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Along with increasingly serious water pollution, water environmental problems have become major factors that hinder the sustainable development of our economy and society. Reliable evaluation of water quality and accurate prediction of water pollution indicators are the key links in water resource management and water pollution control. In this paper, the water quality data of Lanzhou Xincheng Bridge section in the Yellow River Basin and Sichuan Panzhihua Longdong section in the Yangtze River Basin were used to establish a water quality evaluation model and a prediction model. For the water quality evaluation model, we constructed the research samples by means of equal intervals and uniform distribution of interpolated water quality index data according to Environmental Quality Standards for Surface Water. The training samples were determined by a stratified sampling method, and the water quality evaluation model was established using a T-S fuzzy neural network. The experimental results show that the highest accuracy achieved by the evaluation model in water quality classification was 94.12%. With respect to the water quality prediction model, we propose ARIMA-WNN, which combines the autoregressive integrated moving average model (ARIMA) and a wavelet neural network (WNN) with the bat algorithm (BA) to determine the optimal weight of each individual model. The experimental results show that the highest prediction accuracy of ARIMA-WNN is 68.06% higher than that of the original model.

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With the rapid development of the social economy, the demand for water resources is gradually increasing, and the corresponding impact of water pollution is also becoming more severe. Therefore, the technology of sewage treatment is developing rapidly, but corresponding problems also arise. The requirements of energy conservation and emissions reduction under the goal of carbon neutrality and dual carbon pose a challenge to the traditional concept of sewage treatment, and there is an urgent need for low-carbon sewage treatment technology aiming at energy conservation, consumption reduction and resource reuse. This review briefly introduces conventional sewage treatment technology and low-carbon sewage treatment technology, and analyzes the research status and development trend of low-carbon sewage treatment technology in detail. The analysis and comparison of conventional and low-carbon sewage treatment technologies is expected to provide a theoretical basis for the practical engineering application of low-carbon sewage treatment technologyto achieve the goal of carbon neutrality. It is of great significance to promote the sustainable development of society and the economy.