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| DDA-based method for evaluating and predicting groundwater quality in goafs of copper mines |
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Received:January 06, 2022
Revised:January 17, 2022
Accepted:January 20, 2022
Published Online:October 25, 2022
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| DOI： |
| KeyWord:Copper mine goaf;Groundwater quality evaluation; Distance discrimination analysis; Hierarchical prediction |
| Author | Institution |
| Li Yong |
School of land and resources engineering,Kunming University of technology,Kunming;China;Yunnan hubai Environmental Protection Technology Co,Ltd,Kunming;China;School of earth and environment,Anhui University of technology,Huainan;China |
| Cao Guangzhu |
School of land and resources engineering,Kunming University of technology,Kunming |
| Qin Ronggao |
School of land and resources engineering,Kunming University of technology,Kunming |
| Qiu Renmin |
Yunnan hubai Environmental Protection Technology Co,Ltd,Kunming |
| Fan Yingjun |
School of earth and environment,Anhui University of technology,Huainan |
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| Abstract: |
| Carrying out groundwater quality evaluation and classification of groundwater quality are of great significance to the protection and utilization of groundwater resources in mines. According to the "Groundwater Quality Standard" (GB/T 14848-2017), 8 evaluation indicators of total hardness, total dissolved solids, sulfate, chloride, iron, nitrate, nitrite and ammonia nitrogen are selected as the distinguishing factors. Taking 28 sets of groundwater data as samples, a distance discriminant analysis(DDA)prediction model is established, the samples are classified using the linear discriminant function obtained, and the model is tested by back-generation estimation. The model was applied to 14 sets of groundwater data in the goaf of Taoshuping Copper Mine in Dongchuan, Yunnan, and the model predictions were completely consistent with the actual results. The research shows that the accuracy of using distance discriminant analysis method to predict the quality of groundwater in the goaf of mines is relatively high. This article provides a new idea and method for the quality evaluation and prediction of groundwater in similar mines. |
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