资源科学 ›› 2019, Vol. 41 ›› Issue (11): 2020-2031.doi: 10.18402/resci.2019.11.06

• 水资源 • 上一篇    下一篇

基于证据推理的流域水质综合评价法——以湘江水质评价为例

胡东滨1,3, 蔡洪鹏1(), 陈晓红1,3, 孟凡永1, 罗岳平2,3, 潘海婷2,3   

  1. 1. 中南大学商学院,长沙 410083
    2. 湖南省环境监测中心站,长沙 410014
    3. 湖南省两型社会与生态文明协同创新中心,长沙 410083
  • 收稿日期:2017-01-05 修回日期:2019-08-05 出版日期:2019-11-25 发布日期:2019-12-03
  • 通讯作者: 蔡洪鹏
  • 作者简介:胡东滨,男,湖南长沙人,教授,博士,主要从事环境大数据研究。E-mail:hdbin@163.com
  • 基金资助:
    国家自然科学基金项目(71431006);国家自然科学基金项目(91846301)

Comprehensive assessment of water quality based on evidential reasoning: Taking the Xiangjiang River as an example

HU Dongbin1,3, CAI Hongpeng1(), CHEN Xiaohong1,3, MENG Fanyong1, LUO Yueping2,3, PAN Haiting2,3   

  1. 1. Business school, Central South University, Changsha 410083, China
    2. Hunan Environmental Monitoring Center, Changsha 410014, China
    3. Resource-Conserving & Environment-Friendly Society and Ecological Civilization Collaborative Innovation Center of Hunan Province, Changsha 410083, China;
  • Received:2017-01-05 Revised:2019-08-05 Online:2019-11-25 Published:2019-12-03
  • Contact: CAI Hongpeng

摘要:

水质综合评价是水环境综合整治的重要基础性工作,通过科学准确的评价,才能对水质治理做出科学的治理规划和有效的治理措施。本文基于证据推理理论,提出了一种水质综合评价方法。通过建立水质综合评估模型和信度分布函数,将水质指标的监测值转化为各评估等级的置信度;结合证据推理的合成规则和算法,将隶属于同一评估等级的指标进行证据递归合成,计算出各评估等级的概率分布;并引入效用理论,实现水质的相互比较。本文以湘江为例,对其2011—2017年水质进行综合评估。同时,将本方法与水质评价中应用较为广泛的模糊综合评价法、灰色聚类法进行比较,结果显示,基于证据推理的水质综合评价法更加科学准确,能有效地反映水质的实际情况。本文对流域内不同空间、时间点水质的多指标数据融合和不确定性数据处理具有参考价值,也为湘江流域的水质精准治理和环境管理决策提供支持。

关键词: 水质综合评价, 水环境不确定性, 置信度评估, 证据组合规则, 证据推理, 效用理论, 湘江流域

Abstract:

Comprehensive evaluation of water quality is an important basic work in the integrated improvement of water environment. Reliable and accurate assessment facilitates the development of scientific management plan and effective control measures for water quality. This article proposes a comprehensive assessment method of water quality based on evidential reasoning. Through establishing a water quality comprehensive evaluation model and belief distribution function, the observed values of water quality indicators can be transformed into the confidence degree of each evaluation grade. Combining the synthesis rules and algorithms of evidential reasoning, the probability distribution of each evaluation grade is calculated by synthesizing recursively the indicators that belong to the same evaluation grade. Then the comparison of water quality is realized by introducing the utility theory. Finally, this article takes the Xiangjiang River as an example to comprehensively evaluate its water quality from 2011 to 2017, and compares this method with the fuzzy comprehensive evaluation method and grey clustering method, which have been widely used in water quality assessment. The results show that the comprehensive assessment method based on evidential reasoning is more accurate, and can effectively reflect the actual situation of water quality. This study is important in the multi-index data fusion and uncertainty data processing of water quality in different space and time, and also provides support for managing water quality precisely and for environmental management policy and decision making in the Xiangjiang River Basin.

Key words: comprehensive assessment of water quality, uncertainty of water environment, confidence degree assessment, combination rule of evidence, evidential reasoning, utility theory, Xiangjiang River Basin