摘要
用三角模糊数表征参评的水质指标浓度,并进行α截集处理,将经过处理的区间数代入传统的贝叶斯水质模型,建立了三角模糊数优化的贝叶斯水质模型评价方法。该方法综合了三角模糊数和贝叶斯水质模型的共同优点,考虑了水质监测过程中的误差,通过计算各采样点水质对不同水质级别的隶属度,再判定水质级别。将该方法应用于太湖竺山湾缓冲带湿地,结果表明：竺山湾缓冲带湿地水体水质为Ⅲ-Ⅳ类,未能达到Ⅰ类水质目标的要求;水体TN和COD污染较严重,在缓冲带生态建设和功能修复工作中应重点关注氮和有机物污染。
Concentrations of water quality indicators were expressed with triangular fuzzy numbers. Interval numbers were obtained using acut set technology. Triangular fuzzy numbers optimized Bayesian water quality model assessment method was established by introducing interval numbers into conventional Bayesian model and used to evaluate the water quality of Zhushan Bay buffer zone wetland of Taihu Lake. The method combines the advantages of triangular fuzzy numbers and Bayesian water quality model, considering the error of water quality monitoring process. The water quality level is obtained according to the membership degree. The results indicated that the water quality of Zhushan Bay buffer zone wetland distributed Grade Ⅲ-Ⅳ, which failed to reach the goal of Grade Ⅰ . TN and COD pollution in Zhushan Bay buffer zone wetland was relatively serious,so the nitrogen and organic matters should be paid attention to in ecological construction and functional restoration.
出处
《环境污染与防治》
CAS
CSCD
北大核心
2016年第11期7-14,共8页
Environmental Pollution & Control
基金
国家水体污染控制与治理科技重大专项(No.2012ZX07101-009)
关键词
三角模糊数
贝叶斯水质模型
竺山湾
水质评价
triangular fuzzy numbers
Bayesian water quality model
Zhushan Bay
water quality assessment
