Suppr超能文献

基于复合函数的水质评价改进型熵权模型。

The improved entropy weighting model in water quality evaluation based on the compound function.

机构信息

College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, 210098, China.

Key Laboratory of Poyang Lake Environment and Resource Utilization, Ministry of Education, Nanchang University, Nanchang, 330031, China.

出版信息

Environ Monit Assess. 2022 Aug 10;194(9):662. doi: 10.1007/s10661-022-10304-4.

Abstract

Entropy weight model (EWM) is widely used in water quality evaluation. In the conventional EWM, the weight is a monotone increasing function of the dispersion degree. However, this weighting principle often neglects the heavily polluted indicators. To solve this problem, an improved EWM is designed, in which the weight of the indicator is a compound function of its dispersion degree and pollution degree. In the clean domain, the weight increases with the dispersion degree, while in the polluted domain, the weight decreases with the dispersion degree. And for the same dispersion degree, the larger the pollution degree is, the higher the weight is, and vice versa. Subsequently, the improved EWM is applied to the water quality evaluation of Wucheng Wetland in Poyang Lake, China. Results are as follows: (i) For TP, COD, and NH-N, their dispersion degrees are 0.001, 0.158, and 0.084; and their pollution degrees are 0.971, 0.277, and 0.281, respectively. (ii) According to the improved EWM, the weights of TP, COD, and NH-N are 0.613, 0.197, and 0.190, respectively. (iii) The comprehensive water quality indices of estuary region, wetland region, and the central lake area are 32.5, 30.9, and 35.6, respectively, all of which belong to a "bad" grade. The water environment of Wucheng Wetland suffered serious damage of phosphorus, and the ecosystem faced a high threat. (iv) Compared with the conventional EWM, the improved EWM highlights the importance of polluted indicators, which makes the comprehensive evaluation results more rigorous and reasonable.

摘要

熵权模型(EWM)广泛应用于水质评价。在传统的 EWM 中,权重是离散度的单调递增函数。然而,这种加权原理往往忽略了污染严重的指标。为了解决这个问题,设计了一种改进的 EWM,其中指标的权重是其离散度和污染度的复合函数。在清洁域中,权重随离散度增加而增加,而在污染域中,权重随离散度减小而减小。对于相同的离散度,污染度越大,权重越高,反之亦然。随后,将改进的 EWM 应用于中国鄱阳湖五城湿地的水质评价。结果如下:(i)对于 TP、COD 和 NH-N,其离散度分别为 0.001、0.158 和 0.084;其污染度分别为 0.971、0.277 和 0.281。(ii)根据改进的 EWM,TP、COD 和 NH-N 的权重分别为 0.613、0.197 和 0.190。(iii)河口区、湿地区和中心湖区的综合水质指数分别为 32.5、30.9 和 35.6,均属于“差”级。五城湿地的水环境受到磷的严重破坏,生态系统面临高威胁。(iv)与传统 EWM 相比,改进的 EWM 突出了污染指标的重要性,使综合评价结果更加严谨合理。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验