Prediction of the Height of Fractured Water-Conducting Zone: Significant Factors and Model Optimization

• Published in: Water (Basel) 2023-08, Vol.15 (15), p.2720
• Main Authors: Gu, Linjun, Shen, Yanjun, Wang, Nianqin, Kou, Haibo, Song, Shijie
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; Coal industry; Coal mining; Correlation analysis; Groundwater overdraft; Management; Mineral industry; Mining industry; Physicists; Simulation; Soil erosion; Statistical analysis; Water; Water conservation
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w15152720

Predicting the height of the fractured water-conducting zone (FWCZ) can be challenging due to their significant grey characteristics and the difficulty in scientifically selecting relevant influencing factors. To address this issue, we utilized the Pearson correlation analysis method and the grey entropy correlation analysis method to identify the significant factors and their degree of correlation with the height of FWCZ. Based on this, several constructed models were optimized, and the reliability of the best regression model was verified through parameter inversion analysis. The results indicate that the spatial distribution differences of the main coal mining seams contribute to the complex and variable occurrence conditions of coal seams. This is an important factor that contributes to the significant gray characteristics in predicting the height of FWCZ in the study area. A modeling approach has been proposed for predicting the height of FWCZ. This method is based on analyzing significant factors and conducting a multi-level evaluation of the selected prediction models. The order of correlation between significant influencing factors and the height of FWCZ is as follows: comprehensive hardness of overlying rock > average thickness of sandstone > mining depth > mining height. The results of the multi-level evaluation analysis show that, when using small sample high-quality datasets, the GA-Catboost algorithm has better prediction accuracy compared to the MSR and GA-BP algorithms. The results of the parameter inversion analysis for the GA-Catboost regression prediction model indicate that within the mining height range of 2.5–5.5 m, the ratio of fractured/mining height in the main coal seams is primarily concentrated between 20.45–30.59. In addition, a prediction method was developed to determine the limiting mining height by considering water conservation in coal mining. The relevant research results can provide fundamental theoretical support for ensuring safety in underground production and protecting groundwater in mining areas.