水科学进展2012，Vol.23Issue(1)：74-79,6.DOI:32.1309.P.20120104.2012.008
资料缺失河道水质风险分析
Risk analysis of river water quality with incomplete data
摘要
Abstract
Incomplete data poses a challenge in river water quality risk analysis. Using the priori distribution of water quality indices and existing water quality data, a water quality model is established to dynamically simulate the concentrations of pollutants in the water. The statistical characteristics of the model parameters and super-parameters are estimated simultaneously using the Bayesian theory and the Gibbs sampling method. If the incomplete data are assumed to be missing completely at random, the proposed sampling method can provide large number of samples to the model parameter estimation. The substandard water risk analysis can thus be conducted by the model water quality. The result of a case study shows that the model is able to perform risk analysis of the river water quality with incomplete data, which provides a new approach to the risk analysis of water pollution.关键词
水质/风险分析/Bayes理论/Gibbs抽样方法Key words
water quality/ risk analysis/ Bayesian theory/ Gibbs sampling method分类
建筑与水利引用本文复制引用
顾文权,邵东国..资料缺失河道水质风险分析[J].水科学进展,2012,23(1):74-79,6.基金项目
高等学校博士学科点专顼科研基金资助项目(20100141120029) （20100141120029）
水利部公益性行业科研专项经费资助项目(201001003-6) （201001003-6）
