基于改进灰色关联度聚类的海水质量状况评价方法研究:以大亚湾为例

Seawater quality assessment method based on improved grey relational degree clustering: a case study of Daya Bay

  • 摘要: 海洋环境质量评价是开展海洋环境管理的依据,而海洋环境评价的精度取决于海洋环境的监测和评价水平。为建立科学有效的指标评价体系,准确分析目前大亚湾西部的海水质量状况,通过改进灰色关联度聚类,将其与层次聚类结合起来,在大亚湾核电海域开展了海水质量评价探索研究。结果表明,在海水质量状况相对评价中,一类站点占比20.83%,二类站点占比66.67%,三类站点占比12.5%,总体结果表现良好。将4个季节进行对比发现,平均绝对关联度为夏季 (0.747 9) >冬季 (0.734 5) >春季 (0.729 0) >秋季 (0.709 7),夏季海水质量状况相对较好,秋季表现较差。根据评价结果可将大亚湾24个站点分成3个区域,而这3个区域的划分与大亚湾周边实际生产生活状况及实地踏勘情况相符,体现了评价方法的可操作性。

     

    Abstract: Marine environmental quality assessment is the basis of marine environmental management, and its accuracy depends on the level of marine environmental monitoring and evaluation. In order to establish a scientific and effective indicator evaluation system and analyze the current seawater quality situation in western Daya Bay accurately, we carried out an exploration and research on sea water quality assessment in Daya Bay nuclear power sea area by improving grey relational degree clustering and combining it with hierarchical clustering. The evaluation results show that for relative evaluation of seawater quality, the proportions of Class I, Class II and Class III stations were 20.83%, 66.67% and 12.5%, respectively, which was an overall good result. Comparing the the four seasons, it is found that the average absolute correlation followed a descending order of summer (0.747 9) > winter (0.734 5) > spring (0.729 0) > autumn (0.709 7). The seawater quality was better in summer but worse in autumn. According to the evaluation results, the 24 stations in Daya Bay can be divided into three areas, which is consistent with the actual production, living conditions around Daya Bay and field survey, proving the operability of this evaluation method.

     

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