Water quality assessment using optimized CWQII in Taihu Lake

Abstract

To improve the rationality of weight allocation and weight proportion of different periods in the process of water quality assessment, the comprehensive water quality identification index (CWQII) model was optimized in this study. A new improved comprehensive water quality identification index (ICWQIIG) model based on game theory was established to combine subjective weight and objective weight. Based on ICWQIIG, an improved comprehensive water quality identification index (ICWQIIP) model with phased period combination weights was established to determine determined the weight proportion of phased periods was established. In this study, CWQII, ICWQIIG, and ICWQIIP were used to evaluate the water quality of seventeen sites in Taihu Lake in 2020. The models selected nine water quality parameters and six water quality indicators. The assessment results of water quality classification were between “slightly polluted” and “moderately polluted”. The pollution level on the east bank was lower than that on the west bank and north bank. Furthermore, it was also affected by seasonal change, water quality was worse in January and February but better in October and November. The mean value of Iwq calculated by CWQII, ICWQIIG, and ICWQIIP were 2.405, 2.833, and 3.000, respectively. The compared results showed that the ICWQIIG method can more representative identify the location of polluted water than CWQII. Moreover, the ICWQIIP method calculation results not only retained the representative polluted water samples in the ICWQIIG method but can also identify more pollution sites and worse polluted water bodies. Both ICWQIIG and ICWQIIP had high reliability and accuracy in assessment results, and ICWQIIP was more accurate under sufficient data conditions. This study can offer a scientific basis for local water resource management in Taihu Lake, while simultaneously proposing a science-based and valid methodology for the assessment of other similar water bodies.