Assessment of drinking water quality and health risk using water quality index and multiple computational models: a case study of Yangtze River in suburban areas of Wuhan, central China, from 2016 to 2021.

Water quality, increasingly recognized for its significant impact on health, is garnering heightened attention. Previous studies were limited by the number of water quality indicators and the duration of analysis. This study assessed the drinking water quality and its associated health risk in suburban areas of Wuhan, a city in central China, from 2016 to 2021. We collected 368 finished water samples and 1090 tap water samples and tested these for 37 different indicators. The water quality was evaluated using the water quality index, with trends over time analyzed via the Mann-Kendall test. Furthermore, an artificial neural network model was employed for future water quality prediction. Our findings indicated that the water quality in rural Wuhan was generally good and had an improvement from 2016 to 2021. The qualification and excellent rates were 98.91% and 86.81% for finished water, and 97.89% and 78.07% for tap water, respectively. The drinking water quality was predicted to maintain satisfactory in 2022 and 2023. Additionally, principal component analysis revealed that the primary sanitary issues in the water were poor sensory properties, elevated metal contents, high levels of dissolved solids, and microbial contamination. These issues were likely attributable to domestic and industrial waste discharge and aging water pipelines. The health risks associated with the long-term consumption of this water have been steadily decreasing over the years, underscoring the effectiveness of Wuhan's ongoing water management efforts.

Quality assessment and prediction of municipal drinking water using water quality index and artificial neural network: A case study of Wuhan, central China, from 2013 to 2019.

The sanitary security of drinking water is closely related to human health, but its quality assessment mainly focused on limited types of indicators and relatively restricted time span. The current study was aimed to evaluate the long-term spatial-temporal distribution of municipal drinking water quality and explore the origin of water contamination based on multiple water indicators of 137 finished water samples and 863 tap water samples from Wuhan city, China. Water quality indexes (WQIs) were calculated to integrate the measured indicators. WQIs of the finished water samples ranged from 0.24 to 0.92, with the qualification rate and excellent rate of 100 % and 96.4 %, respectively, while those of the tap water samples ranged from 0.09 to 3.20, with the qualification rate of 99.9 %, and excellent rate of 95.5 %. Artificial neural network model was constructed based on the time series of WQIs from 2013 to 2019 to predict the water quality thereafter. The predicted WQIs of finished and tap water in 2020 and 2021 qualified on the whole, with the excellent rate of 87.5 % and 92.9 %, respectively. Except for three samples exceeding the limits of free chlorine residual, chloroform and fluoride, respectively, the majority of indicators reached the threshold values for drinking. Our study suggested that municipal drinking water quality in Wuhan was generally stable and in line with the national hygiene standards. Moreover, principal component analysis illustrated that the main potential sources of drinking water contamination were inorganic salts and organic matters, followed by pollution from distribution systems, the use of aluminum-containing coagulants and turbidity involved in water treatment, which need more attention.