The stepwise DA identified five variables (chl-a, DO, TKN, TP and WT) as the most important discriminating variables. Table 2 shows that the first function in the stepwise DA was perfectly correlated with temperature (coefficient = 1.000), and then mostly correlated with DO (coefficient = 0.613). Classification functions (CFs) and the classification matrices (CMs) obtained from standard and stepwise modes of DA are shown in Tables 3 and 4. In the standard mode, all 12 variables were included to construct CFs which correctly classified 95.3% of the original grouped cases. In the stepwise mode, the DA correctly assigned 93.2% of the cases using only five discriminating variables. Therefore, the temporal DA results of the stepwise mode suggested that chl-a, DO, TKN, pH, and WT were the most significant parameters for discriminating differences between the wet season and dry season, and could be used to explain most of the expected temporal variations in water quality.