Development and application of water environment assessment model for lithium mining area based on python

Abstract

Sixty-four surface water samples were selected to study the water quality around the lithium mining area in western Sichuan Province. Principal component analysis, in which 6 principal component indexes (Mn, Zn, As, Cl−, SO42−, NO3−) with cumulative contribution rate >85% were selected as the assessment index. Based on fuzzy mathematics, the membership function is used to determine the attribution of all indexes, and the pollution contribution rate is used to determine the index weight. Using the national standard (Environmental quality standards for surface water, GB3838-2002 and Quality standard for ground water, GB/T 14848-93) as a benchmark, a fuzzy comprehensive assessment model based on Python language was established to assess the water environment quality of the mining area. The result shows that the water environment classification of sixty-four sampling points in the mining area are all Grade I. This result indicates that the water environment quality of the mining area is very good, and the mineralization and mining engineering activities do not pollute the water environment around the mining area.