基于主成分分析和熵权的水库生态系统健康评价——以海南省万宁水库为例

Assessment of aquatic ecosystem health based on principal component analysis with entropy weight: A case study of Wanning Reservoir(Hainan Island,China)

采用主成分分析(PCA)与熵权相结合的新方法,对万宁水库水生态系统健康进行评价,旨在检验该方法是否能解决传统的基于熵权法的水生态系统健康评价方法所存在的赋权重复问题.结果表明:2010—2012年,万宁水库的水生态系统健康状况整体呈变好趋势;年均水生态系统健康综合指数(EHCI)分别为0.534、0.617、0.634,健康状态评级分别为Ⅲ类(中等)、Ⅱ类(较好)、Ⅱ类(较好).该水库水生态系统健康状况存在季节性差异,但并没有明显的季节性变化规律.从EHCI的整体波动程度来看,其波幅逐渐变小,表明近年来万宁水库的水生态系统趋于相对稳定.新方法与传统方法的指标赋权对比表明,传统方法中相关性较强的溶解氧、化学需氧量、五日生化需要量、铵态氮4项指标的累计权重为0.382,而新方法中仅为0.179;说明PCA的引入有效解决了赋权重复的问题.营养状态指数与EHCI呈显著的负相关关系,说明PCA与熵权结合的新方法在解决了赋权重复的基础上,很好地保证了评价结果的准确性,适用于该水库水生态系统健康评价.

A new assessment method based on principal component analysis （PCA） and entropy weight for ecosystem health was applied to Wanning Reservoir, Hainan Island, China to investigate whether the new method could solve the overlap in weighting which existed in the traditional entropy weight-based method for ecosystem health. The results showed that, the ecosystem health status of Wanning Reservoir showed an improvement trend overall from 2010 to 2012; the means of ecosys- tem health comprehensive index （EHCI） in each year were 0. 534, 0.617, 0.634 for 2010, 2011 and 2012 respectively, and the ecosystem health status was Ⅲ （medium）, Ⅱ （good）, and Ⅱ（good） , respectively. In addition, the ecosystem health status of the reservoir displayed a weak seasonal variation. The variation of EHCI became smaller recently, showing that Wanning Reservoir tended to be relatively stable. Comparison of the weight of indices in the new and the traditional methods indicated that, the cumulative weight of the four indices （i. e. , DO, COD, BOD5 and NH4＋-N） had a stronger correlation of 0.382 for the traditional one than that （0. 178） for the new method. It suggested the application of PCA with entropy could avoid the overlap in weighting effec- tively. In addition, the correlation analysis between the trophic status index and EHCI showed sig- nificant negative correlation （P〈0.05）, indicating that the new method based on PCA with entropyweight could improve not only the assignment of weighting but also the accuracy of the results. The new method here is suitable for evaluating ecosystem health of the reservoir.