Abstract
Mining-induced water inrush is a sudden and destructive underground disaster caused by a mining disturbance. This disaster occurs frequently in the northern region of Shaanxi province in China due to overburden fractures in shallow seam mining, which pose a great threat to residents’ safety. It is therefore essential to construct an accurate prediction model. This study first applies selection hierarchy analysis to the main controlling factors of roof water inrush to study their weights using an analytic hierarchy process (AHP) including five factors: surface water catchment features, wateriness of the aquifer, water-resistant characteristics of aquiclude, combined influence of overburden, and mining disturbance characteristics. The grey relational analysis (GRA) method is used to calculate the correlation degree of each water inrush. The AHP-GRA method presents a comprehensive evaluative model combining the advantages of both approaches to analyze mining safety. Qualitative and quantitative indicators of the roof water inrush prediction model in shallow seam mining are established. Secondly, risk prediction of roof water inrush points and comprehensive water inrush is determined using engineering examples from the Hanjiawan coal mine. Results indicate that during safety mining, water inflow data are consistent with our prediction, thereby substantiating the model’s accuracy and providing a new method for predicting roof water inrush in shallow seam mining.
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This study was supported by the National Natural Science Foundation of China (5147173, 51774229). The agency’s funding is gratefully acknowledged.
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Zhang, J., Yang, T. Study of a roof water inrush prediction model in shallow seam mining based on an analytic hierarchy process using a grey relational analysis method. Arab J Geosci 11, 153 (2018). https://doi.org/10.1007/s12517-018-3498-2
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DOI: https://doi.org/10.1007/s12517-018-3498-2