Water quality assessment using optimized CWQII in Taihu Lake

Fei Ding; Wenjie Zhang; Liangyao Chen; Zongguang Sun; Wenpan Li; Cong-Yun Li; Mingcen Jiang

doi:10.1016/j.envres.2022.113713

Water quality assessment using optimized CWQII in Taihu Lake

Environ Res. 2022 Nov;214(Pt 1):113713. doi: 10.1016/j.envres.2022.113713. Epub 2022 Jun 25.

Authors

Fei Ding¹, Wenjie Zhang¹, Liangyao Chen¹, Zongguang Sun², Wenpan Li², Cong-Yun Li³, Mingcen Jiang⁴

Affiliations

¹ Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering, College of Architecture and Civil Engineering, Beijing University of Technology, Beijing, 100124, China.
² State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring, China National Environmental Monitoring Centre, Beijing 100012, China.
³ State Grid Beijing Economic Research Institute, Beijing 100055, China.
⁴ State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring, China National Environmental Monitoring Centre, Beijing 100012, China. Electronic address: jiangmc@cnemc.cn.

PMID: 35764128
DOI: 10.1016/j.envres.2022.113713

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 (ICWQII_G) model based on game theory was established to combine subjective weight and objective weight. Based on ICWQII_G, an improved comprehensive water quality identification index (ICWQII_P) model with phased period combination weights was established to determine determined the weight proportion of phased periods was established. In this study, CWQII, ICWQII_G, and ICWQII_P 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 I_wq calculated by CWQII, ICWQII_G, and ICWQII_P were 2.405, 2.833, and 3.000, respectively. The compared results showed that the ICWQII_G method can more representative identify the location of polluted water than CWQII. Moreover, the ICWQII_P method calculation results not only retained the representative polluted water samples in the ICWQII_G method but can also identify more pollution sites and worse polluted water bodies. Both ICWQII_G and ICWQII_P had high reliability and accuracy in assessment results, and ICWQII_P 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.

Keywords: Game theory; ICWQII(P); Phased period weight; Spatiotemporal variation; Taihu lake.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

China
Environmental Monitoring
Lakes*
Reproducibility of Results
Water Pollutants, Chemical*
Water Pollution
Water Quality

Substances

Water Pollutants, Chemical