基于遗传算法的次级河流回水段水质模型多参数识别  

Parameters identification of water quality model in branch backwater reach based on genetic algorithm

作　　者：罗固源[1] 郑剑锋[1] 许晓毅[1] 曹佳[2] 舒为群[2] 

机构地区：[1]重庆大学三峡库区生态环境教育部重点实验室,重庆400045 [2]第三军医大学军事预防医学院,重庆400038

出　　处：《中国环境科学》2009年第9期962-966,共5页China Environmental Science

基　　金：科技部国际合作项目(2007DFA90660);重庆市科技攻关计划项目(2006AB7020;2006AA7003;2008BB7305)

摘　　要：根据长江次级河流临江河回水段的实际情况,建立一维水质模型,模型中的各变化项采用有限差分法(FDM)进行离散,以回水段水体中COD和NH3-N的实测资料为基础,利用自适应遗传算法(AGA)对2种污染物的纵向离散系数及一级降解系数进行反演计算,得出回水段COD和NH3-N的纵向离散系数分别为0.5227,0.5196km2/h,一级降解系数分别为0.0342,0.0367h-1;计算值与实测值吻合较好,表明FDM-AGA方法能较好地运用于次级河流回水段水质模型的多参数识别.Taking Linjiang River which is a branch of Yangtze River as the research object, one-dimensional water quality model of its backwater reach was created. Finite difference method （FDM） was applied to disperse the variational items of model, water quality model parameters were obtained by adaptive genetic algorithm （AGA）. The dispersion coefficients of COD and NH3-N were 0.5227, 0.5196km^2/h, the degradation coefficients of COD and NH3-N were 0.0342, 0.0367h^- 1. The model＇s simulated values were in agreement with the experimental value, suggesting the method of FDM-AGA can be used in water quality model parameter identification of branch backwater reach.

关 键 词：次级河流 回水段 水质模型 参数识别 遗传算法 

分 类 号：X143[环境科学与工程—环境科学] X11