| Autor: |
Wang, Qiqing, Lin, Yuxiang, Li, Wenping, Yu, Xiaoyang, Zhang, Yong |
| Zdroj: |
Arabian Journal of Geosciences; Feb2022, Vol. 15 Issue 3, p1-11, 11p |
| Abstrakt: |
With the gradual increase in coal mining depth in China, the threat of floor water disaster in coal mines is also increasing. The risk assessment of floor water inrush is the key to the prevention and control of floor water disaster. The purpose of this study was to evaluate and compare the results obtained from the certainty factor (CF) and logistic regression (LR) models applied for estimating water-inrush risk from coal floor in Xintaoyang coal mine of Feicheng City, China. First, the geological and hydrogeological conditions of the study area were analyzed, and the distribution of floor water-inrush points during mining was collected and counted. Then, a total of 38 water-inrush points were randomly divided using a ratio of 70/30 for training and validation of the two methods. Five water-inrush influencing factors, including thickness of aquiclude, hydraulic pressure, water abundance, distance to fault, and distance to intersections and endpoints of fault, were considered. Water-inrush risk maps were produced for each of the two methods. Risk maps were verified and compared using the area under the curve (AUC) method. The validation results showed that the success rate of CF model (AUC = 78.20%) was slightly higher than that of the LR model (AUC = 75.20%). Moreover, it was found that the prediction rate of the CF model (AUC = 78.99%) was slightly higher than that of the LR model (AUC = 74.32%). The water-inrush risk maps produced from this study were successful and can be useful for guiding the mining. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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