湘江流域水质特征及水污染经济损失估算

基于2008~2016年湘江流域内40个监测站点10项参数的月观测资料，运用水质指数法分析流域水质时空分异特征，并采用主成分分析和多元线性回归分析识别影响流域水环境演变的主要因素.在此基础上将水质、水量与水资源价值结合起来，利用改进的污染损失率法和模糊数学法，构建污染价值损失模型，定量估算流域水污染经济损失.结果表明，湘江流域水质总体以优为主，2008~2011年水质变差，2011年后水质逐渐改善，2015~2016年改善状况较为明显.在季节尺度上，枯水期水质最差，丰水期和平水期接近.流域主要污染物是Hg、Pb、TP、NH₄⁺-N和COD_Mn.经济发展是影响流域水质变化的主要驱动因素.污染价值损失结果表明，长沙和郴州损失量最大，湘潭、株洲和衡阳次之，娄底损失最小.在年际尺度上，2013年污染损失最高（297.04亿元），2008年最低（66.53亿元），总体上2008~2016年污染损失在波动中增加.

Characteristics of water quality and estimation of economic loss from water pollution in Xiangjiang River Basin

Based on monthly observations of 10 parameters at 40 monitoring sites in the basin during 2008~2016, the spatio-temporal variation characteristics were analyzed by employing water quality index method, and the main factors of water environment evolution were also identified using principal component analysis and multivariate linear regression analysis. Further, a pollution value loss model with consideration of water quality, quantity and its resource value was proposed using the improved pollution loss rate method and fuzzy mathematics method to quantitatively estimate the economic loss from water pollution in the basin. The water quality was generally excellent in Xiangjiang River Basin. Within the research period, the water quality deteriorated first from 2008 to 2011, then, gradually improved after 2011, especially in 2015 and 2016. Seasonally, the water quality was the worst in low-flow periods, and similar between moderate-flow periods and high-flow periods. The main pollutants in the basin were Hg、Pb、TP、 NH₄⁺-N and COD_Mn. Economic development was one of the main determining factors to the variation of water quality in the basin. The results of pollution value loss analysis indicated that Changsha and Chenzhou had the largest loss, followed by Xiangtan, Zhuzhou and Hengyang, and Loudi had the smallest loss. Annually, the pollution loss was the highest in 2013(29.704billion yuan) and the lowest in 2008(6.653billion yuan). In general, the pollution loss showed an increasing trend from 2008 to 2016 with annual fluctuations. Our results could provide scientific support and reference for the research of water pollution prevention and ecological compensation.