Analyzing and Predicting of Tianjin Coastal Water Quality by Fractional Theory

In this paper, a new method for analyzing and predicting the pollution characteristics of Tianjin coastal water quality was proposed through the study on the fractional theory, and this method was based on environmental monitoring data completely. Firstly, the COD values of recent years from the 9 monitoring points were gathered and normalized, and the 9 monitoring points are distributed on the Tianjin coastal marine. The COD values from the same monitoring point were regarded as an interval time series strictly. Secondly, the rescaled range analysis was used to analyze the pollution characteristics of COD time series. The Hurst exponents H of COD time series were computed and the results showed that the Hurst exponents were around 0.85. It proved that the coastal water quality pollution presented fractional characteristics. Thirdly, according to the periodicity and self-similarity of coastal water quality and the fractional collage theory, the fractional interpolation method which based on affine transform was used to find the iterated function system, whose attractor is close to the historical water quality data. Then the fractional predicting model was established according to the above iterated function system. Finally, the random iterated algorithm was used to find the attractor of each predicting period which could provide the predicting data according to the time values. The predicting results showed that the average prediction error was 24.4%. The fractional theory could analyze and predict the pollution characteristics of coastal water quality deeply and precisely. And the method proposed in this paper was practicable and could be the decision support for environmental management of coastal marine.