title: An integrated model for simulating and diagnosing the water quality based on the system dynamics and Bayesian network.
abstract: An integrated model for simulating and diagnosing water quality based on the system dynamics and Bayesian network (BN) is presented in the paper. The research aims to connect water monitoring downstream with outlet management upstream in order to present an efficiency outlet management strategy. The integrated model was built from two components: the system dynamics were used to simulate the water quality and the BN was applied to diagnose the reason for water quality deterioration according to the water quality simulation. The integrated model was applied in a case study of the Songhua River from the Baiqi section to the Songlin section to prove its reasonability and accuracy. The results showed that the simulation fit to the variation trend of monitoring data, and the average relative error was less than 10%. The water quality deterioration in the Songlin section was mainly found to be caused by the water quality in the upper reach and Hadashan Reservoir drain by using the diagnosis function of the integrated model based on BN. The relevant result revealed that the integrated model could provide reasonable and quantitative support for the basin manager to make a reasonable outlet control strategy to avoid more serious water quality deterioration.
authors.affiliation: Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of Environment and Resources, Jilin University, Changchun, Jilin Province 130012, China E-mail: shuowang@jlu.edu.cn.
authors.forename: Gengzhe
authors.initials: G
authors.lastname: Wang
authors.affiliation: Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of Environment and Resources, Jilin University, Changchun, Jilin Province 130012, China E-mail: shuowang@jlu.edu.cn.
authors.forename: Shuo
authors.initials: S
authors.lastname: Wang
authors.affiliation: Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of Environment and Resources, Jilin University, Changchun, Jilin Province 130012, China E-mail: shuowang@jlu.edu.cn.
authors.forename: Qiao
authors.initials: Q
authors.lastname: Kang
authors.affiliation: Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of Environment and Resources, Jilin University, Changchun, Jilin Province 130012, China E-mail: shuowang@jlu.edu.cn.
authors.forename: Haiyan
authors.initials: H
authors.lastname: Duan
authors.affiliation: Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of Environment and Resources, Jilin University, Changchun, Jilin Province 130012, China E-mail: shuowang@jlu.edu.cn.
authors.forename: Xian'En
authors.initials: X
authors.lastname: Wang
mesh_terms: D001499:Bayes Theorem; D004784:Environmental Monitoring / Q000379:methods; D008962:Models, Theoretical; D045483:Rivers; D014876:Water Pollution / Q000032:analysis; D060753:Water Quality