Improvement on Entropy Weighting Model in Groundwater Quality Evaluation

Abstract

Entropy weighting model (EWM) is a widely used weighting method in groundwater quality assessment. EWM assigns weight according to the information amount principle. For the indicator with a higher dispersion degree, a larger weight parameter is assigned; and vice versa. However, through multiple practical applications, we find that the conventional EWM often neglects the indicator with high pollution degree, for it only takes the statistics characteristics of the observation data into consideration, but ignores their practical meaning in aquatic environment management. To solve this problem, this study makes an improvement on the conventional EWM through introducing a pollution degree principle. And then, the improved EWM is applied into the groundwater quality evaluation in Suihua city as an illustration. The results show that: (i) the conventional EWM theory neglects the indicator with high pollution degree, and makes the synthetic assessment result distorted and over-optimistic. (ii) Through introducing a pollution degree principle, the improved EWM highlights the heavily polluted indicators and excludes the “zero weight” phenomenon, which makes the final comprehensive groundwater quality assessment much stricter and more reasonable. (iii) The comprehensive groundwater quality of Suihua city is “Marginal”, and its crucial pollutants are iron, manganese and ammonia nitrogen.