论文总字数:14806字
摘 要
近海与人类的生产生活活动的密切相关,直接决定其能为人类提供着多种资源和各种重要的生态、环境服务功能,其水质优劣与否也直接关系到人类社会的可持续发展。本文以海洲湾近岸海域为例,为探明该区域水环境质量状况,运用本文建立的基于主成分分析的改进投影寻踪聚类评价模型对海洲湾近岸海域13个监测点的水质状况进行分析,结果表明,13个监测点中,水质状况维持在一类、二类、三类级别的分别占30.77%、30.77%以及38.46%,未有点位处于四类及以上级别。从整体上看,海洲湾近岸海域水体质量不能令人满意,而且它还可能会继续恶化。另为判别该方法的有效性,采用模糊综合评价法对其加以验证,发现2种方法的评价结果较为一致,从而初步证明了应用基于主成分分析的改进投影寻踪聚类评价模型评估海洲湾近岸海域水质的状况具有一定的合理性。关键词:评价标准,水质,投影寻踪聚类评价模型,主成分分析法,模糊综合评价法,海洲湾近岸海域
Abstract:Offshore water and human production and life activities are closely related, this determined its direct for human resources and provide a variety of various important ecological and environmental service function, the water quality is bad or not directly related to the sustainable development of the human society. In this paper, the coastal water area of Haizhou Bay is taken as a case study, to verify the water quality condition of this area, we used the improved projection pursuit cluster evaluation model based on principal component analysis method to analyze the water quality condition of 13 monitoring points in the coastal waters of Haizhou Bay. The result showed that in the 13 monitoring points in the coastal waters of Haizhou Bay, water quality condition maintained in the first class level accounted for 30.77%, the second class level accounted for 30.77% and 38.46% for the third class level, and monitoring points with no point belonged to the fourth class level. In general, the water quality condition of coastal waters of Haizhou Bay was not good and it is likely to be even worse. Apart from that, to judge the validity of this method, we adopted fuzzy comprehensive evaluation method to test and prove, and then we found that the results of the two methods were similar. Therefore, it preliminary proved that the improved projection pursuit cluster evaluation model based on principal component analysis method is of rationality when it is used to analyze the water quality condition.
Keywords:Assessment standard, water quality, projection pursuit cluster evaluation model, principal component analysis method, fuzzy comprehensive evaluation method, the coastal water area of Haizhou Bay
目 录
1 引言 6
2 监测数据的获取 6
3 海洲湾水质现状分析 7
4 海洲湾近岸海域水体质量综合评价 8
4.1 投影寻踪聚类评价模型 8
4.1.1 基本步骤 8
4.1.2 等级评价标准 11
4.1.3 评价结果 11
4.2 验证方法——模糊综合评价法 11
4.2.1 确定评价指标 12
4.2.2 建立模糊关系矩阵R 12
4.2.3 建立权重集 13
4.3 比较分析 14
结 论 16
参考文献 17
致 谢 19
1 引言
海洲湾位置处于江苏省最北端的黄海之滨,东以岚山头与连云港外的东西连岛的连线为界与黄海相通,面积约820km2,是我国八大渔场之一,沿岸有十余条河注入海区,年径流量为17×108m3[1]。《中国海洋环境质量公报》显示,2011年[2]海洲湾近岸海域海水水质污染进一步加剧,陆源污染物污染严重,并导致赤潮多次发生。因此,对海洲湾近岸海域的水质状况进行评估就显得尤为重要,故本文拟采用基于主成分分析的改进投影寻踪聚类评价模型对海洲湾近岸海域水环境质量进行评价,依据13个监测点水质参数的实际监测值,得出各监测点的水质类别,从而可为海洲湾近岸海域水环境质量的保护提供一定的参考。
2 监测数据的获取
布点、采样、样品保存及分析方法均采用国家海洋局颁布的海洋监测规范规定的方法,具体分春、夏、秋、冬4个季节在海州湾近岸海域监测点位上进行采样,最终分析数据取4个季节的平均值。采样的具体站位编号及分布见表1和图1。
表1 海洲湾近岸海域监测点坐标
序号 | 站位 | 经度 | 纬度 |
1 | Js01 | 119°30′37.5″ | 35°10′19.8″ |
2 | Js02 | 120°23′58.0″ | 35°09′58.2″ |
3 | Js03 | 119°18′12.9″ | 34°59′16.7″ |
4 | Js04 | 119°44′57.7″ | 34°59′36.4″ |
5 | Js05 | 120°11′38.2″ | 35°00′44.8″ |
6 | Js06 | 119°45′33.4″ | 34°39′40.5″ |
7 | Js07 | 120°28′42.4″ | 34°39′05.0″ |
8 | Js08 | 120°09′44.1″ | 34°28′20.8″ |
9 | Js09 | 120°39′04.0″ | 34°30′15.6″ |
10 | Js10 | 120°28′19.5″ | 34°09′59.8″ |
11 | Js11 | 120°54′04.9″ | 34°10′42.1″ |
12 | Js12 | 120°44′55.3″ | 33°59′45.2″ |
13 | Js13 | 121°04′40.4″ | 34°01′26.7″ |
图1 海洲湾近岸海域监测点分布(Ⅰ:临洪河;Ⅱ:灌河;Ⅲ:射阳河)
3 海洲湾水质现状分析
依据资料获取的情况,并综合考虑海洲湾近岸海域的具体状况,该区域水质现状的初步分析主要基于DO、SS、TOC、TN、TP、活性磷酸盐(Activated phosphate, AP)6个参数。海洲湾近岸海域13个监测点包含SS、DO等参数的监测结果见图2。
(a) (b)
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