Groundwater quality evaluation based on dynaset pair analysis model
HE Fujuan1*, LI Wangcheng2, YAN Wenjie1
1.College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, Jiangsu 210098, China; 2.School of Civil Engineering and Hydraulic Engineering, Ningxia University, Yinchuan, Ningxia 750021, China
Abstract：In terms of the drawback such as relatively fixed weights for evaluation indexes in existing water quality evaluation methods, a water quality evaluation method was proposed based on variable weights. Firstly, a multi-index groundwater quality evaluation system was established. Then, entropy weight method and analytic hierarchy process were used to calculate the objective and subjective weights, respectively. The two weights decided were used to determine the variable weights of an index, which could vary with index itself. Thirdly, the connection number in dynaset pair analysis was extended to 5 from 3, and the variable weights was introduced into this improved set pair analysis model; Eventually, a variable weight-based set pair analysis model was developed to evaluate groundwater quality. This model was applied to assess the quality of groundwater in Dawukou District, Shizuishan of Ningxia. Results show that the quality of the water at monitoring points 1, 2 and 5 is in level I but in level III at monitoring points 3, 4, 6 and 7. These evaluations have accounted for geological, hydrogeological conditions and human activities in the studied areas and are verified to be scientific and reasonable. In comparison with the comprehensive evaluation, attribute recognition and fuzzy matter-element methods, the result evaluated by variable weight set analysis model is more objective and reasonable, and has better practicability and scientificity.
何福娟*, 李王成, 闫文杰. 基于动态集对分析模型的地下水水质评价[J]. 排灌机械工程学报, 2018, 36(5): 433-438.
HE Fujuan*, LI Wangcheng, YAN Wenjie. Groundwater quality evaluation based on dynaset pair analysis model. Journal of Drainage and Irrigation Machinery Engin, 2018, 36(5): 433-438.
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