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    基于主成分分析和熵权法的新安江流域水质评价

    Evaluation of water quality in Xin'anjiang River Basin based on principal component analysis and entropy weight method

    • 摘要:
      研究目的 新安江流域是华东地区重要的生态安全屏障,其治理具有长期性、艰巨性、复杂性和反复性。科学评价流域水环境质量状况,识别重点污染区域和主要污染因子,可为流域生态环境整治提供重要依据。
      研究方法 以新安江流域88个监测点水质数据为基础,采用主成分分析法对水质评价指标体系进行优化,再运用熵权法计算各指标权重及各个监测点的水质综合指数,并结合GIS空间分析功能绘制了水质综合指数图。
      研究结果 88个监测点的水质综合指数范围为0.02~1.313,流域地表水环境质量总体较好,以Ⅲ类水为主,且浙江段水质好于安徽段。重点污染区域分布在休宁—歙县—徽州区一带,形成了潜口镇、岩寺镇—三村镇两个污染中心。TN、TP和NH3-N为流域主要污染指标,其中TN为全局型污染物,TP和NH3-N为区域型污染物。
      结论 主成分分析和熵权法结合的水质评价模型避免了评价指标的重复性以及权重赋值的主观性,能够有效评估复杂的水环境指标体系,具有较好的可行性和实用性。

       

      Abstract:
      This paper is the result of hydrogeological survey engineering.
      Objective The Xin'anjiang River Basin is an important ecological security barrier in East China, and its governance is long-term, arduous, complex, and repetitive. Scientifically evaluating the water environment quality of the basin and identifying the key polluted areas and major pollution factors could provide an important basis for promoting the improvement of the ecological environment of the river basin.
      Methods Based on the water quality data of 88 monitoring points of Xin'anjiang River basin, the principal component analysis method was used to optimize the evaluation index system of water quality, and then the entropy weight method was adopted to calculate the weight of each index and the comprehensive water quality index of each monitoring point. Moreover, the comprehensive index map of water quality was drawn by the spatial analysis function of GIS.
      Results The results show that the comprehensive index of 88 monitoring points ranged from 0.02-1.313, and the environmental quality of surface water in the basin was generally good, mainly for class Ⅲ. The water quality of Zhejiang section was better than that of the Anhui section. The key pollution area was distributed in the Xiuning-Shexian-Huizhou district, forming two pollution centers in Qiankou Town, Yansi Town-Sancun Town. Moreover, TN, TP and NH3-N were the main pollution indicators of the basin, where TN was a global pollutant, TP and NH3-N were regional pollutants.
      Conclusions The water quality evaluation model composed of principal component analysis and entropy weighting method avoids the repeated selection and the subjectivity of weight assignment for evaluation index, which could efficiently evaluate the complex index system of water environment and better reflect the actual spatial distribution of water quality. It is feasible and practical in water quality evaluation.

       

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