基于主成分分析法的新乡市地下水水质评价

Groundwater quality assessment in Xinxiang City based on principal component analysis

以新乡市7个地下水水质监测断面为研究对象,采用主成分分析法分析了影响地下水水质的主要因素,并对断面水质进行排名。结果表明,使用主成分分析法,可将6个水质指标综合为2个主成分进行解释,解释率为96.464%,水质综合控制指标为总硬度、溶解性固体、硫酸盐和锰。主成分分析法预测结果与文献中使用的熵权集对分析法预测结果很好的吻合,说明主成分分析法适合预测新乡市地下水水质。主成分分析法还有效弥补了熵权集对分析法无法判断同一水质等级下不同断面水质优劣的缺陷,说明两种模型结合使用后综合预测结果要比单一预测模型更加可靠。

Water quality was assessed by principal component analysis(PCA),and the main indices affecting the groundwater quality were analyzed for seven groundwater quality monitoring sections in Xinxiang City.The results indicate that water quality could be explained by two main components instead of six water quality indices in PCA,and the interpretation rate was 96.464%.The comprehensive control indices are total hardness,dissolved solids,sulfate and manganese.The predicted results of PCA are consistent with that of the set pair analysis based on entropy weight(SPAEW)used in the literature,indicating that PCA is suitable for groundwater quality assessment in Xinxiang City.PCA can remedy the limitation that SPAEW can't provide the quality orders of groundwater sites with the same water quality grade,indicating that the predicted results of the two models combined are more reliable than that of the single predictive model.