The significance of the fluctuation and randomness of the time series of each pollutant in environmental quality assessment is described for the first time in this paper. A comparative study was made of three different computing methods: the same starting point method, the striding averaging method, and the stagger phase averaging method. All of them can be used to calculate the
Hurst index, which quantifies fluctuation and randomness. This study used real water quality data from Shazhu monitoring station on
Taihu Lake in
Wuxi, Jiangsu Province. The results show that, of the three methods, the stagger phase averaging method is best for calculating the
Hurst index of a pollutant time series from the perspective of statistical regularity.