A GM (1,1)-Markov Model for Forecasting CODMn in a Eutrophicated Lake

Many lakes in China have suffered from the eutrophication every year. Chemical oxygen demand (CODMn) is one of the main indexes that reflect lake eutrophication, so accurate simulation and forecast of CODMn can provide a scientific basis for decision-making of eutrophication control. In this paper, a GM(1,1)-Markov model is applied to forecast CODMn in Dianchi Lake, which is a seriously eutrophicated lake in southwestern China. The results show that the GM(1,1)-Markov model obtains 9 better simulated results among the total 14 simulated results and has a better reflection of actual fluctuation than the GM(1,1) model. With a satisfactory accuracy, the GM(1,1)-Markov model is simple to build and easy to use for predicting the trophic factors.