifying samples.The results show that the area of environmental catastrophe is about 1132.37 km2,accounting for 20.68%;The area of environmental gradual deterioration is about 879.94 km2,accounting for 16.07%;The area of environmental gradual recovery is about 2063.24 km2,accounting for 37.68%;The area of environment-friendly is about 1400.14 km2,accounting for 25.57%.Finally,suggestions for the next coal mining under different environmental engineering geological pattern were put forward.The research results provide a scientific basis for solving the problem of environmental engineering geological problems caused by the destruction of superficial water resources in the area of coal mining,which is of great significance to realize the successful development and green development of large coal bases in the fragile areas of northern Shaanxi.
Keywords/Search Tags:environmental engineering geological pattern, water-preserved mining, zoning prediction, BP neural network, ecological fragile region
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