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Groundwater quality assessment based on rough sets attribute reduction and TOPSIS method in a semi-arid area, China

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Abstract

In order to enrich and improve the groundwater quality assessment system, a new coupled assessment model based on rough set attribute reduction and the technique for order preference by similarity to ideal solution (TOPSIS) was proposed. The proposed model was applied in the groundwater quality assessment of a semi-arid area, northwest China. The results show that most chemical indices except NH +4 , F−, and Mn meet the Standards for Drinking Water of China and the groundwater quality overall is good. All assessed water samples are found to be fit for human consumption according to the comprehensive assessment results. Rough set attribute reduction for groundwater quality assessment is practical. The assessment results after attribute reduction show a good consistency with those before attribute reduction. Rough set attribute reduction and TOPSIS evaluation coupled model is clear in ideas and simple in calculation, and evaluation results are reasonable as well. The coupled model can be applied to solve many multiple criteria decision making problems such as groundwater quality assessment.

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Acknowledgment

This work was jointly supported by the National Natural Science Foundation of China (grant no. 40772160) and Program for Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China (grant no. IRT0811). The authors appreciate the anonymous reviewers for their useful comments to improve quality of the study.

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  1. School of Environmental Science and Engineering, Chang’an University, No. 126, Yanta Road, Xi’an, 710054, China

    Peiyue Li, Jianhua Wu & Hui Qian

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  1. Peiyue Li
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  2. Jianhua Wu
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  3. Hui Qian
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Correspondence to Peiyue Li.

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Li, P., Wu, J. & Qian, H. Groundwater quality assessment based on rough sets attribute reduction and TOPSIS method in a semi-arid area, China. Environ Monit Assess 184, 4841–4854 (2012). https://doi.org/10.1007/s10661-011-2306-1

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  • DOI: https://doi.org/10.1007/s10661-011-2306-1

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