Groundwater quality evaluation model based on multi-scale fuzzy comprehensive evaluation and big data analysis method

The reasonable use of water resources has become an important issue for the sustainable development of humanity in the future. Many researches focus on groundwater quality inspection, but not groundwater quality assessment. This paper aims to study groundwater quality evaluation models based on multi-scale fuzzy comprehensive evaluation and big data analysis methods. We combines coarse-grained multi-scale fuzzy entropy and fuzzy comprehensive evaluation method to establish a groundwater quality evaluation model based on big data environment. The evaluation of groundwater samples from 327 test points in Huangpu District, Xuhui District, Hongkou District, and Putuo District of Shanghai was conducted. The results show that the overall condition of Shanghai groundwater is better, and more than 94% of samples qualified as drinking water sources. The method presented in this paper not only guarantees that the coarse-grained data on all scales are consistent with the length of the original data, but also avoids the phenomenon of data loss, which greatly improves the accuracy of subsequent algorithms.