| 基于三角模糊数-贝叶斯方法的九洲江水环境质量评价 |
| Water Quality Assessment of Jiuzhou River Based on the Integrated Method of Triangular Fuzzy Numbers and Bayesian Network |
| 投稿时间：2016-09-30 修订日期：2019-01-14 |
| DOI：10.15928/j.1674-3075.2019.02.003 |
| 中文关键词:三角模糊数 贝叶斯 九洲江 水质评价 |
| 英文关键词:triangular fuzzy numbers Bayesian theory Jiuzhou River water quality assessment |
| 基金项目:广西社会科学重点课题（GXSK201605）；广西科技计划项目 (1598014-3) ；广西自然科学基金重大项目（2013GXNSFEA053001） |
|
| 摘要点击次数: 2232 |
| 全文下载次数: 869 |
| 中文摘要: |
| 为更为全面考察水质评价过程中的不确定性，将模糊集理论和贝叶斯理论引入河流水质评价中，建立了三角模糊数-贝叶斯方法的水环境质量评价模型，并选取2016年7月九洲江跨省交界处5个断面的溶解氧、生化需氧量、高锰酸盐指数、氨氮、总磷作为水质评价因子，将该模型应用于九洲江跨省段的水质评价中。结果表明，九洲江文车桥、圭地河下游1km、温水浪、山角、石角蟠龙桥断面水质区间数分别为[3.320,3.365]、[3.120,3.179]、[3.178,3.196]、[3.432,3.428]、[3.404,3.470]，均在[3,4]区间范围，为III类水质；断面水质优劣排序为：石角蟠龙桥＞山角＞文车桥＞温水浪＞圭地河下游1km。该模型与综合污染指数法相比，断面水质优劣排序情况一致，除圭地河下游1km断面外，其他断面的水质评价结果也一致。由于模型计算过程中考虑了历史先验信息，并采用了三角模糊数及区间数的结果表达方式，有利于更客观反映流域水质状况。 |
| 英文摘要: |
| With increasing economic development and population growth in China, water pollution, water security and shortage of water resources have become issues of concern. To date, few studies have addressed both the uncertainties of model structure and parameterization when assessing water quality. As a result, the accuracy and comprehensiveness of the assessment results is compromised. This study aimed to investigate the uncertainties in the process of water quality assessment. An integrated fuzzy Bayesian water quality evaluation model has been developed and the fuzzy set and Bayesian analysis were introduced in this study. Water quality parameters included in the assessment included dissolved oxygen (DO), biochemical oxygen demand (BOD5), permanganate index (CODMn), ammonia nitrogen (NH3-N) and total phosphorus (TP). Approximately 30 water samples were collected from the Jiuzhou River within the trans-provincial basin areas in July 2016. The integrated fuzzy Bayesian water quality evaluation model was then used to evaluate water quality based on the monitoring results. The water quality interval numbers at Wenche Bridge, Guidi River 1000m downstream, Wenshuilang, Shanjiao and Shijiaopanlong Bridge monitoring sites were, respectively, [3.320, 3.365], [3.120, 3.179], [3.178, 3.196], [3.432, 3.428] and [3.404, 3.470]. Water quality in all sections was Class III according to water quality evaluation standards. The order of sections, in order of water quality was Shijiaopanlong Bridge > Shanjiao > Wenche Bridge > Wenshuilang > Guidi River 1000m downstream. Compared with water quality evaluation results based on the comprehensive pollution index, ranking was the same and the water quality classification was consistent for all monitoring sections, except for Guidi River 1000m downstream. In conclusion, the triangular fuzzy number model of assessment was shown to have a strong model structure and mitigated model parameter uncertainties. The assessment results obtained using this method are therefore more objective for evaluating water quality. |
| 邓渠成,许桂苹,尹娟,滕云梅,黄玉清,王晓飞,陈洋,夏新建.2019.基于三角模糊数-贝叶斯方法的九洲江水环境质量评价[J].水生态学杂志,40(2):14-19. |
| 查看全文 查看/发表评论 下载PDF阅读器 HTML |
|
|
|
