Combined risk prediction in the water environment based on an MS-AR model and Copula theory

Making a quantitative prediction on the combined risk of the water body is helpful for the objective evaluation of the water environment system's state of health, and also has important results for the water environment system's safety management. In this paper, the Markov status switching theory (Markov Switching, MS), Monte Carlo method (Monte Carlo, MC) and Copula theory were used together, to establish a method for the water environment system's combined risk assessment. This method firstly using MS theory established the water quality time series' autoregression model (MS-AR); then the MS-AR model and MC method were used to carry out random simulation on the water quality time series; finally, multi-dimensional joint distribution among random simulation results were established by Copula function, and this distribution utilized to make a quantitative analysis of the water environment system's combined risk. By means of the above combined risk analysis model, the combined risk prediction and correlation analysis of the water quality of the Guohe River bridge section were carried out. The results showed that the total phosphorus (TP) and 5-day biochemical oxygen demand (BOD5) had an important effect on the Guohe River water environment's state of health, and there was a strong positive correlation between TP and BOD5.