Application of Bayes theorem in parameter identification for river water quality modeling
Bayes理论在河流水质模型参数识别中的应用

Parameter identification is one of the most important steps in water quality modelling. But it often happens that there is not enough data to support parameter identification, and thus it becomes dependent on the experience of the researchers to reduce the modelling risk to some extent. Bayes theorem makes it possible to quantify the experience of the researcher into the modelling. On the basis of the monitoring data of a river section, this paper identifies the parameters of a CSTR model, and the identification results are also analyzed. The verification shows that the identification results are reasonably acceptable.